WorldWideScience

Sample records for hybrid intelligent methodology

  1. Hybrid intelligent methodology to design translation invariant morphological operators for Brazilian stock market prediction.

    Science.gov (United States)

    Araújo, Ricardo de A

    2010-12-01

    This paper presents a hybrid intelligent methodology to design increasing translation invariant morphological operators applied to Brazilian stock market prediction (overcoming the random walk dilemma). The proposed Translation Invariant Morphological Robust Automatic phase-Adjustment (TIMRAA) method consists of a hybrid intelligent model composed of a Modular Morphological Neural Network (MMNN) with a Quantum-Inspired Evolutionary Algorithm (QIEA), which searches for the best time lags to reconstruct the phase space of the time series generator phenomenon and determines the initial (sub-optimal) parameters of the MMNN. Each individual of the QIEA population is further trained by the Back Propagation (BP) algorithm to improve the MMNN parameters supplied by the QIEA. Also, for each prediction model generated, it uses a behavioral statistical test and a phase fix procedure to adjust time phase distortions observed in stock market time series. Furthermore, an experimental analysis is conducted with the proposed method through four Brazilian stock market time series, and the achieved results are discussed and compared to results found with random walk models and the previously introduced Time-delay Added Evolutionary Forecasting (TAEF) and Morphological-Rank-Linear Time-lag Added Evolutionary Forecasting (MRLTAEF) methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

  2. Hybrid intelligent engineering systems

    CERN Document Server

    Jain, L C; Adelaide, Australia University of

    1997-01-01

    This book on hybrid intelligent engineering systems is unique, in the sense that it presents the integration of expert systems, neural networks, fuzzy systems, genetic algorithms, and chaos engineering. It shows that these new techniques enhance the capabilities of one another. A number of hybrid systems for solving engineering problems are presented.

  3. Intelligent systems engineering methodology

    Science.gov (United States)

    Fouse, Scott

    1990-01-01

    An added challenge for the designers of large scale systems such as Space Station Freedom is the appropriate incorporation of intelligent system technology (artificial intelligence, expert systems, knowledge-based systems, etc.) into their requirements and design. This presentation will describe a view of systems engineering which successfully addresses several aspects of this complex problem: design of large scale systems, design with requirements that are so complex they only completely unfold during the development of a baseline system and even then continue to evolve throughout the system's life cycle, design that involves the incorporation of new technologies, and design and development that takes place with many players in a distributed manner yet can be easily integrated to meet a single view of the requirements. The first generation of this methodology was developed and evolved jointly by ISX and the Lockheed Aeronautical Systems Company over the past five years on the Defense Advanced Research Projects Agency/Air Force Pilot's Associate Program, one of the largest, most complex, and most successful intelligent systems constructed to date. As the methodology has evolved it has also been applied successfully to a number of other projects. Some of the lessons learned from this experience may be applicable to Freedom.

  4. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  5. Response to traumatic brain injury neurorehabilitation through an artificial intelligence and statistics hybrid knowledge discovery from databases methodology.

    Science.gov (United States)

    Gibert, Karina; García-Rudolph, Alejandro; García-Molina, Alberto; Roig-Rovira, Teresa; Bernabeu, Montse; Tormos, José María

    2008-01-01

    Develop a classificatory tool to identify different populations of patients with Traumatic Brain Injury based on the characteristics of deficit and response to treatment. A KDD framework where first, descriptive statistics of every variable was done, data cleaning and selection of relevant variables. Then data was mined using a generalization of Clustering based on rules (CIBR), an hybrid AI and Statistics technique which combines inductive learning (AI) and clustering (Statistics). A prior Knowledge Base (KB) is considered to properly bias the clustering; semantic constraints implied by the KB hold in final clusters, guaranteeing interpretability of the resultis. A generalization (Exogenous Clustering based on rules, ECIBR) is presented, allowing to define the KB in terms of variables which will not be considered in the clustering process itself, to get more flexibility. Several tools as Class panel graph are introduced in the methodology to assist final interpretation. A set of 5 classes was recommended by the system and interpretation permitted profiles labeling. From the medical point of view, composition of classes is well corresponding with different patterns of increasing level of response to rehabilitation treatments. All the patients initially assessable conform a single group. Severe impaired patients are subdivided in four profiles which clearly distinct response patterns. Particularly interesting the partial response profile, where patients could not improve executive functions. Meaningful classes were obtained and, from a semantics point of view, the results were sensibly improved regarding classical clustering, according to our opinion that hybrid AI & Stats techniques are more powerful for KDD than pure ones.

  6. Recent Advances on Hybrid Intelligent Systems

    CERN Document Server

    Melin, Patricia; Kacprzyk, Janusz

    2013-01-01

    This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algo...

  7. Air quality estimation by computational intelligence methodologies

    Directory of Open Access Journals (Sweden)

    Ćirić Ivan T.

    2012-01-01

    Full Text Available The subject of this study is to compare different computational intelligence methodologies based on artificial neural networks used for forecasting an air quality parameter - the emission of CO2, in the city of Niš. Firstly, inputs of the CO2 emission estimator are analyzed and their measurement is explained. It is known that the traffic is the single largest emitter of CO2 in Europe. Therefore, a proper treatment of this component of pollution is very important for precise estimation of emission levels. With this in mind, measurements of traffic frequency and CO2 concentration were carried out at critical intersections in the city, as well as the monitoring of a vehicle direction at the crossroad. Finally, based on experimental data, different soft computing estimators were developed, such as feed forward neural network, recurrent neural network, and hybrid neuro-fuzzy estimator of CO2 emission levels. Test data for some characteristic cases presented at the end of the paper shows good agreement of developed estimator outputs with experimental data. Presented results are a true indicator of the implemented method usability. [Projekat Ministarstva nauke Republike Srbije, br. III42008-2/2011: Evaluation of Energy Performances and br. TR35016/2011: Indoor Environment Quality of Educational Buildings in Serbia with Impact to Health and Research of MHD Flows around the Bodies, in the Tip Clearances and Channels and Application in the MHD Pumps Development

  8. Evolving Intelligent Systems Methodology and Applications

    CERN Document Server

    Angelov, Plamen; Kasabov, Nik

    2010-01-01

    From theory to techniques, the first all-in-one resource for EIS. There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on th

  9. Hybrid Applications Of Artificial Intelligence

    Science.gov (United States)

    Borchardt, Gary C.

    1988-01-01

    STAR, Simple Tool for Automated Reasoning, is interactive, interpreted programming language for development and operation of artificial-intelligence application systems. Couples symbolic processing with compiled-language functions and data structures. Written in C language and currently available in UNIX version (NPO-16832), and VMS version (NPO-16965).

  10. Hybrid Intelligent Warning System for Boiler tube Leak Trips

    Directory of Open Access Journals (Sweden)

    Singh Deshvin

    2017-01-01

    Full Text Available Repeated boiler tube leak trips in coal fired power plants can increase operating cost significantly. An early detection and diagnosis of boiler trips is essential for continuous safe operations in the plant. In this study two artificial intelligent monitoring systems specialized in boiler tube leak trips have been proposed. The first intelligent warning system (IWS-1 represents the use of pure artificial neural network system whereas the second intelligent warning system (IWS-2 represents merging of genetic algorithms and artificial neural networks as a hybrid intelligent system. The Extreme Learning Machine (ELM methodology was also adopted in IWS-1 and compared with traditional training algorithms. Genetic algorithm (GA was adopted in IWS-2 to optimize the ANN topology and the boiler parameters. An integrated data preparation framework was established for 3 real cases of boiler tube leak trip based on a thermal power plant in Malaysia. Both the IWSs were developed using MATLAB coding for training and validation. The hybrid IWS-2 performed better than IWS-1.The developed system was validated to be able to predict trips before the plant monitoring system. The proposed artificial intelligent system could be adopted as a reliable monitoring system of the thermal power plant boilers.

  11. Intelligence for embedded systems a methodological approach

    CERN Document Server

    Alippi, Cesare

    2014-01-01

    Addressing current issues of which any engineer or computer scientist should be aware, this monograph is a response to the need to adopt a new computational paradigm as the methodological basis for designing pervasive embedded systems with sensor capabilities. The requirements of this paradigm are to control complexity, to limit cost and energy consumption, and to provide adaptation and cognition abilities allowing the embedded system to interact proactively with the real world. The quest for such intelligence requires the formalization of a new generation of intelligent systems able to exploit advances in digital architectures and in sensing technologies. The book sheds light on the theory behind intelligence for embedded systems with specific focus on: ·        robustness (the robustness of a computational flow and its evaluation); ·        intelligence (how to mimic the adaptation and cognition abilities of the human brain), ·        the capacity to learn in non-stationary and evolv...

  12. Adaptation and hybridization in computational intelligence

    CERN Document Server

    Jr, Iztok

    2015-01-01

      This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.  

  13. Methodology, Birth Order, Intelligence, and Personality.

    Science.gov (United States)

    Michalski, Richard L.; Shackelford, Todd K.

    2001-01-01

    Critiques recent research on the effects of birth order on intelligence and personality, which found that the between-family design revealed that birth order negatively related to intelligence, while the within-family design revealed that birth order was unrelated to intelligence. Suggests that it may not be intelligence that co-varies with birth…

  14. 15th International conference on Hybrid Intelligent Systems

    CERN Document Server

    Han, Sang; Al-Sharhan, Salah; Liu, Hongbo

    2016-01-01

    This book is devoted to the hybridization of intelligent systems which is a promising research field of modern computational intelligence concerned with the development of the next generation of intelligent systems. This Volume contains the papers presented in the Fifteenth International conference on Hybrid Intelligent Systems (HIS 2015) held in Seoul, South Korea during November 16-18, 2015. The 26 papers presented in this Volume were carefully reviewed and selected from 90 paper submissions. The Volume will be a valuable reference to researchers, students and practitioners in the computational intelligence field.

  15. Hybrid-augmented intelligence:collaboration and cognition

    Institute of Scientific and Technical Information of China (English)

    Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

    2017-01-01

    The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

  16. Hybrid Intelligent Control for Submarine Stabilization

    Directory of Open Access Journals (Sweden)

    Minghui Wang

    2013-05-01

    Full Text Available Abstract While sailing near the sea surface, submarines will often undergo rolling motion caused by wave disturbance. Fierce rolling motion seriously affects their normal operation and even threatens their security. We propose a new control method for roll stabilization. This paper studies hybrid intelligent control combining a fuzzy control, a neural network and extension control technology. Every control strategy can achieve the ideal control effect within the scope of its effective control. The neuro-fuzzy control strategy is used to improve the robustness of the controller. The speed control strategy and the course control strategy are conducted to extend the control range. The paper also proposes the design of the controller and carries out the simulation experiment in different sea conditions. The simulation results show that the control method proposed can indeed effectively improve the control performance of submarine stabilization.

  17. three intelligence methodologies for border defence and border

    African Journals Online (AJOL)

    Administrator

    Of these there are three intelligence methodologies applicable to this article – trends ..... globalisation associated with open and artificial borders and ever increasing costs of weapon ..... the technological development of mass tourist transport.

  18. Methodologies and intelligent systems for technology enhanced learning

    CERN Document Server

    Gennari, Rosella; Vitorini, Pierpaolo; Vicari, Rosa; Prieta, Fernando

    2014-01-01

    This volume presents recent research on Methodologies and Intelligent Systems for Technology Enhanced Learning. It contains the contributions of ebuTEL 2013 conference which took place in Trento, Italy, on September, 16th 2013 and of mis4TEL 2014 conference, which took take place in Salamanca, Spain, on September, 4th-6th 2014 This conference series are an open forum for discussing intelligent systems for Technology Enhanced Learning and empirical methodologies for its design or evaluation.

  19. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

    Directory of Open Access Journals (Sweden)

    Shan Li

    2014-01-01

    Full Text Available With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

  20. Beyond AI: Multi-Intelligence (MI Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    Directory of Open Access Journals (Sweden)

    Stephen Fox

    2017-06-01

    Full Text Available Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, the extensive post-anthropocentric research into intelligence is not given sufficient consideration. Third, AI is discussed often in reductionist mechanistic terms. Rather than in organicist emergentist terms as a contributor to multi-intelligence (MI hybrid beings and/or systems. Thus, current framing of AI can be a self-validating reduction within which AI development is focused upon AI becoming the single-variable mechanism causing future effects. In this paper, AI is reframed as a contributor to MI.

  1. Methodologies and Intelligent Systems for Technology Enhanced Learning

    CERN Document Server

    Gennari, Rosella; Vittorini, Pierpaolo; Prieta, Fernando

    2015-01-01

    This volume presents recent research on Methodologies and Intelligent Systems for Technology Enhanced Learning. It contains the contributions of MIS4TEL 2015, which took place in Salamanca, Spain,. On June 3rd to 5th 2015. Like the previous edition, this proceedings and the conference is an open forum for discussing intelligent systems for Technology Enhanced Learning and empirical methodologies for their design or evaluation MIS4TEL’15 conference has been organized by University of L’aquila, Free University of Bozen-Bolzano and the University of Salamanca.  .

  2. Hybrid intelligent optimization methods for engineering problems

    Science.gov (United States)

    Pehlivanoglu, Yasin Volkan

    The purpose of optimization is to obtain the best solution under certain conditions. There are numerous optimization methods because different problems need different solution methodologies; therefore, it is difficult to construct patterns. Also mathematical modeling of a natural phenomenon is almost based on differentials. Differential equations are constructed with relative increments among the factors related to yield. Therefore, the gradients of these increments are essential to search the yield space. However, the landscape of yield is not a simple one and mostly multi-modal. Another issue is differentiability. Engineering design problems are usually nonlinear and they sometimes exhibit discontinuous derivatives for the objective and constraint functions. Due to these difficulties, non-gradient-based algorithms have become more popular in recent decades. Genetic algorithms (GA) and particle swarm optimization (PSO) algorithms are popular, non-gradient based algorithms. Both are population-based search algorithms and have multiple points for initiation. A significant difference from a gradient-based method is the nature of the search methodologies. For example, randomness is essential for the search in GA or PSO. Hence, they are also called stochastic optimization methods. These algorithms are simple, robust, and have high fidelity. However, they suffer from similar defects, such as, premature convergence, less accuracy, or large computational time. The premature convergence is sometimes inevitable due to the lack of diversity. As the generations of particles or individuals in the population evolve, they may lose their diversity and become similar to each other. To overcome this issue, we studied the diversity concept in GA and PSO algorithms. Diversity is essential for a healthy search, and mutations are the basic operators to provide the necessary variety within a population. After having a close scrutiny of the diversity concept based on qualification and

  3. Using a hybrid methodology of dasyametric mapping and data ...

    African Journals Online (AJOL)

    Using a hybrid methodology of dasyametric mapping and data interpolation techniques ... AFRICAN JOURNALS ONLINE (AJOL) · Journals · Advanced Search ... the value and accuracy of the developed methodology is that of the 2011 census ...

  4. Forecasting in Intelligence: Indications and Warning Methodology in Modern Practice

    Directory of Open Access Journals (Sweden)

    Marina Gennadievna Vlasova

    2015-12-01

    Full Text Available Today the national security system effectiveness seriously depends on the professional analysis of information and timely forecasts. Thus the efficient methods of forecasting in the sphere of international relations are of current importance for the modern intelligence services. The Indications and Warning Technique that was a key element of forecasting methodology in intelligence until the end of Cold War is estimated in the present article. Is this method still relevant in the contemporary world with its new international order, new security challenges and technological revolution in the data collection and processing? The main conclusion based on the overview of current researches and known intelligence practice is that indicators technique is still relevant for the early warning of national security threats but requires some adaptation to today’s issues. The most important trends in adaptation are supposed to be a creation of broadest possible spectrum of threatens scenarios as well as research of current strategic threatens and corresponding indicators. Also the appropriate software that automates the use of indications technique by the security services is very important. The author believes that the cooperation between intelligence services and academic community can increase the efficiency of the Indications Methodology and of the strategic forecasting as well.

  5. Hybrid intelligent monironing systems for thermal power plant trips

    Science.gov (United States)

    Barsoum, Nader; Ismail, Firas Basim

    2012-11-01

    Steam boiler is one of the main equipment in thermal power plants. If the steam boiler trips it may lead to entire shutdown of the plant, which is economically burdensome. Early boiler trips monitoring is crucial to maintain normal and safe operational conditions. In the present work two artificial intelligent monitoring systems specialized in boiler trips have been proposed and coded within the MATLAB environment. The training and validation of the two systems has been performed using real operational data captured from the plant control system of selected power plant. An integrated plant data preparation framework for seven boiler trips with related operational variables has been proposed for IMSs data analysis. The first IMS represents the use of pure Artificial Neural Network system for boiler trip detection. All seven boiler trips under consideration have been detected by IMSs before or at the same time of the plant control system. The second IMS represents the use of Genetic Algorithms and Artificial Neural Networks as a hybrid intelligent system. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. Also, the optimal selection of the most influencing variables performed successfully by the hybrid intelligent system.

  6. Methodology for the hybrid solution of systems of differential equations

    International Nuclear Information System (INIS)

    Larrinaga, E.F.; Lopez, M.A.

    1993-01-01

    This work shows a general methodology of solution to systems of differential equations in hybrid computers. Taking into account this methodology, a mathematical model was elaborated. It offers wide possibilities of recording and handling the results on the basis of using the hybrid system IBM-VIDAC 1224 which the ISCTN has. It also presents the results gained when simulating a simple model of a nuclear reactor, which was used in the validation of the results of the computational model

  7. DIAGNOSIS WINDOWS PROBLEMS BASED ON HYBRID INTELLIGENCE SYSTEMS

    Directory of Open Access Journals (Sweden)

    SAFWAN O. HASOON

    2013-10-01

    Full Text Available This paper describes the artificial intelligence technologies by integrating Radial Basis Function networks with expert systems to construct a robust hybrid system. The purpose of building the hybrid system is to give recommendations to repair the operating system (Windows problems and troubleshoot the problems that can be repaired. The neural network has unique characteristics which it can complete the uncompleted data, the expert system can't deal with data that is incomplete, but using the neural network individually has some disadvantages which it can't give explanations and recommendations to the problems. The expert system has the ability to explain and give recommendations by using the rules and the human expert in some conditions. Therefore, we have combined the two technologies. The paper will explain the integration methods between the two technologies and which method is suitable to be used in the proposed hybrid system.

  8. Nature-inspired design of hybrid intelligent systems

    CERN Document Server

    Castillo, Oscar; Kacprzyk, Janusz

    2017-01-01

    This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as...

  9. ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

    Institute of Scientific and Technical Information of China (English)

    X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

    2003-01-01

    An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

  10. Artificial Intelligence Methodologies and Their Application to Diabetes.

    Science.gov (United States)

    Rigla, Mercedes; García-Sáez, Gema; Pons, Belén; Hernando, Maria Elena

    2018-03-01

    In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers-doctors and nurses-in this field.

  11. High-density hybrid interconnect methodologies

    International Nuclear Information System (INIS)

    John, J.; Zimmermann, L.; Moor, P.De; Hoof, C.Van

    2003-01-01

    Full text: The presentation gives an overview of the state-of-the-art of hybrid integration and in particular the IMEC technological approaches that will be able to address future hybrid detector needs. The dense hybrid flip-chip integration of an array of detectors and its dedicated readout electronics can be achieved with a variety of solderbump techniques such as pure Indium or Indium alloys, Ph-In, Ni/PbSn, but also conducting polymers... Particularly for cooled applications or ultra-high density applications, Indium solderbump technology (electroplated or evaporated) is the method of choice. The state-of-the-art of solderbump technologies that are to a high degree independent of the underlying detector material will be presented and examples of interconnect densities between 5x1E4cm-2 and 1x1E6 cm-2 will be demonstrated. For several classes of detectors, flip-chip integration is not allowed since the detectors have to be illuminated from the top. This applies to image sensors for EUV applications such as GaN/AlGaN based detectors and to MEMS-based sensors. In such cases, the only viable interconnection method has to be through the (thinned) detector wafer followed by a solderbump-based integration. The approaches for dense and ultra-dense through-the-wafer interconnect 'vias' will be presented and wafer thinning approaches will be shown

  12. Intelligent systems/software engineering methodology - A process to manage cost and risk

    Science.gov (United States)

    Friedlander, Carl; Lehrer, Nancy

    1991-01-01

    A systems development methodology is discussed that has been successfully applied to the construction of a number of intelligent systems. This methodology is a refinement of both evolutionary and spiral development methodologies. It is appropriate for development of intelligent systems. The application of advanced engineering methodology to the development of software products and intelligent systems is an important step toward supporting the transition of AI technology into aerospace applications. A description of the methodology and the process model from which it derives is given. Associated documents and tools are described which are used to manage the development process and record and report the emerging design.

  13. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2014-01-01

    Full Text Available Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health. Although there are several ways to measure the body fat percentage (BFP, the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR, artificial neural network (ANN, multivariate adaptive regression splines (MARS, and support vector regression (SVR techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.

  14. A 3D Hybrid Integration Methodology for Terabit Transceivers

    DEFF Research Database (Denmark)

    Dong, Yunfeng; Johansen, Tom Keinicke; Zhurbenko, Vitaliy

    2015-01-01

    integration are described. An equivalent circuit model of the via-throughs connecting the RF circuitry to the modulator is proposed and its lumped element parameters are extracted. Wire bonding transitions between the driving and RF circuitry were designed and simulated. An optimized 3D interposer design......This paper presents a three-dimensional (3D) hybrid integration methodology for terabit transceivers. The simulation methodology for multi-conductor structures are explained. The effect of ground vias on the RF circuitry and the preferred interposer substrate material for large bandwidth 3D hybrid...

  15. Hybrid Risk Management Methodology: A Case Study

    Directory of Open Access Journals (Sweden)

    Jacky Siu-Lun Ting

    2009-10-01

    Full Text Available Risk management is a decision-making process involving considerations of political, social, economic and engineering factors with relevant risk assessments relating to a potential hazard. In the last decade, a number of risk management tools are introduced and employed to manage and minimize the uncertainty and threats realization to the organizations. However, the focus of these methodologies are different; in which companies need to adopt various risk management principles to visualize a full picture of the organizational risk level. Regarding to this, this paper presents a new approach of risk management that integrates Hierarchical Holographic Modeling (HHM, Enterprise Risk Management (ERM and Business Recovery Planning (BCP for identifying and assessing risks as well as managing the consequences of realized residual risks. To illustrate the procedures of the proposed methodology, a logistic company ABC Limited is chosen to serve as a case study Through applying HHM and ERM to investigate and assess the risk, ABC Limited can be better evaluated the potential risks and then took the responsive actions (e.g. BCP to handle the risks and crisis in near future.

  16. Hybrid intelligent control concepts for optimal data fusion

    Science.gov (United States)

    Llinas, James

    1994-02-01

    In the post-Cold War era, Naval surface ship operations will be largely conducted in littoral waters to support regional military missions of all types, including humanitarian and evacuation activities, and amphibious mission execution. Under these conditions, surface ships will be much more isolated and vulnerable to a variety of threats, including maneuvering antiship missiles. To deal with these threats, the optimal employment of multiple shipborne sensors for maximum vigilance is paramount. This paper characterizes the sensor management problem as one of intelligent control, identifies some of the key issues in controller design, and presents one approach to controller design which is soon to be implemented and evaluated. It is argued that the complexity and hierarchical nature of problem formulation demands a hybrid combination of knowledge-based methods and scheduling techniques from 'hard' real-time systems theory for its solution.

  17. New Intelligent Transmission Concept for Hybrid Mobile Robot Speed Control

    Directory of Open Access Journals (Sweden)

    Nazim Mir-Nasiri

    2008-11-01

    Full Text Available This paper presents a new concept of a mobile robot speed control by using two degree of freedom gear transmission. The developed intelligent speed controller utilizes a gear box which comprises of epicyclic gear train with two inputs, one coupled with the engine shaft and another with the shaft of a variable speed dc motor. The net output speed is a combination of the two input speeds and is governed by the transmission ratio of the planetary gear train. This new approach eliminates the use of a torque converter which is otherwise an indispensable part of all available automatic transmissions, thereby reducing the power loss that occurs in the box during the fluid coupling. By gradually varying the speed of the dc motor a stepless transmission has been achieved. The other advantages of the developed controller are pulling over and reversing the vehicle, implemented by intelligent mixing of the dc motor and engine speeds. This approach eliminates traditional braking system in entire vehicle design. The use of two power sources, IC engine and battery driven DC motor, utilizes the modern idea of hybrid vehicles. The new mobile robot speed controller is capable of driving the vehicle even in extreme case of IC engine failure, for example, due to gas depletion..

  18. New Intelligent Transmission Concept for Hybrid Mobile Robot Speed Control

    Directory of Open Access Journals (Sweden)

    Nazim Mir-Nasiri

    2005-09-01

    Full Text Available This paper presents a new concept of a mobile robot speed control by using two degree of freedom gear transmission. The developed intelligent speed controller utilizes a gear box which comprises of epicyclic gear train with two inputs, one coupled with the engine shaft and another with the shaft of a variable speed dc motor. The net output speed is a combination of the two input speeds and is governed by the transmission ratio of the planetary gear train. This new approach eliminates the use of a torque converter which is otherwise an indispensable part of all available automatic transmissions, thereby reducing the power loss that occurs in the box during the fluid coupling. By gradually varying the speed of the dc motor a stepless transmission has been achieved. The other advantages of the developed controller are pulling over and reversing the vehicle, implemented by intelligent mixing of the dc motor and engine speeds. This approach eliminates traditional braking system in entire vehicle design. The use of two power sources, IC engine and battery driven DC motor, utilizes the modern idea of hybrid vehicles. The new mobile robot speed controller is capable of driving the vehicle even in extreme case of IC engine failure, for example, due to gas depletion.

  19. Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Jui-Yu Wu

    2013-01-01

    Full Text Available Stochastic global optimization (SGO algorithms such as the particle swarm optimization (PSO approach have become popular for solving unconstrained global optimization (UGO problems. The PSO approach, which belongs to the swarm intelligence domain, does not require gradient information, enabling it to overcome this limitation of traditional nonlinear programming methods. Unfortunately, PSO algorithm implementation and performance depend on several parameters, such as cognitive parameter, social parameter, and constriction coefficient. These parameters are tuned by using trial and error. To reduce the parametrization of a PSO method, this work presents two efficient hybrid SGO approaches, namely, a real-coded genetic algorithm-based PSO (RGA-PSO method and an artificial immune algorithm-based PSO (AIA-PSO method. The specific parameters of the internal PSO algorithm are optimized using the external RGA and AIA approaches, and then the internal PSO algorithm is applied to solve UGO problems. The performances of the proposed RGA-PSO and AIA-PSO algorithms are then evaluated using a set of benchmark UGO problems. Numerical results indicate that, besides their ability to converge to a global minimum for each test UGO problem, the proposed RGA-PSO and AIA-PSO algorithms outperform many hybrid SGO algorithms. Thus, the RGA-PSO and AIA-PSO approaches can be considered alternative SGO approaches for solving standard-dimensional UGO problems.

  20. Development of hybrid artificial intelligent based handover decision algorithm

    Directory of Open Access Journals (Sweden)

    A.M. Aibinu

    2017-04-01

    Full Text Available The possibility of seamless handover remains a mirage despite the plethora of existing handover algorithms. The underlying factor responsible for this has been traced to the Handover decision module in the Handover process. Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. The developed model is made up of hybrid of Artificial Neural Network (ANN based prediction model and Fuzzy Logic. On accessing the network, the Received Signal Strength (RSS was acquired over a period of time to form a time series data. The data was then fed to the newly proposed k-step ahead ANN-based RSS prediction system for estimation of prediction model coefficients. The synaptic weights and adaptive coefficients of the trained ANN was then used to compute the k-step ahead ANN based RSS prediction model coefficients. The predicted RSS value was later codified as Fuzzy sets and in conjunction with other measured network parameters were fed into the Fuzzy logic controller in order to finalize handover decision process. The performance of the newly developed k-step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. Results obtained in both cases shows that the proposed algorithm is capable of predicting ahead the RSS value to about ±0.0002 dB. Also, the cascaded effect of the complete handover decision module was also evaluated. Results obtained show that the newly proposed hybrid approach was able to reduce ping-pong effect associated with other handover techniques.

  1. Intelligent Power Management of hybrid Wind/ Fuel Cell/ Energy Storage Power Generation System

    OpenAIRE

    A. Hajizadeh; F. Hassanzadeh

    2013-01-01

    This paper presents an intelligent power management strategy for hybrid wind/ fuel cell/ energy storage power generation system. The dynamic models of wind turbine, fuel cell and energy storage have been used for simulation of hybrid power system. In order to design power flow control strategy, a fuzzy logic control has been implemented to manage the power between power sources. The optimal operation of the hybrid power system is a main goal of designing power management strategy. The hybrid ...

  2. New approaches in intelligent control techniques, methodologies and applications

    CERN Document Server

    Kountchev, Roumen

    2016-01-01

    This volume introduces new approaches in intelligent control area from both the viewpoints of theory and application. It consists of eleven contributions by prominent authors from all over the world and an introductory chapter. This volume is strongly connected to another volume entitled "New Approaches in Intelligent Image Analysis" (Eds. Roumen Kountchev and Kazumi Nakamatsu). The chapters of this volume are self-contained and include summary, conclusion and future works. Some of the chapters introduce specific case studies of various intelligent control systems and others focus on intelligent theory based control techniques with applications. A remarkable specificity of this volume is that three chapters are dealing with intelligent control based on paraconsistent logics.

  3. Hybrid methodological approach to context-dependent speech recognition

    Directory of Open Access Journals (Sweden)

    Dragiša Mišković

    2017-01-01

    Full Text Available Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents.

  4. 16th International Conference on Hybrid Intelligent Systems and the 8th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

    Haqiq, Abdelkrim; Alimi, Adel; Mezzour, Ghita; Rokbani, Nizar; Muda, Azah

    2017-01-01

    This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21–23, 2016 in Marrakech, Morocco. HIS - NaBIC 2016 was jointly organized by the Machine Intelligence Research Labs (MIR Labs), USA; Hassan 1st University, Settat, Morocco and University of Sfax, Tunisia. Hybridization of intelligent systems is a promising research field in modern artificial/computational intelligence and is concerned with the development of the next generation of intelligent systems. The conference’s main aim is to inspire further exploration of the intriguing potential of hybrid intelligent systems and bio-inspired computing. As such, the book is a valuable resource for practicing engineers /scientists and researchers working in the field of computational intelligence and artificial intelligence.

  5. Special Issue: New trends and applications on hybrid artificial intelligence systems

    OpenAIRE

    Corchado Rodríguez, Emilio; Graña Romay, Manuel; Woźniak, MichaŁ

    2017-01-01

    This Special Issue is an outgrowth of the HAIS'10, the 5th International Conference on Hybrid Artificial Intelligence Systems, which was held in San Sebastián, Spain, 23–25 June 2010. The HAIS conference series is devoted to the presentation of innovative techniques involving the hybridization of emerging and active topics in data mining and decision support systems, information fusion, evolutionary computation, visualization techniques, ensemble models, intelligent agent-based systems (compl...

  6. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

  7. A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system

    International Nuclear Information System (INIS)

    Al-falahi, Monaaf D.A.; Jayasinghe, S.D.G.; Enshaei, H.

    2017-01-01

    Highlights: • Possible combinations and configurations for standalone PV-WT HES were discussed. • Most recently used assessment parameters for standalone PV-WT HES were explained. • Optimization algorithms and software tools were comprehensively reviewed. • The recent trend of using hybrid algorithms over single algorithms was discussed. • Optimization algorithms for sizing standalone PV-WT HES were critically compared. - Abstract: Electricity demand in remote and island areas are generally supplied by diesel or other fossil fuel based generation systems. Nevertheless, due to the increasing cost and harmful emissions of fossil fuels there is a growing trend to use standalone hybrid renewable energy systems (HRESs). Due to the complementary characteristics, matured technologies and availability in most areas, hybrid systems with solar and wind energy have become the popular choice in such applications. However, the intermittency and high net present cost are the challenges associated with solar and wind energy systems. In this context, optimal sizing is a key factor to attain a reliable supply at a low cost through these standalone systems. Therefore, there has been a growing interest to develop algorithms for size optimization in standalone HRESs. The optimal sizing methodologies reported so far can be broadly categorized as classical algorithms, modern techniques and software tools. Modern techniques, based on single artificial intelligence (AI) algorithms, are becoming more popular than classical algorithms owing to their capabilities in solving complex optimization problems. Moreover, in recent years, there has been a clear trend to use hybrid algorithms over single algorithms mainly due to their ability to provide more promising optimization results. This paper aims to present a comprehensive review on recent developments in size optimization methodologies, as well as a critical comparison of single algorithms, hybrid algorithms, and software tools

  8. An intelligent clustering based methodology for confusable diseases ...

    African Journals Online (AJOL)

    Journal of Computer Science and Its Application ... In this paper, an intelligent system driven by fuzzy clustering algorithm and Adaptive Neuro-Fuzzy Inference System for ... Data on patients diagnosed and confirmed by laboratory tests of viral ...

  9. New approaches in intelligent image analysis techniques, methodologies and applications

    CERN Document Server

    Nakamatsu, Kazumi

    2016-01-01

    This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the...

  10. The application of hybrid artificial intelligence systems for forecasting

    Science.gov (United States)

    Lees, Brian; Corchado, Juan

    1999-03-01

    The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

  11. Multimodal hybrid reasoning methodology for personalized wellbeing services.

    Science.gov (United States)

    Ali, Rahman; Afzal, Muhammad; Hussain, Maqbool; Ali, Maqbool; Siddiqi, Muhammad Hameed; Lee, Sungyoung; Ho Kang, Byeong

    2016-02-01

    A wellness system provides wellbeing recommendations to support experts in promoting a healthier lifestyle and inducing individuals to adopt healthy habits. Adopting physical activity effectively promotes a healthier lifestyle. A physical activity recommendation system assists users to adopt daily routines to form a best practice of life by involving themselves in healthy physical activities. Traditional physical activity recommendation systems focus on general recommendations applicable to a community of users rather than specific individuals. These recommendations are general in nature and are fit for the community at a certain level, but they are not relevant to every individual based on specific requirements and personal interests. To cover this aspect, we propose a multimodal hybrid reasoning methodology (HRM) that generates personalized physical activity recommendations according to the user׳s specific needs and personal interests. The methodology integrates the rule-based reasoning (RBR), case-based reasoning (CBR), and preference-based reasoning (PBR) approaches in a linear combination that enables personalization of recommendations. RBR uses explicit knowledge rules from physical activity guidelines, CBR uses implicit knowledge from experts׳ past experiences, and PBR uses users׳ personal interests and preferences. To validate the methodology, a weight management scenario is considered and experimented with. The RBR part of the methodology generates goal, weight status, and plan recommendations, the CBR part suggests the top three relevant physical activities for executing the recommended plan, and the PBR part filters out irrelevant recommendations from the suggested ones using the user׳s personal preferences and interests. To evaluate the methodology, a baseline-RBR system is developed, which is improved first using ranged rules and ultimately using a hybrid-CBR. A comparison of the results of these systems shows that hybrid-CBR outperforms the

  12. Beyond AI: Multi-Intelligence (MI) Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    OpenAIRE

    Stephen Fox

    2017-01-01

    Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI) are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, t...

  13. User needs for a standardized CO2 emission assessment methodology for intelligent transport systems

    NARCIS (Netherlands)

    Mans, D.; Rekiel, J.; Wolfermann, A.; Klunder, G.

    2012-01-01

    The Amitran FP7 project will define a reference methodology to assess the impact of intelligent transport systems on CO2 emissions. The methodology is intended to be used as a reference by future projects and covers both passenger and freight transport. The project will lead to a validated

  14. A Hybrid Dynamic System Assessment Methodology for Multi-Modal Transportation-Electrification

    Directory of Open Access Journals (Sweden)

    Thomas J.T. van der Wardt

    2017-05-01

    Full Text Available In recent years, electrified transportation, be it in the form of buses, trains, or cars have become an emerging form of mobility. Electric vehicles (EVs, especially, are set to expand the amount of electric miles driven and energy consumed. Nevertheless, the question remains as to whether EVs will be technically feasible within infrastructure systems. Fundamentally, EVs interact with three interconnected systems: the (physical transportation system, the electric power grid, and their supporting information systems. Coupling of the two physical systems essentially forms a nexus, the transportation-electricity nexus (TEN. This paper presents a hybrid dynamic system assessment methodology for multi-modal transportation-electrification. At its core, it utilizes a mathematical model which consists of a marked Petri-net model superimposed on the continuous time microscopic traffic dynamics and the electrical state evolution. The methodology consists of four steps: (1 establish the TEN structure; (2 establish the TEN behavior; (3 establish the TEN Intelligent Transportation-Energy System (ITES decision-making; and (4 assess the TEN performance. In the presentation of the methodology, the Symmetrica test case is used throughout as an illustrative example. Consequently, values for several measures of performance are provided. This methodology is presented generically and may be used to assess the effects of transportation-electrification in any city or area; opening up possibilities for many future studies.

  15. Multiple Intelligences in Online, Hybrid, and Traditional Business Statistics Courses

    Science.gov (United States)

    Lopez, Salvador; Patron, Hilde

    2012-01-01

    According to Howard Gardner, Professor of Cognition and Education at Harvard University, intelligence of humans cannot be measured with a single factor such as the IQ level. Instead, he and others have suggested that humans have different types of intelligence. This paper examines whether students registered in online or mostly online courses have…

  16. A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns

    Science.gov (United States)

    Li, Xiang; Zhang, Yang; Wong, Hau-San; Qin, Zhongfeng

    2009-11-01

    Portfolio selection theory with fuzzy returns has been well developed and widely applied. Within the framework of credibility theory, several fuzzy portfolio selection models have been proposed such as mean-variance model, entropy optimization model, chance constrained programming model and so on. In order to solve these nonlinear optimization models, a hybrid intelligent algorithm is designed by integrating simulated annealing algorithm, neural network and fuzzy simulation techniques, where the neural network is used to approximate the expected value and variance for fuzzy returns and the fuzzy simulation is used to generate the training data for neural network. Since these models are used to be solved by genetic algorithm, some comparisons between the hybrid intelligent algorithm and genetic algorithm are given in terms of numerical examples, which imply that the hybrid intelligent algorithm is robust and more effective. In particular, it reduces the running time significantly for large size problems.

  17. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

    2011-02-15

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  18. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

    2011-01-01

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  19. Multiple Intelligences: The Most Effective Platform for Global 21st Century Educational and Instructional Methodologies

    Science.gov (United States)

    McFarlane, Donovan A.

    2011-01-01

    This paper examines the theory of Multiple Intelligences (MI) as the most viable and effective platform for 21st century educational and instructional methodologies based on the understanding of the value of diversity in today's classrooms and educational institutions, the unique qualities and characteristics of individual learners, the…

  20. Safety, mobility and comfort assessment methodologies of intelligent transport systems for vulnerable road users

    NARCIS (Netherlands)

    Malone, K.; Silla, A.; Johanssen, C.; Bell, D.

    2017-01-01

    Introduction: This paper describes the modification and development of methodologies to assess the impacts of Intelligent Transport Systems (ITS) applications for Vulnerable Road users (VRUs) in the domains of safety, mobility and comfort. This effort was carried out in the context of the VRUITS

  1. An intelligent design methodology for nuclear power systems

    International Nuclear Information System (INIS)

    Nassersharif, B.; Martin, R.P.; Portal, M.G.; Gaeta, M.J.

    1989-01-01

    The goal of this investigation is to research possible methodologies into automating the design of, specifically, nuclear power facilities; however, it is relevant to all thermal power systems. The strategy of this research has been to concentrate on individual areas of the thermal design process, investigate procedures performed, develop methodology to emulate that behavior, and prototype it in the form of a computer program. The design process has been generalized as follows: problem definition, design definition, component selection procedure, optimization and engineering analysis, testing and final design with the problem definition defining constraints that will be applied to the selection procedure as well as design definition. The result of this research is a prototype computer program applying an original procedure for the selection of the best set of real components that would be used in constructing a system with desired performance characteristics. The mathematical model used for the selection procedure is possibility theory

  2. A Cybernetic Design Methodology for 'Intelligent' Online Learning Support

    Science.gov (United States)

    Quinton, Stephen R.

    The World Wide Web (WWW) provides learners and knowledge workers convenient access to vast stores of information, so much that present methods for refinement of a query or search result are inadequate - there is far too much potentially useful material. The problem often encountered is that users usually do not recognise what may be useful until they have progressed some way through the discovery, learning, and knowledge acquisition process. Additional support is needed to structure and identify potentially relevant information, and to provide constructive feedback. In short, support for learning is needed. The learning envisioned here is not simply the capacity to recall facts or to recognise objects. The focus is on learning that results in the construction of knowledge. Although most online learning platforms are efficient at delivering information, most do not provide tools that support learning as envisaged in this chapter. It is conceivable that Web-based learning environments can incorporate software systems that assist learners to form new associations between concepts and synthesise information to create new knowledge. This chapter details the rationale and theory behind a research study that aims to evolve Web-based learning environments into 'intelligent thinking' systems that respond to natural language human input. Rather than functioning simply as a means of delivering information, it is argued that online learning solutions will 1 day interact directly with students to support their conceptual thinking and cognitive development.

  3. 7th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning

    CERN Document Server

    Gennari, Rosella; Mascio, Tania; Rodríguez, Sara; Prieta, Fernando; Ramos, Carlos; Silveira, Ricardo

    2017-01-01

    This book presents the outcomes of the 7th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL'17), hosted by the Polytechnic of Porto, Portugal from 21 to 23 June 2017. Expanding on the topics of the previous conferences, it provided an open forum for discussing intelligent systems for technology enhanced learning (TEL) and their roots in novel learning theories, empirical methodologies for their design or evaluation, stand-alone and web-based solutions, and makerspaces. It also fostered entrepreneurship and business startup ideas, bringing together researchers and developers from industry, education and the academic world to report on the latest scientific research, technical advances and methodologies.

  4. 6th International Conference in Methodologies and intelligent Systems for Technology Enhanced Learning

    CERN Document Server

    Prieta, Fernando; Mascio, Tania; Gennari, Rosella; Rodríguez, Javier; Vittorini, Pierpaolo

    2016-01-01

    The 6th International Conference in Methodologies and intelligent Systems for Technology Enhanced Learning held in Seville (Spain) is host by the University of Seville from 1st to 3rd June, 2016. The 6th edition of this conference expands the topics of the evidence-based TEL workshops series in order to provide an open forum for discussing intelligent systems for TEL, their roots in novel learning theories, empirical methodologies for their design or evaluation, stand-alone solutions or web-based ones. It intends to bring together researchers and developers from industry, the education field and the academic world to report on the latest scientific research, technical advances and methodologies.

  5. Modeling, control, and simulation of grid connected intelligent hybrid battery/photovoltaic system using new hybrid fuzzy-neural method.

    Science.gov (United States)

    Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid

    2016-07-01

    Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  6. A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge

    2014-01-01

    Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily

  7. A methodology for the design of experiments in computational intelligence with multiple regression models.

    Science.gov (United States)

    Fernandez-Lozano, Carlos; Gestal, Marcos; Munteanu, Cristian R; Dorado, Julian; Pazos, Alejandro

    2016-01-01

    The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.

  8. A methodology for the design of experiments in computational intelligence with multiple regression models

    Directory of Open Access Journals (Sweden)

    Carlos Fernandez-Lozano

    2016-12-01

    Full Text Available The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.

  9. Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems

    Directory of Open Access Journals (Sweden)

    Andreas König

    2009-11-01

    Full Text Available The emergence of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for the design and application of intelligent systems. Each new application system must be designed from scratch, employing sophisticated methods ranging from conventional signal processing to computational intelligence. Currently, a significant part of this overall algorithmic chain of the computational system model still has to be assembled manually by experienced designers in a time and labor consuming process. In this research work, this challenge is picked up and a methodology and algorithms for automated design of intelligent integrated and resource-aware multi-sensor systems employing multi-objective evolutionary computation are introduced. The proposed methodology tackles the challenge of rapid-prototyping of such systems under realization constraints and, additionally, includes features of system instance specific self-correction for sustained operation of a large volume and in a dynamically changing environment. The extension of these concepts to the reconfigurable hardware platform renders so called self-x sensor systems, which stands, e.g., for self-monitoring, -calibrating, -trimming, and -repairing/-healing systems. Selected experimental results prove the applicability and effectiveness of our proposed methodology and emerging tool. By our approach, competitive results were achieved with regard to classification accuracy, flexibility, and design speed under additional design constraints.

  10. Methodological comparison on hybrid nano organic solar cell fabrication

    Science.gov (United States)

    Vairavan, Rajendaran; Hambali, Nor Azura Malini Ahmad; Wahid, Mohamad Halim Abd; Retnasamy, Vithyacharan; Shahimin, Mukhzeer Mohamad

    2018-02-01

    The development of low cost solar cells has been the main focus in recent years. This has lead to the generation of photovoltaic cells based on hybrid of nanoparticle-organic polymer materials. This type of hybrid photovoltaic cells can overcome the problem of polymeric devices having low optical absorption and carrier mobilities. The hybrid cell has the potential of bridging the efficiency gap, which in present in organic and inorganic semiconductor materials. This project focuses on obtaining an hybrid active layer consisting of nanoparticles and organic polymer, to understand the parameter involved in obtaining this active layer and finally to investigate if the addition of nano particles in to the active layer could enhance the output of the hybrid solar cell. The hybrid active layer have will be deposited using the spin coating technique by using CdTe, CdS nano particles mixed with poly (2-methoxy,5-(2-ethyl-hexyloxy)-p-phenylvinylene)MEH-PPV.

  11. Optimisation of Software-Defined Networks Performance Using a Hybrid Intelligent System

    Directory of Open Access Journals (Sweden)

    Ann Sabih

    2017-06-01

    Full Text Available This paper proposes a novel intelligent technique that has been designed to optimise the performance of Software Defined Networks (SDN. The proposed hybrid intelligent system has employed integration of intelligence-based optimisation approaches with the artificial neural network. These heuristic optimisation methods include Genetic Algorithms (GA and Particle Swarm Optimisation (PSO. These methods were utilised separately in order to select the best inputs to maximise SDN performance. In order to identify SDN behaviour, the neural network model is trained and applied. The maximal optimisation approach has been identified using an analytical approach that considered SDN performance and the computational time as objective functions. Initially, the general model of the neural network was tested with unseen data before implementing the model using GA and PSO to determine the optimal performance of SDN. The results showed that the SDN represented by Artificial Neural Network ANN, and optmised by PSO, generated a better configuration with regards to computational efficiency and performance index.

  12. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    OpenAIRE

    Daniel-Petru GHENCEA; Miron ZAPCIU; Claudiu-Florinel BISU; Elena-Iuliana BOTEANU; Elena-Luminiţa OLTEANU

    2017-01-01

    The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic). The paper presents a prediction mode obtaining valid range of values f...

  13. Intelligent Hybrid Control Strategy for Trajectory Tracking of Robot Manipulators

    Directory of Open Access Journals (Sweden)

    Yi Zuo

    2008-01-01

    Full Text Available We address the problem of robust tracking control using a PD-plus-feedforward controller and an intelligent adaptive robust compensator for a rigid robotic manipulator with uncertain dynamics and external disturbances. A key feature of this scheme is that soft computer methods are used to learn the upper bound of system uncertainties and adjust the width of the boundary layer base. In this way, the prior knowledge of the upper bound of the system uncertainties does need not to be required. Moreover, chattering can be effectively eliminated, and asymptotic error convergence can be guaranteed. Numerical simulations and experiments of two-DOF rigid robots are presented to show effectiveness of the proposed scheme.

  14. An intelligent hybrid system for surface coal mine safety analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lilic, N.; Obradovic, I.; Cvjetic, A. [University of Belgrade, Belgrade (Serbia)

    2010-06-15

    Analysis of safety in surface coal mines represents a very complex process. Published studies on mine safety analysis are usually based on research related to accidents statistics and hazard identification with risk assessment within the mining industry. Discussion in this paper is focused on the application of AI methods in the analysis of safety in mining environment. Complexity of the subject matter requires a high level of expert knowledge and great experience. The solution was found in the creation of a hybrid system PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. The main goal of the system is the estimation of mining environment as one of the significant components of general safety state in a mine. This global goal is subdivided into a hierarchical structure of subgoals where each subgoal can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination, geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. Both the hybrid nature of the system and the possibilities it offers are illustrated through a case study using field data related to an existing Serbian surface coal mine.

  15. A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization

    Directory of Open Access Journals (Sweden)

    Daqing Wu

    2012-01-01

    Full Text Available A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO and the stochastic exploitation of the cooperative artificial bee colony algorithm (CABC for solving the function optimization. In the proposed hybrid algorithm, the whole process is divided into three stages. In the first stage, a dynamic multiswarm PSO is constructed to maintain the population diversity. In the second stage, the parallel, positive feedback of CABC was implemented in each small swarm. In the third stage, we make use of the particle swarm optimization global model, which has a faster convergence speed to enhance the global convergence in solving the whole problem. To verify the effectiveness and efficiency of the proposed hybrid algorithm, various scale benchmark problems are tested to demonstrate the potential of the proposed multistage hybrid swarm intelligence optimization algorithm. The results show that DM-PSO-ABC is better in the search precision, and convergence property and has strong ability to escape from the local suboptima when compared with several other peer algorithms.

  16. Intelligent emission-sensitive routing for plugin hybrid electric vehicles.

    Science.gov (United States)

    Sun, Zhonghao; Zhou, Xingshe

    2016-01-01

    The existing transportation sector creates heavily environmental impacts and is a prime cause for the current climate change. The need to reduce emissions from this sector has stimulated efforts to speed up the application of electric vehicles (EVs). A subset of EVs, called plug-in hybrid electric vehicles (PHEVs), backup batteries with combustion engine, which makes PHEVs have a comparable driving range to conventional vehicles. However, this hybridization comes at a cost of higher emissions than all-electric vehicles. This paper studies the routing problem for PHEVs to minimize emissions. The existing shortest-path based algorithms cannot be applied to solving this problem, because of the several new challenges: (1) an optimal route may contain circles caused by detour for recharging; (2) emissions of PHEVs not only depend on the driving distance, but also depend on the terrain and the state of charge (SOC) of batteries; (3) batteries can harvest energy by regenerative braking, which makes some road segments have negative energy consumption. To address these challenges, this paper proposes a green navigation algorithm (GNA) which finds the optimal strategies: where to go and where to recharge. GNA discretizes the SOC, then makes the PHEV routing problem to satisfy the principle of optimality. Finally, GNA adopts dynamic programming to solve the problem. We evaluate GNA using synthetic maps generated by the delaunay triangulation. The results show that GNA can save more than 10 % energy and reduce 10 % emissions when compared to the shortest path algorithm. We also observe that PHEVs with the battery capacity of 10-15 KWh detour most and nearly no detour when larger than 30 KWh. This observation gives some insights when developing PHEVs.

  17. Methodology of Integration for Competitive Technical Intelligence with Blue Ocean Strategy: Application to an exotic fruit

    Directory of Open Access Journals (Sweden)

    Marisela Rodríguez Salvador

    2011-12-01

    Full Text Available This article presents a new methodology that integrates Competitive Technical Intelligence with Blue Ocean Strategy. We explore new business niches taking advantage of the synergy that both areas offer, developing a model based on cyclic interactions through a process developed in two stages: Understanding opportunity that arise from idea formulation to decision making and strategic development. The validity of our approach (first stage was observed in the evaluation of an exotic fruit, Anacardium Occidentale, in the South of the State of Veracruz, Mexico with the support of the university ITESM, Campus Monterrey. We identified critical factors for success, opportunities and threats. Results confirm the attractiveness of this crop.

  18. Data Mining: A Hybrid Methodology for Complex and Dynamic Research

    Science.gov (United States)

    Lang, Susan; Baehr, Craig

    2012-01-01

    This article provides an overview of the ways in which data and text mining have potential as research methodologies in composition studies. It introduces data mining in the context of the field of composition studies and discusses ways in which this methodology can complement and extend our existing research practices by blending the best of what…

  19. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

  20. Optimal sensor placement for large structures using the nearest neighbour index and a hybrid swarm intelligence algorithm

    International Nuclear Information System (INIS)

    Lian, Jijian; He, Longjun; Ma, Bin; Peng, Wenxiang; Li, Huokun

    2013-01-01

    Research on optimal sensor placement (OSP) has become very important due to the need to obtain effective testing results with limited testing resources in health monitoring. In this study, a new methodology is proposed to select the best sensor locations for large structures. First, a novel fitness function derived from the nearest neighbour index is proposed to overcome the drawbacks of the effective independence method for OSP for large structures. This method maximizes the contribution of each sensor to modal observability and simultaneously avoids the redundancy of information between the selected degrees of freedom. A hybrid algorithm combining the improved discrete particle swarm optimization (DPSO) with the clonal selection algorithm is then implemented to optimize the proposed fitness function effectively. Finally, the proposed method is applied to an arch dam for performance verification. The results show that the proposed hybrid swarm intelligence algorithm outperforms a genetic algorithm with decimal two-dimension array encoding and DPSO in the capability of global optimization. The new fitness function is advantageous in terms of sensor distribution and ensuring a well-conditioned information matrix and orthogonality of modes, indicating that this method may be used to provide guidance for OSP in various large structures. (paper)

  1. Overall intelligent hybrid control system for a fossil-fuel power unit

    Energy Technology Data Exchange (ETDEWEB)

    Garduno-Ramirez, Raul

    2000-08-01

    This research present a methodology to design a generalized overall unit control system for a fossil fuel power unit (FFPU), and develops a minimum prototype to demonstrate its feasibility. Toward the above goal, the associated research project was undertaken as a technology innovation process with its two ends identified as follows. First, it is recognized that the coordinated control strategies constitute the uppermost control level in current FFPUs, and so, are responsible for driving the boiler-turbine-generator set as a single entity. Second, a FFPU is envisioned as a complex process, subject to multiple changing operating conditions, that should perform as an intelligent system, for which an advanced integral control concept is needed. Therefore, as an outcome of the innovation process, a generalized unit control concept that extends the capabilities of current coordinated control schemes is proposed. This concept is presented as the Intelligent Coordinated Control System (ICCS) paradigm, which establishes an open reference framework for the development of overall unit control schemes. The ICCS's system goals are identified using power plant process engineering concepts, and intelligent control systems engineering concepts are used to identify main tasks and to achieve system functional decomposition. A software engineering agency concept is used to identify and group agents according to their knowledge and purpose interactions. The resultant ICCS structure is an open set of functionally grouped agent clusters in a two-level hierarchical system. The upper level, mainly characterized for knowledge-driven processes, performs the supervisory functions needed to provide self governing operation characteristics, while the lower level, mainly characterized for data-driven processes, performs the fast reactive behavior functions necessary for hybrid real-time control and protection. Developed through several stages, the ICCS-MP finally implements a two

  2. Intelligent sizing of a series hybrid electric power-train system based on Chaos-enhanced accelerated particle swarm optimization

    International Nuclear Information System (INIS)

    Zhou, Quan; Zhang, Wei; Cash, Scott; Olatunbosun, Oluremi; Xu, Hongming; Lu, Guoxiang

    2017-01-01

    Highlights: • A novel algorithm for hybrid electric powertrain intelligent sizing is introduced and applied. • The proposed CAPSO algorithm is capable of finding the real optimal result with much higher reputation. • Logistic mapping is the most effective strategy to build CAPSO. • The CAPSO gave more reliable results and increased the efficiency by 1.71%. - Abstract: This paper firstly proposed a novel HEV sizing method using the Chaos-enhanced Accelerated Particle Swarm Optimization (CAPSO) algorithm and secondly provided a demonstration on sizing a series hybrid electric powertrain with investigations of chaotic mapping strategies to achieve the global optimization. In this paper, the intelligent sizing of a series hybrid electric powertrain is formulated as an integer multi-objective optimization issue by modelling the powertrain system. The intelligent sizing mechanism based on APSO is then introduced, and 4 types of the most effective chaotic mapping strategy are investigated to upgrade the standard APSO into CAPSO algorithms for intelligent sizing. The evaluation of the intelligent sizing systems based on standard APSO and CAPSOs are then performed. The Monte Carlo analysis and reputation evaluation indicate that the CAPSO outperforms the standard APSO for finding the real optimal sizing result with much higher reputation, and CAPSO with logistic mapping strategy is the most effective algorithm for HEV powertrain components intelligent sizing. In addition, this paper also performs the sensitivity analysis and Pareto analysis to help engineers customize the intelligent sizing system.

  3. Hybrid probabilistic and possibilistic safety assessment. Methodology and application

    International Nuclear Information System (INIS)

    Kato, Kazuyuki; Amano, Osamu; Ueda, Hiroyoshi; Ikeda, Takao; Yoshida, Hideji; Takase, Hiroyasu

    2002-01-01

    This paper presents a unified methodology to handle variability and ignorance by using probabilistic and possibilistic techniques respectively. The methodology has been applied to the safety assessment of geological disposal of high-level radioactive waste. Uncertainties associated with scenarios, models and parameters were defined in terms of fuzzy membership functions derived through a series of interviews to the experts, while variability was formulated by means of probability density functions (pdfs) based on available data sets. The exercise demonstrated the applicability of the new methodology and, in particular, its advantage in quantifying uncertainties based on expert opinion and in providing information on the dependence of assessment results on the level of conservatism. In addition, it was shown that sensitivity analysis can identify key parameters contributing to uncertainties associated with results of the overall assessment. The information mentioned above can be utilized to support decision-making and to guide the process of disposal system development and optimization of protection against potential exposure. (author)

  4. Intelligent controller of a flexible hybrid robot machine for ITER assembly and maintenance

    International Nuclear Information System (INIS)

    Al-saedi, Mazin I.; Wu, Huapeng; Handroos, Heikki

    2014-01-01

    Highlights: • Studying flexible multibody dynamic of hybrid parallel robot. • Investigating fuzzy-PD controller to control a hybrid flexible hydraulically driven robot. • Investigating ANFIS-PD controller to control a hybrid flexible robot. Compare to traditional PID this method gives better performance. • Using the equilibrium of reaction forces between the parallel and serial parts of hybrid robot to control the serial part hydraulically driven. - Abstract: The assembly and maintenance of International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. To fulfill the tasks in ITER application, this paper presents a hybrid redundant manipulator with four DOFs provided by serial kinematic axes and six DOFs by parallel mechanism. Thus, in machining, to achieve greater end-effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. In this paper, the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two control schemes have been investigated: (1) fuzzy-PID self tuning controller composed of the conventional PID control and with fuzzy logic; (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel robot based on rod position predictions. The obtained results of the fuzzy-PID and ANFIS-PID self tuning controller can reduce more tracking errors than the conventional PID controller. Subsequently, the serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should

  5. Intelligent controller of a flexible hybrid robot machine for ITER assembly and maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Al-saedi, Mazin I., E-mail: mazin.al-saedi@lut.fi; Wu, Huapeng; Handroos, Heikki

    2014-10-15

    Highlights: • Studying flexible multibody dynamic of hybrid parallel robot. • Investigating fuzzy-PD controller to control a hybrid flexible hydraulically driven robot. • Investigating ANFIS-PD controller to control a hybrid flexible robot. Compare to traditional PID this method gives better performance. • Using the equilibrium of reaction forces between the parallel and serial parts of hybrid robot to control the serial part hydraulically driven. - Abstract: The assembly and maintenance of International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. To fulfill the tasks in ITER application, this paper presents a hybrid redundant manipulator with four DOFs provided by serial kinematic axes and six DOFs by parallel mechanism. Thus, in machining, to achieve greater end-effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. In this paper, the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two control schemes have been investigated: (1) fuzzy-PID self tuning controller composed of the conventional PID control and with fuzzy logic; (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel robot based on rod position predictions. The obtained results of the fuzzy-PID and ANFIS-PID self tuning controller can reduce more tracking errors than the conventional PID controller. Subsequently, the serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should

  6. Hybrid Intelligent Control Method to Improve the Frequency Support Capability of Wind Energy Conversion Systems

    Directory of Open Access Journals (Sweden)

    Shin Young Heo

    2015-10-01

    Full Text Available This paper presents a hybrid intelligent control method that enables frequency support control for permanent magnet synchronous generators (PMSGs wind turbines. The proposed method for a wind energy conversion system (WECS is designed to have PMSG modeling and full-scale back-to-back insulated-gate bipolar transistor (IGBT converters comprising the machine and grid side. The controller of the machine side converter (MSC and the grid side converter (GSC are designed to achieve maximum power point tracking (MPPT based on an improved hill climb searching (IHCS control algorithm and de-loaded (DL operation to obtain a power margin. Along with this comprehensive control of maximum power tracking mode based on the IHCS, a method for kinetic energy (KE discharge control of the supporting primary frequency control scheme with DL operation is developed to regulate the short-term frequency response and maintain reliable operation of the power system. The effectiveness of the hybrid intelligent control method is verified by a numerical simulation in PSCAD/EMTDC. Simulation results show that the proposed approach can improve the frequency regulation capability in the power system.

  7. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    Science.gov (United States)

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

  8. Process monitoring for intelligent manufacturing processes - Methodology and application to Robot Assisted Polishing

    DEFF Research Database (Denmark)

    Pilny, Lukas

    Process monitoring provides important information on the product, process and manufacturing system during part manufacturing. Such information can be used for process optimization and detection of undesired processing conditions to initiate timely actions for avoidance of defects, thereby improving...... quality assurance. This thesis is aimed at a systematic development of process monitoring solutions, constituting a key element of intelligent manufacturing systems towards zero defect manufacturing. A methodological approach of general applicability is presented in this concern.The approach consists...... of six consecutive steps for identification of product Vital Quality Characteristics (VQCs) and Key Process Variables (KPVs), selection and characterization of sensors, optimization of sensors placement, validation of the monitoring solutions, definition of the reference manufacturing performance...

  9. Development and application of a deterministic-realistic hybrid methodology for LOCA licensing analysis

    International Nuclear Information System (INIS)

    Liang, Thomas K.S.; Chou, Ling-Yao; Zhang, Zhongwei; Hsueh, Hsiang-Yu; Lee, Min

    2011-01-01

    Highlights: → A new LOCA licensing methodology (DRHM, deterministic-realistic hybrid methodology) was developed. → DRHM involves conservative Appendix K physical models and statistical treatment of plant status uncertainties. → DRHM can generate 50-100 K PCT margin as compared to a traditional Appendix K methodology. - Abstract: It is well recognized that a realistic LOCA analysis with uncertainty quantification can generate greater safety margin as compared with classical conservative LOCA analysis using Appendix K evaluation models. The associated margin can be more than 200 K. To quantify uncertainty in BELOCA analysis, generally there are two kinds of uncertainties required to be identified and quantified, which involve model uncertainties and plant status uncertainties. Particularly, it will take huge effort to systematically quantify individual model uncertainty of a best estimate LOCA code, such as RELAP5 and TRAC. Instead of applying a full ranged BELOCA methodology to cover both model and plant status uncertainties, a deterministic-realistic hybrid methodology (DRHM) was developed to support LOCA licensing analysis. Regarding the DRHM methodology, Appendix K deterministic evaluation models are adopted to ensure model conservatism, while CSAU methodology is applied to quantify the effect of plant status uncertainty on PCT calculation. Generally, DRHM methodology can generate about 80-100 K margin on PCT as compared to Appendix K bounding state LOCA analysis.

  10. Fatigue Life Methodology for Tapered Hybrid Composite Flexbeams

    Science.gov (United States)

    urri, Gretchen B.; Schaff, Jeffery R.

    2006-01-01

    Nonlinear-tapered flexbeam specimens from a full-size composite helicopter rotor hub flexbeam were tested under combined constant axial tension and cyclic bending loads. Two different graphite/glass hybrid configurations tested under cyclic loading failed by delamination in the tapered region. A 2-D finite element model was developed which closely approximated the flexbeam geometry, boundary conditions, and loading. The analysis results from two geometrically nonlinear finite element codes, ANSYS and ABAQUS, are presented and compared. Strain energy release rates (G) associated with simulated delamination growth in the flexbeams are presented from both codes. These results compare well with each other and suggest that the initial delamination growth from the tip of the ply-drop toward the thick region of the flexbeam is strongly mode II. The peak calculated G values were used with material characterization data to calculate fatigue life curves for comparison with test data. A curve relating maximum surface strain to number of loading cycles at delamination onset compared well with the test results.

  11. Planning "and" Sprinting: Use of a Hybrid Project Management Methodology within a CIS Capstone Course

    Science.gov (United States)

    Baird, Aaron; Riggins, Frederick J.

    2012-01-01

    An increasing number of information systems projects in industry are managed using hybrid project management methodologies, but this shift in project management methods is not fully represented in our CIS curriculums. CIS capstone courses often include an applied project that is managed with traditional project management methods (plan first,…

  12. Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement

    Science.gov (United States)

    Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.

    In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.

  13. A novel hybrid joining methodology for composite to steel joints

    Science.gov (United States)

    Sarh, Bastian

    This research has established a novel approach for designing, analyzing, and fabricating load bearing structural connections between resin infused composite materials and components made of steel or other metals or alloys. A design philosophy is proposed wherein overlapping joint sections comprised of fiber reinforced plastics (FRP's) and steel members are connected via a combination of adhesive bonding and integrally placed composite pins. A film adhesive is utilized, placed into the dry stack prior to resin infusion and is cured after infusion through either local heat elements or by placing the structure into an oven. The novel manner in which the composite pins are introduced consists of perforating the steel member with holes and placing pre-formed composite pins through them, also prior to resin infusion of the composite section. In this manner joints are co-molded structures such that secondary processing is eliminated. It is shown that such joints blend the structural benefits of adhesive and mechanically connected joints, and that the fabrication process is feasible for low-cost, large-scale production as applicable to the shipbuilding industry. Analysis procedures used for designing such joints are presented consisting of an adhesive joint design theory and a pin placement theory. These analysis tools are used in the design of specimens, specific designs are fabricated, and these evaluated through structural tests. Structural tests include quasi-static loading and low cycle fatigue evaluation. This research has thereby invented a novel philosophy on joints, created the manufacturing technique for fabricating such joints, established simple to apply analysis procedures used in the design of such joints (consisting of both an adhesive and a pin placement analysis), and has validated the methodology through specimen fabrication and testing.

  14. Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

    Science.gov (United States)

    Mohamed, Ahmed

    Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available

  15. REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES

    Directory of Open Access Journals (Sweden)

    R. Chitra

    2013-07-01

    Full Text Available The Healthcare industry generally clinical diagnosis is done mostly by doctor’s expertise and experience. Computer Aided Decision Support System plays a major role in medical field. With the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. From the study it is observed that Hybrid Intelligent Algorithm improves the accuracy of the heart disease prediction system. The commonly used techniques for Heart Disease Prediction and their complexities are summarized in this paper.

  16. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    Directory of Open Access Journals (Sweden)

    Daniel-Petru GHENCEA

    2017-06-01

    Full Text Available The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic. The paper presents a prediction mode obtaining valid range of values for spindles with similar characteristics based on measured data sets from a few spindles test without additional measures being required. Extracting polynomial functions of graphs resulting from simultaneous measurements and predict the dynamics of the two features with multi-objective criterion is the main advantage of this method.

  17. Proceedings of the sixth international symposium on methodologies for intelligent systems (Poster Session)

    Energy Technology Data Exchange (ETDEWEB)

    Harber, K.S. (ed.)

    1991-09-01

    This volume contains papers which have been selected for the poster Session at the Sixth International Symposium for Intelligent Systems held October 1991, The following major areas were covered: expert systems; intelligent databases; knowledge representation; learning and adaptive systems; and logic for artificial intelligence. Nineteen full papers are included. (GHH)

  18. Verification of a hybrid adjoint methodology in Titan for single photon emission computed tomography - 316

    International Nuclear Information System (INIS)

    Royston, K.; Haghighat, A.; Yi, C.

    2010-01-01

    The hybrid deterministic transport code TITAN is being applied to a Single Photon Emission Computed Tomography (SPECT) simulation of a myocardial perfusion study. The TITAN code's hybrid methodology allows the use of a discrete ordinates solver in the phantom region and a characteristics method solver in the collimator region. Currently we seek to validate the adjoint methodology in TITAN for this application using a SPECT model that has been created in the MCNP5 Monte Carlo code. The TITAN methodology was examined based on the response of a single voxel detector placed in front of the heart with and without collimation. For the case without collimation, the TITAN response for single voxel-sized detector had a -9.96% difference relative to the MCNP5 response. To simulate collimation, the adjoint source was specified in directions located within the collimator acceptance angle. For a single collimator hole with a diameter matching the voxel dimension, a difference of -0.22% was observed. Comparisons to groupings of smaller collimator holes of two different sizes resulted in relative differences of 0.60% and 0.12%. The number of adjoint source directions within an acceptance angle was increased and showed no significant change in accuracy. Our results indicate that the hybrid adjoint methodology of TITAN yields accurate solutions greater than a factor of two faster than MCNP5. (authors)

  19. Introducing a Novel Hybrid Artificial Intelligence Algorithm to Optimize Network of Industrial Applications in Modern Manufacturing

    Directory of Open Access Journals (Sweden)

    Aydin Azizi

    2017-01-01

    Full Text Available Recent advances in modern manufacturing industries have created a great need to track and identify objects and parts by obtaining real-time information. One of the main technologies which has been utilized for this need is the Radio Frequency Identification (RFID system. As a result of adopting this technology to the manufacturing industry environment, RFID Network Planning (RNP has become a challenge. Mainly RNP deals with calculating the number and position of antennas which should be deployed in the RFID network to achieve full coverage of the tags that need to be read. The ultimate goal of this paper is to present and evaluate a way of modelling and optimizing nonlinear RNP problems utilizing artificial intelligence (AI techniques. This effort has led the author to propose a novel AI algorithm, which has been named “hybrid AI optimization technique,” to perform optimization of RNP as a hard learning problem. The proposed algorithm is composed of two different optimization algorithms: Redundant Antenna Elimination (RAE and Ring Probabilistic Logic Neural Networks (RPLNN. The proposed hybrid paradigm has been explored using a flexible manufacturing system (FMS, and results have been compared with Genetic Algorithm (GA that demonstrates the feasibility of the proposed architecture successfully.

  20. Multi-objective decoupling algorithm for active distance control of intelligent hybrid electric vehicle

    Science.gov (United States)

    Luo, Yugong; Chen, Tao; Li, Keqiang

    2015-12-01

    The paper presents a novel active distance control strategy for intelligent hybrid electric vehicles (IHEV) with the purpose of guaranteeing an optimal performance in view of the driving functions, optimum safety, fuel economy and ride comfort. Considering the complexity of driving situations, the objects of safety and ride comfort are decoupled from that of fuel economy, and a hierarchical control architecture is adopted to improve the real-time performance and the adaptability. The hierarchical control structure consists of four layers: active distance control object determination, comprehensive driving and braking torque calculation, comprehensive torque distribution and torque coordination. The safety distance control and the emergency stop algorithms are designed to achieve the safety and ride comfort goals. The optimal rule-based energy management algorithm of the hybrid electric system is developed to improve the fuel economy. The torque coordination control strategy is proposed to regulate engine torque, motor torque and hydraulic braking torque to improve the ride comfort. This strategy is verified by simulation and experiment using a forward simulation platform and a prototype vehicle. The results show that the novel control strategy can achieve the integrated and coordinated control of its multiple subsystems, which guarantees top performance of the driving functions and optimum safety, fuel economy and ride comfort.

  1. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Science.gov (United States)

    Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

  2. Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

    International Nuclear Information System (INIS)

    Lazzús, Juan A.; Rivera, Marco; López-Caraballo, Carlos H.

    2016-01-01

    A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

  3. Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Lazzús, Juan A., E-mail: jlazzus@dfuls.cl; Rivera, Marco; López-Caraballo, Carlos H.

    2016-03-11

    A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

  4. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  5. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  6. A Alternative Analog Circuit Design Methodology Employing Integrated Artificial Intelligence Techniques

    Science.gov (United States)

    Tuttle, Jeffery L.

    In consideration of the computer processing power now available to the designer, an alternative analog circuit design methodology is proposed. Computer memory capacities no longer require the reduction of the transistor operational characteristics to an imprecise formulation. Therefore, it is proposed that transistor modelling be abandoned in favor of fully characterized transistor data libraries. Secondly, availability of the transistor libraries would facilitate an automated selection of the most appropriate device(s) for the circuit being designed. More specifically, a preprocessor computer program to a more sophisticated circuit simulator (e.g. SPICE) is developed to assist the designer in developing the basic circuit topology and the selection of the most appropriate transistor. Once this is achieved, the circuit topology and selected transistor data library would be downloaded to the simulator for full circuit operational characterization and subsequent design modifications. It is recognized that the design process is enhanced by the use of heuristics as applied to iterative design results. Accordingly, an artificial intelligence (AI) interface is developed to assist the designer in applying the preprocessor results. To demonstrate the retrofitability of the AI interface to established programs, the interface is specifically designed to be as non-intrusive to the host code as possible. Implementation of the proposed methodology offers the potential to speed the design process, since the preprocessor both minimizes the required number of simulator runs and provides a higher acceptance potential of the initial and subsequent simulator runs. Secondly, part count reductions may be realizable since the circuit topologies are not as strongly driven by transistor limitations. Thirdly, the predicted results should more closely match actual circuit operations since the inadequacies of the transistor models have been virtually eliminated. Finally, the AI interface

  7. A demand-centered, hybrid life-cycle methodology for city-scale greenhouse gas inventories.

    Science.gov (United States)

    Ramaswami, Anu; Hillman, Tim; Janson, Bruce; Reiner, Mark; Thomas, Gregg

    2008-09-01

    Greenhouse gas (GHG) accounting for individual cities is confounded by spatial scale and boundary effects that impact the allocation of regional material and energy flows. This paper develops a demand-centered, hybrid life-cycle-based methodology for conducting city-scale GHG inventories that incorporates (1) spatial allocation of surface and airline travel across colocated cities in larger metropolitan regions, and, (2) life-cycle assessment (LCA) to quantify the embodied energy of key urban materials--food, water, fuel, and concrete. The hybrid methodology enables cities to separately report the GHG impact associated with direct end-use of energy by cities (consistent with EPA and IPCC methods), as well as the impact of extra-boundary activities such as air travel and production of key urban materials (consistent with Scope 3 protocols recommended by the World Resources Institute). Application of this hybrid methodology to Denver, Colorado, yielded a more holistic GHG inventory that approaches a GHG footprint computation, with consistency of inclusions across spatial scale as well as convergence of city-scale per capita GHG emissions (approximately 25 mt CO2e/person/year) with state and national data. The method is shown to have significant policy impacts, and also demonstrates the utility of benchmarks in understanding energy use in various city sectors.

  8. Knowledge-based and model-based hybrid methodology for comprehensive waste minimization in electroplating plants

    Science.gov (United States)

    Luo, Keqin

    1999-11-01

    The electroplating industry of over 10,000 planting plants nationwide is one of the major waste generators in the industry. Large quantities of wastewater, spent solvents, spent process solutions, and sludge are the major wastes generated daily in plants, which costs the industry tremendously for waste treatment and disposal and hinders the further development of the industry. It becomes, therefore, an urgent need for the industry to identify technically most effective and economically most attractive methodologies and technologies to minimize the waste, while the production competitiveness can be still maintained. This dissertation aims at developing a novel WM methodology using artificial intelligence, fuzzy logic, and fundamental knowledge in chemical engineering, and an intelligent decision support tool. The WM methodology consists of two parts: the heuristic knowledge-based qualitative WM decision analysis and support methodology and fundamental knowledge-based quantitative process analysis methodology for waste reduction. In the former, a large number of WM strategies are represented as fuzzy rules. This becomes the main part of the knowledge base in the decision support tool, WMEP-Advisor. In the latter, various first-principles-based process dynamic models are developed. These models can characterize all three major types of operations in an electroplating plant, i.e., cleaning, rinsing, and plating. This development allows us to perform a thorough process analysis on bath efficiency, chemical consumption, wastewater generation, sludge generation, etc. Additional models are developed for quantifying drag-out and evaporation that are critical for waste reduction. The models are validated through numerous industrial experiments in a typical plating line of an industrial partner. The unique contribution of this research is that it is the first time for the electroplating industry to (i) use systematically available WM strategies, (ii) know quantitatively and

  9. Development of a field measurement methodology for studying the thermal indoor environment in hybrid GEOTABS buildings

    DEFF Research Database (Denmark)

    Kazanci, Ongun Berk; Khovalyg, Dolaana; Olesen, Bjarne W.

    2018-01-01

    buildings. The three demonstration buildings were an office building in Luxembourg, an elderly care home in Belgium, and an elementary school in Czech Republic. All of these buildings are equipped with hybrid GEOTABS systems; however, they vary in size and function, which requires a unique measurement...... methodology for studying them. These buildings already have advanced Building Management Systems (BMS); however, a more detailed measurement plan was needed for the purposes of the project to document the current performance of these systems regarding thermal indoor environment and energy performance......, and to be able to document the improvements after the implementation of the MPC. This study provides the details of the developed field measurement methodology for each of these buildings to study the indoor environmental quality (IEQ) in details. The developed measurement methodology can be applied to other...

  10. Methodology Investigation of AI(Artificial Intelligence) Test Officer Support Tool. Volume 1

    Science.gov (United States)

    1989-03-01

    American Association for Artificial inteligence A! ............. Artificial inteliigence AMC ............ Unt:ed States Army Maeriel Comand ASL...block number) FIELD GROUP SUB-GROUP Artificial Intelligence, Expert Systems Automated Aids to Testing 9. ABSTRACT (Continue on reverse if necessary and...identify by block number) This report covers the application of Artificial Intelligence-Techniques to the problem of creating automated tools to

  11. A methodology for optimal sizing of autonomous hybrid PV/wind system

    International Nuclear Information System (INIS)

    Diaf, S.; Diaf, D.; Belhamel, M.; Haddadi, M.; Louche, A.

    2007-01-01

    The present paper presents a methodology to perform the optimal sizing of an autonomous hybrid PV/wind system. The methodology aims at finding the configuration, among a set of systems components, which meets the desired system reliability requirements, with the lowest value of levelized cost of energy. Modelling a hybrid PV/wind system is considered as the first step in the optimal sizing procedure. In this paper, more accurate mathematical models for characterizing PV module, wind generator and battery are proposed. The second step consists to optimize the sizing of a system according to the loss of power supply probability (LPSP) and the levelized cost of energy (LCE) concepts. Considering various types and capacities of system devices, the configurations, which can meet the desired system reliability, are obtained by changing the type and size of the devices systems. The configuration with the lowest LCE gives the optimal choice. Applying this method to an assumed PV/wind hybrid system to be installed at Corsica Island, the simulation results show that the optimal configuration, which meet the desired system reliability requirements (LPSP=0) with the lowest LCE, is obtained for a system comprising a 125 W photovoltaic module, one wind generator (600 W) and storage batteries (using 253 Ah). On the other hand, the device system choice plays an important role in cost reduction as well as in energy production

  12. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Directory of Open Access Journals (Sweden)

    Montri Inthachot

    2016-01-01

    Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

  13. Towards Sustainable Smart Homes by a Hierarchical Hybrid Architecture of an Intelligent Agent

    Directory of Open Access Journals (Sweden)

    K. Yang

    2016-10-01

    Full Text Available A smart home can be realized by the provision of services, such as building control, automation and security implemented in accordance with a user’s request. One of the important issues is how to respond quickly and appropriately to a user’s request in a “dynamic environment”. An intelligent agent infers the user’s intention and provides the intact service. This paper proposes a smart home agent system based on a hierarchical hybrid architecture of a user intention model, which models the user intention as a hierarchical structure and implements it in a dynamic environment. The conventional rule-based approach needs to obtain all information before it is executed, which requires a large number of rules and is hardly scalable as the control objects are increasing. On the other hand, the proposed system consists of several modules that construct a hierarchical user intention model. The smart home system needs to take account of the information, such as time, state of device and state of the home, in addition to users’ intention. We evaluate the performance of the proposed system in a dynamic environment and conduct a blind test with seven subjects to measure the satisfaction of service, resulting in the average score of 81.46.

  14. Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

    Directory of Open Access Journals (Sweden)

    Ahmed Hussein

    2018-01-01

    Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

  15. FIVE PHASE PENTAGON HYBRID STEPPER MOTOR INTELLIGENT HALF/FULL DRIVER

    Directory of Open Access Journals (Sweden)

    Alexandru Morar

    2017-06-01

    Full Text Available Stepper motors are very well suited for positioning applications since they can achieve very good positional accuracy without complicated feedback loops associated with servo systems. In this paper, an intelligent five-phase stepper motor driver of business card size proposed. Constant current chopping technique was applied for the purposes of high torque, high velocity and high efficiency. The driver was designed to drive a middle-sized hybrid stepper motor with wire current rating from 0.4 to 1.5A. An up-to-dated translator of five-phase stepping motor was used to drive the gates of N- channel MOSFET array. The resolution in full/half mode is 0.72/0.36 degrees/step. Moreover, an automatic power down circuit was used to limit the power consuming as the motor stops. Additionally, a self-testing program embedded in a 80C31-CPU (PCL838 can self-test whether the driver is normal or not. This embedded program including linear acceleration and deceleration routines also can serve as a positioning controller. The dimension of this driver is approximate 70x65x35 millimeters, which is smaller than a business card. Experimental results demonstrate that the responses of the driver can reach 60 kilo pulses per second

  16. Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises.

    Science.gov (United States)

    Borrajo, M Lourdes; Baruque, Bruno; Corchado, Emilio; Bajo, Javier; Corchado, Juan M

    2011-08-01

    During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents. The core of the multi-agent system is a type of agent that incorporates a case-based reasoning system and automates the business control process and failure prediction. The stages of the case-based reasoning system are implemented by means of web services: the retrieval stage uses an innovative weighted voting summarization of self-organizing maps ensembles-based method and the reuse stage is implemented by means of a radial basis function neural network. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented.

  17. An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2011-03-01

    Full Text Available Congested roads, high traffic, and parking problems are major concerns for any modern city planning. Congestion of on-street spaces in official neighborhoods may give rise to inappropriate parking areas in office and shopping mall complex during the peak time of official transactions. This paper proposes an intelligent and optimized scheme to solve parking space problem for a small city (e.g., Mauritius using a reactive search technique (named as Tabu Search assisted by rough set. Rough set is being used for the extraction of uncertain rules that exist in the databases of parking situations. The inclusion of rough set theory depicts the accuracy and roughness, which are used to characterize uncertainty of the parking lot. Approximation accuracy is employed to depict accuracy of a rough classification [1] according to different dynamic parking scenarios. And as such, the hybrid metaphor proposed comprising of Tabu Search and rough set could provide substantial research directions for other similar hard optimization problems.

  18. Optimization of the core configuration design using a hybrid artificial intelligence algorithm for research reactors

    International Nuclear Information System (INIS)

    Hedayat, Afshin; Davilu, Hadi; Barfrosh, Ahmad Abdollahzadeh; Sepanloo, Kamran

    2009-01-01

    To successfully carry out material irradiation experiments and radioisotope productions, a high thermal neutron flux at irradiation box over a desired life time of a core configuration is needed. On the other hand, reactor safety and operational constraints must be preserved during core configuration selection. Two main objectives and two safety and operational constraints are suggested to optimize reactor core configuration design. Suggested parameters and conditions are considered as two separate fitness functions composed of two main objectives and two penalty functions. This is a constrained and combinatorial type of a multi-objective optimization problem. In this paper, a fast and effective hybrid artificial intelligence algorithm is introduced and developed to reach a Pareto optimal set. The hybrid algorithm is composed of a fast and elitist multi-objective genetic algorithm (GA) and a fast fitness function evaluating system based on the cascade feed forward artificial neural networks (ANNs). A specific GA representation of core configuration and also special GA operators are introduced and used to overcome the combinatorial constraints of this optimization problem. A software package (Core Pattern Calculator 1) is developed to prepare and reform required data for ANNs training and also to revise the optimization results. Some practical test parameters and conditions are suggested to adjust main parameters of the hybrid algorithm. Results show that introduced ANNs can be trained and estimate selected core parameters of a research reactor very quickly. It improves effectively optimization process. Final optimization results show that a uniform and dense diversity of Pareto fronts are gained over a wide range of fitness function values. To take a more careful selection of Pareto optimal solutions, a revision system is introduced and used. The revision of gained Pareto optimal set is performed by using developed software package. Also some secondary operational

  19. Optimization of the core configuration design using a hybrid artificial intelligence algorithm for research reactors

    Energy Technology Data Exchange (ETDEWEB)

    Hedayat, Afshin, E-mail: ahedayat@aut.ac.i [Department of Nuclear Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Reactor Research and Development School, Nuclear Science and Technology Research Institute (NSTRI), End of North Karegar Street, P.O. Box 14395-836, Tehran (Iran, Islamic Republic of); Davilu, Hadi [Department of Nuclear Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Barfrosh, Ahmad Abdollahzadeh [Department of Computer Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Sepanloo, Kamran [Reactor Research and Development School, Nuclear Science and Technology Research Institute (NSTRI), End of North Karegar Street, P.O. Box 14395-836, Tehran (Iran, Islamic Republic of)

    2009-12-15

    To successfully carry out material irradiation experiments and radioisotope productions, a high thermal neutron flux at irradiation box over a desired life time of a core configuration is needed. On the other hand, reactor safety and operational constraints must be preserved during core configuration selection. Two main objectives and two safety and operational constraints are suggested to optimize reactor core configuration design. Suggested parameters and conditions are considered as two separate fitness functions composed of two main objectives and two penalty functions. This is a constrained and combinatorial type of a multi-objective optimization problem. In this paper, a fast and effective hybrid artificial intelligence algorithm is introduced and developed to reach a Pareto optimal set. The hybrid algorithm is composed of a fast and elitist multi-objective genetic algorithm (GA) and a fast fitness function evaluating system based on the cascade feed forward artificial neural networks (ANNs). A specific GA representation of core configuration and also special GA operators are introduced and used to overcome the combinatorial constraints of this optimization problem. A software package (Core Pattern Calculator 1) is developed to prepare and reform required data for ANNs training and also to revise the optimization results. Some practical test parameters and conditions are suggested to adjust main parameters of the hybrid algorithm. Results show that introduced ANNs can be trained and estimate selected core parameters of a research reactor very quickly. It improves effectively optimization process. Final optimization results show that a uniform and dense diversity of Pareto fronts are gained over a wide range of fitness function values. To take a more careful selection of Pareto optimal solutions, a revision system is introduced and used. The revision of gained Pareto optimal set is performed by using developed software package. Also some secondary operational

  20. Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction.

    Science.gov (United States)

    Park, Seong Ho; Han, Kyunghwa

    2018-03-01

    The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical images. Adoption of an artificial intelligence tool in clinical practice requires careful confirmation of its clinical utility. Herein, the authors explain key methodology points involved in a clinical evaluation of artificial intelligence technology for use in medicine, especially high-dimensional or overparameterized diagnostic or predictive models in which artificial deep neural networks are used, mainly from the standpoints of clinical epidemiology and biostatistics. First, statistical methods for assessing the discrimination and calibration performances of a diagnostic or predictive model are summarized. Next, the effects of disease manifestation spectrum and disease prevalence on the performance results are explained, followed by a discussion of the difference between evaluating the performance with use of internal and external datasets, the importance of using an adequate external dataset obtained from a well-defined clinical cohort to avoid overestimating the clinical performance as a result of overfitting in high-dimensional or overparameterized classification model and spectrum bias, and the essentials for achieving a more robust clinical evaluation. Finally, the authors review the role of clinical trials and observational outcome studies for ultimate clinical verification of diagnostic or predictive artificial intelligence tools through patient outcomes, beyond performance metrics, and how to design such studies. © RSNA, 2018.

  1. SCALE6 Hybrid Deterministic-Stochastic Shielding Methodology for PWR Containment Calculations

    International Nuclear Information System (INIS)

    Matijevic, Mario; Pevec, Dubravko; Trontl, Kresimir

    2014-01-01

    The capabilities and limitations of SCALE6/MAVRIC hybrid deterministic-stochastic shielding methodology (CADIS and FW-CADIS) are demonstrated when applied to a realistic deep penetration Monte Carlo (MC) shielding problem of full-scale PWR containment model. The ultimate goal of such automatic variance reduction (VR) techniques is to achieve acceptable precision for the MC simulation in reasonable time by preparation of phase-space VR parameters via deterministic transport theory methods (discrete ordinates SN) by generating space-energy mesh-based adjoint function distribution. The hybrid methodology generates VR parameters that work in tandem (biased source distribution and importance map) in automated fashion which is paramount step for MC simulation of complex models with fairly uniform mesh tally uncertainties. The aim in this paper was determination of neutron-gamma dose rate distribution (radiation field) over large portions of PWR containment phase-space with uniform MC uncertainties. The sources of ionizing radiation included fission neutrons and gammas (reactor core) and gammas from activated two-loop coolant. Special attention was given to focused adjoint source definition which gave improved MC statistics in selected materials and/or regions of complex model. We investigated benefits and differences of FW-CADIS over CADIS and manual (i.e. analog) MC simulation of particle transport. Computer memory consumption by deterministic part of hybrid methodology represents main obstacle when using meshes with millions of cells together with high SN/PN parameters, so optimization of control and numerical parameters of deterministic module plays important role for computer memory management. We investigated the possibility of using deterministic module (memory intense) with broad group library v7 2 7n19g opposed to fine group library v7 2 00n47g used with MC module to fully take effect of low energy particle transport and secondary gamma emission. Compared with

  2. Improvement of Transient Stability in a Hybrid Power Multi-System Using a Designed NIDC (Novel Intelligent Damping Controller

    Directory of Open Access Journals (Sweden)

    Ting-Chia Ou

    2017-04-01

    Full Text Available This paper endeavors to apply a novel intelligent damping controller (NIDC for the static synchronous compensator (STATCOM to reduce the power fluctuations, voltage support and damping in a hybrid power multi-system. In this paper, we discuss the integration of an offshore wind farm (OWF and a seashore wave power farm (SWPF via a high-voltage, alternating current (HVAC electric power transmission line that connects the STATCOM and the 12-bus hybrid power multi-system. The hybrid multi-system consists of a battery energy storage system (BESS and a micro-turbine generation (MTG. The proposed NIDC consists of a designed proportional–integral–derivative (PID linear controller, an adaptive critic network and a proposed functional link-based novel recurrent fuzzy neural network (FLNRFNN. Test results show that the proposed controller can achieve better damping characteristics and effectively stabilize the network under unstable conditions.

  3. Intelligent computing systems emerging application areas

    CERN Document Server

    Virvou, Maria; Jain, Lakhmi

    2016-01-01

    This book at hand explores emerging scientific and technological areas in which Intelligent Computing Systems provide efficient solutions and, thus, may play a role in the years to come. It demonstrates how Intelligent Computing Systems make use of computational methodologies that mimic nature-inspired processes to address real world problems of high complexity for which exact mathematical solutions, based on physical and statistical modelling, are intractable. Common intelligent computational methodologies are presented including artificial neural networks, evolutionary computation, genetic algorithms, artificial immune systems, fuzzy logic, swarm intelligence, artificial life, virtual worlds and hybrid methodologies based on combinations of the previous. The book will be useful to researchers, practitioners and graduate students dealing with mathematically-intractable problems. It is intended for both the expert/researcher in the field of Intelligent Computing Systems, as well as for the general reader in t...

  4. STAR- A SIMPLE TOOL FOR AUTOMATED REASONING SUPPORTING HYBRID APPLICATIONS OF ARTIFICIAL INTELLIGENCE (UNIX VERSION)

    Science.gov (United States)

    Borchardt, G. C.

    1994-01-01

    The Simple Tool for Automated Reasoning program (STAR) is an interactive, interpreted programming language for the development and operation of artificial intelligence (AI) application systems. STAR provides an environment for integrating traditional AI symbolic processing with functions and data structures defined in compiled languages such as C, FORTRAN and PASCAL. This type of integration occurs in a number of AI applications including interpretation of numerical sensor data, construction of intelligent user interfaces to existing compiled software packages, and coupling AI techniques with numerical simulation techniques and control systems software. The STAR language was created as part of an AI project for the evaluation of imaging spectrometer data at NASA's Jet Propulsion Laboratory. Programming in STAR is similar to other symbolic processing languages such as LISP and CLIP. STAR includes seven primitive data types and associated operations for the manipulation of these structures. A semantic network is used to organize data in STAR, with capabilities for inheritance of values and generation of side effects. The AI knowledge base of STAR can be a simple repository of records or it can be a highly interdependent association of implicit and explicit components. The symbolic processing environment of STAR may be extended by linking the interpreter with functions defined in conventional compiled languages. These external routines interact with STAR through function calls in either direction, and through the exchange of references to data structures. The hybrid knowledge base may thus be accessed and processed in general by either side of the application. STAR is initially used to link externally compiled routines and data structures. It is then invoked to interpret the STAR rules and symbolic structures. In a typical interactive session, the user enters an expression to be evaluated, STAR parses the input, evaluates the expression, performs any file input

  5. STAR- A SIMPLE TOOL FOR AUTOMATED REASONING SUPPORTING HYBRID APPLICATIONS OF ARTIFICIAL INTELLIGENCE (DEC VAX VERSION)

    Science.gov (United States)

    Borchardt, G. C.

    1994-01-01

    The Simple Tool for Automated Reasoning program (STAR) is an interactive, interpreted programming language for the development and operation of artificial intelligence (AI) application systems. STAR provides an environment for integrating traditional AI symbolic processing with functions and data structures defined in compiled languages such as C, FORTRAN and PASCAL. This type of integration occurs in a number of AI applications including interpretation of numerical sensor data, construction of intelligent user interfaces to existing compiled software packages, and coupling AI techniques with numerical simulation techniques and control systems software. The STAR language was created as part of an AI project for the evaluation of imaging spectrometer data at NASA's Jet Propulsion Laboratory. Programming in STAR is similar to other symbolic processing languages such as LISP and CLIP. STAR includes seven primitive data types and associated operations for the manipulation of these structures. A semantic network is used to organize data in STAR, with capabilities for inheritance of values and generation of side effects. The AI knowledge base of STAR can be a simple repository of records or it can be a highly interdependent association of implicit and explicit components. The symbolic processing environment of STAR may be extended by linking the interpreter with functions defined in conventional compiled languages. These external routines interact with STAR through function calls in either direction, and through the exchange of references to data structures. The hybrid knowledge base may thus be accessed and processed in general by either side of the application. STAR is initially used to link externally compiled routines and data structures. It is then invoked to interpret the STAR rules and symbolic structures. In a typical interactive session, the user enters an expression to be evaluated, STAR parses the input, evaluates the expression, performs any file input

  6. Research on the Special Railway Intelligence Transportation Hierarchy and System Integration Methodology

    Directory of Open Access Journals (Sweden)

    Meng-Jie WANG

    2013-05-01

    Full Text Available Following the rapid development of information technology in the field of railway transportation, the problems of establishing a digital, integrated and intelligent special railway system need to be solved immediately. This paper designs and implements the intelligent transportation information system based on the unique pattern of transportation organization, the characteristics of transportation operations and the workflow of special railway. Through the detailed analysis of system architecture and framework design, the main subsystems and the internal comprehensive integrated principle, business system from a system integration perspective of the special railway is optimized, which can be able to realize the integration of all kinds of information resources. The implementation of integration and the special railway intelligent system is a great change in terms of maximizing transportation capacity, improving efficiency and guaranteeing the safety of special railway transportation.

  7. Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rajeev Kumar

    2016-01-01

    Full Text Available Currently, wireless sensor networks (WSNs are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i selection of optimal number of subregions and further subregion parts, (ii cluster head selection using ABC algorithm, and (iii efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS. The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively.

  8. VEHIL: a full-scale test methodology for intelligent transport systems, vehicles and subsystems

    NARCIS (Netherlands)

    Verhoeff, L.; Verburg, D.J.; Lupker, H.A.; Kusters, L.J.J.

    2000-01-01

    To enhance the efficiency and safety of today's road transport, the application of driver support systems and fully automated, intelligent transport systems becomes increasingly important. The safety and reliability requirements of these systems and their complexity are high, which results in a

  9. Joint Intelligence Operations Center (JIOC) Baseline Business Process Model & Capabilities Evaluation Methodology

    Science.gov (United States)

    2012-03-01

    Targeting Review Board OPLAN Operations Plan OPORD Operations Order OPSIT Operational Situation OSINT Open Source Intelligence OV...Analysis Evaluate FLTREPs MISREPs Unit Assign Assets Feedback Asset Shortfalls Multi-Int Collection Political & Embasy Law Enforcement HUMINT OSINT ...Embassy Information OSINT Manage Theater HUMINT Law Enforcement Collection Sort Requests Platform Information Agency Information M-I Collect

  10. New methodology of designing inexpensive hybrid control-acquisition systems for mechatronic constructions.

    Science.gov (United States)

    Augustyn, Jacek

    2013-12-13

    This article presents a new methodology for designing a hybrid control and acquisition system consisting of a 32-bit SoC microsystem connected via a direct Universal Serial Bus (USB) with a standard commercial off-the-shelf (COTS) component running the Android operating system. It is proposed to utilize it avoiding the use of an additional converter. An Android-based component was chosen to explore the potential for a mobile, compact and energy efficient solution with easy to build user interfaces and easy wireless integration with other computer systems. This paper presents results of practical implementation and analysis of experimental real-time performance. It covers closed control loop time between the sensor/actuator module and the Android operating system as well as the real-time sensor data stream within such a system. Some optimisations are proposed and their influence on real-time performance was investigated. The proposed methodology is intended for acquisition and control of mechatronic systems, especially mobile robots. It can be used in a wide range of control applications as well as embedded acquisition-recording devices, including energy quality measurements, smart-grids and medicine. It is demonstrated that the proposed methodology can be employed without developing specific device drivers. The latency achieved was less than 0.5 ms and the sensor data stream throughput was on the order of 750 KB/s (compared to 3 ms latency and 300 KB/s in traditional solutions).

  11. AN INDUCTIVE, INTERACTIVE AND ADAPTIVE HYBRID PROBLEM-BASED LEARNING METHODOLOGY: APPLICATION TO STATISTICS

    Directory of Open Access Journals (Sweden)

    ADA ZHENG

    2011-10-01

    Full Text Available We have developed an innovative hybrid problem-based learning (PBL methodology. The methodology has the following distinctive features: i Each complex question was decomposed into a set of coherent finer subquestions by following the carefully designed criteria to maintain a delicate balance between guiding the students and inspiring them to think independently. This learning methodology enabled the students to solve the complex questions progressively in an inductive context. ii Facilitated by the utilization of our web-based learning systems, the teacher was able to interact with the students intensively and could allocate more teaching time to provide tailor-made feedback for individual student. The students were actively engaged in the learning activities, stimulated by the intensive interaction. iii The answers submitted by the students could be automatically consolidated in the report of the Moodle system in real-time. The teacher could adjust the teaching schedule and focus of the class to adapt to the learning progress of the students by analysing the automatically generated report and log files of the web-based learning system. As a result, the attendance rate of the students increased from about 50% to more than 90%, and the students’ learning motivation have been significantly enhanced.

  12. Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

    Energy Technology Data Exchange (ETDEWEB)

    Harber, K.S. (ed.)

    1993-05-01

    This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries. These papers have been indexed separately.

  13. Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

    Energy Technology Data Exchange (ETDEWEB)

    Harber, K.S. [ed.

    1993-05-01

    This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries. These papers have been indexed separately.

  14. A hybrid design methodology for structuring an Integrated Environmental Management System (IEMS) for shipping business.

    Science.gov (United States)

    Celik, Metin

    2009-03-01

    The International Safety Management (ISM) Code defines a broad framework for the safe management and operation of merchant ships, maintaining high standards of safety and environmental protection. On the other hand, ISO 14001:2004 provides a generic, worldwide environmental management standard that has been utilized by several industries. Both the ISM Code and ISO 14001:2004 have the practical goal of establishing a sustainable Integrated Environmental Management System (IEMS) for shipping businesses. This paper presents a hybrid design methodology that shows how requirements from both standards can be combined into a single execution scheme. Specifically, the Analytic Hierarchy Process (AHP) and Fuzzy Axiomatic Design (FAD) are used to structure an IEMS for ship management companies. This research provides decision aid to maritime executives in order to enhance the environmental performance in the shipping industry.

  15. A new methodological development for solving linear bilevel integer programming problems in hybrid fuzzy environment

    Directory of Open Access Journals (Sweden)

    Animesh Biswas

    2016-04-01

    Full Text Available This paper deals with fuzzy goal programming approach to solve fuzzy linear bilevel integer programming problems with fuzzy probabilistic constraints following Pareto distribution and Frechet distribution. In the proposed approach a new chance constrained programming methodology is developed from the view point of managing those probabilistic constraints in a hybrid fuzzy environment. A method of defuzzification of fuzzy numbers using ?-cut has been adopted to reduce the problem into a linear bilevel integer programming problem. The individual optimal value of the objective of each DM is found in isolation to construct the fuzzy membership goals. Finally, fuzzy goal programming approach is used to achieve maximum degree of each of the membership goals by minimizing under deviational variables in the decision making environment. To demonstrate the efficiency of the proposed approach, a numerical example is provided.

  16. Development and application of a hybrid transport methodology for active interrogation systems

    Energy Technology Data Exchange (ETDEWEB)

    Royston, K.; Walters, W.; Haghighat, A. [Nuclear Engineering Program, Department of Mechanical Engineering, Virginia Tech., 900 N Glebe Rd., Arlington, VA 22203 (United States); Yi, C.; Sjoden, G. [Nuclear and Radiological Engineering, Georgia Tech, 801 Ferst Drive, Atlanta, GA 30332 (United States)

    2013-07-01

    A hybrid Monte Carlo and deterministic methodology has been developed for application to active interrogation systems. The methodology consists of four steps: i) neutron flux distribution due to neutron source transport and subcritical multiplication; ii) generation of gamma source distribution from (n, 7) interactions; iii) determination of gamma current at a detector window; iv) detection of gammas by the detector. This paper discusses the theory and results of the first three steps for the case of a cargo container with a sphere of HEU in third-density water cargo. To complete the first step, a response-function formulation has been developed to calculate the subcritical multiplication and neutron flux distribution. Response coefficients are pre-calculated using the MCNP5 Monte Carlo code. The second step uses the calculated neutron flux distribution and Bugle-96 (n, 7) cross sections to find the resulting gamma source distribution. In the third step the gamma source distribution is coupled with a pre-calculated adjoint function to determine the gamma current at a detector window. The AIMS (Active Interrogation for Monitoring Special-Nuclear-Materials) software has been written to output the gamma current for a source-detector assembly scanning across a cargo container using the pre-calculated values and taking significantly less time than a reference MCNP5 calculation. (authors)

  17. SCALE6.1 Hybrid Shielding Methodology For The Spent Fuel Dry Storage

    International Nuclear Information System (INIS)

    Matijevic, M.; Pevec, D.; Trontl, K.

    2015-01-01

    The SCALE6.1/MAVRIC hybrid deterministic-stochastic shielding methodology was used for dose rates calculation of the generic spent fuel dry storage installation. The neutron-gamma dose rates around the cask array were calculated over a large problem domain in order to determine the boundary of the controlled area. The FW-CADIS methodology, based on the deterministic forward and adjoint solution over the phase - space, was used for optimized, global Monte Carlo results over the mesh tally. The cask inventory was modeled as homogenized material corresponding to 20 fuel assemblies from a standard mid - sized PWR reactor. The global simulation model was an array of 32 casks in 2 rows with concrete foundations and external air, which makes a large spatial domain for shielding calculations. The dose rates around the casks were determined using FW-CADIS method with weighted adjoint source and mesh tally covering a portion of spatial domain of interest. The conservatively obtained dose rates give the upper boundary, since the activation reduction of sources was not taken into account when sequential filling of the dry storage will start. The effective area of the dry storage installation can be additionally reduced with lowering concrete foundation under the ground, embankment raising, and with extra concrete walls, that would additionally lower the dominant gamma dose rates. (author).

  18. An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

    OpenAIRE

    Carreras Pérez, Marc; Yuh, Junku; Batlle i Grabulosa, Joan

    2001-01-01

    Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

  19. Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system

    International Nuclear Information System (INIS)

    Hong, Chih-Ming; Ou, Ting-Chia; Lu, Kai-Hung

    2013-01-01

    A hybrid power control system is proposed in the paper, consisting of solar power, wind power, and a diesel-engine. To achieve a fast and stable response for the real power control, an intelligent controller was proposed, which consists of the Wilcoxon (radial basis function network) RBFN and the improved (Elman neural network) ENN for (maximum power point tracking) MPPT. The pitch angle control of wind power uses improved ENN controller, and the output is fed to the wind turbine to achieve the MPPT. The solar array is integrated with an RBFN control algorithm to track the maximum power. MATLAB (MATrix LABoratory)/Simulink was used to build the dynamic model and simulate the solar and diesel-wind hybrid power system. - Highlights: ► To achieve a fast and stable response for the real power control. ► The pitch control of wind power uses improved ENN (Elman neural network) controller to achieve the MPPT (maximum power point tracking). ► The RBFN (radial basis function network) can quickly and accurately track the maximum power output for PV (photovoltaic) array. ► MATLAB was used to build the dynamic model and simulate the hybrid power system. ► This method can reach the desired performance even under different load conditions

  20. An Intelligent Gear Fault Diagnosis Methodology Using a Complex Wavelet Enhanced Convolutional Neural Network.

    Science.gov (United States)

    Sun, Weifang; Yao, Bin; Zeng, Nianyin; Chen, Binqiang; He, Yuchao; Cao, Xincheng; He, Wangpeng

    2017-07-12

    As a typical example of large and complex mechanical systems, rotating machinery is prone to diversified sorts of mechanical faults. Among these faults, one of the prominent causes of malfunction is generated in gear transmission chains. Although they can be collected via vibration signals, the fault signatures are always submerged in overwhelming interfering contents. Therefore, identifying the critical fault's characteristic signal is far from an easy task. In order to improve the recognition accuracy of a fault's characteristic signal, a novel intelligent fault diagnosis method is presented. In this method, a dual-tree complex wavelet transform (DTCWT) is employed to acquire the multiscale signal's features. In addition, a convolutional neural network (CNN) approach is utilized to automatically recognise a fault feature from the multiscale signal features. The experiment results of the recognition for gear faults show the feasibility and effectiveness of the proposed method, especially in the gear's weak fault features.

  1. An Intelligent Gear Fault Diagnosis Methodology Using a Complex Wavelet Enhanced Convolutional Neural Network

    Science.gov (United States)

    Sun, Weifang; Yao, Bin; Zeng, Nianyin; He, Yuchao; Cao, Xincheng; He, Wangpeng

    2017-01-01

    As a typical example of large and complex mechanical systems, rotating machinery is prone to diversified sorts of mechanical faults. Among these faults, one of the prominent causes of malfunction is generated in gear transmission chains. Although they can be collected via vibration signals, the fault signatures are always submerged in overwhelming interfering contents. Therefore, identifying the critical fault’s characteristic signal is far from an easy task. In order to improve the recognition accuracy of a fault’s characteristic signal, a novel intelligent fault diagnosis method is presented. In this method, a dual-tree complex wavelet transform (DTCWT) is employed to acquire the multiscale signal’s features. In addition, a convolutional neural network (CNN) approach is utilized to automatically recognise a fault feature from the multiscale signal features. The experiment results of the recognition for gear faults show the feasibility and effectiveness of the proposed method, especially in the gear’s weak fault features. PMID:28773148

  2. A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search.

    Science.gov (United States)

    Villagra, Andrea; Alba, Enrique; Leguizamón, Guillermo

    2016-01-01

    This work presents the results of a new methodology for hybridizing metaheuristics. By first locating the active components (parts) of one algorithm and then inserting them into second one, we can build efficient and accurate optimization, search, and learning algorithms. This gives a concrete way of constructing new techniques that contrasts the spread ad hoc way of hybridizing. In this paper, the enhanced algorithm is a Cellular Genetic Algorithm (cGA) which has been successfully used in the past to find solutions to such hard optimization problems. In order to extend and corroborate the use of active components as an emerging hybridization methodology, we propose here the use of active components taken from Scatter Search (SS) to improve cGA. The results obtained over a varied set of benchmarks are highly satisfactory in efficacy and efficiency when compared with a standard cGA. Moreover, the proposed hybrid approach (i.e., cGA+SS) has shown encouraging results with regard to earlier applications of our methodology.

  3. A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search

    Directory of Open Access Journals (Sweden)

    Andrea Villagra

    2016-01-01

    Full Text Available This work presents the results of a new methodology for hybridizing metaheuristics. By first locating the active components (parts of one algorithm and then inserting them into second one, we can build efficient and accurate optimization, search, and learning algorithms. This gives a concrete way of constructing new techniques that contrasts the spread ad hoc way of hybridizing. In this paper, the enhanced algorithm is a Cellular Genetic Algorithm (cGA which has been successfully used in the past to find solutions to such hard optimization problems. In order to extend and corroborate the use of active components as an emerging hybridization methodology, we propose here the use of active components taken from Scatter Search (SS to improve cGA. The results obtained over a varied set of benchmarks are highly satisfactory in efficacy and efficiency when compared with a standard cGA. Moreover, the proposed hybrid approach (i.e., cGA+SS has shown encouraging results with regard to earlier applications of our methodology.

  4. Computational intelligence as a platform for data collection methodology in management science

    DEFF Research Database (Denmark)

    Jespersen, Kristina Risom

    2006-01-01

    With the increased focus in management science on how to collect data close to the real-world of managers, then agent-based simulations have interesting prospects that are usable for the design of business applications aimed at the collection of data. As a new generation of data collection...... methodologies this chapter discusses and presents a behavioral simulation founded in the agent-based simulation life cycle and supported by Web technology. With agent-based modeling the complexity of the method is increased without limiting the research due to the technological support, because this makes...... it possible to exploit the advantages of a questionnaire, an experimental design, a role-play and a scenario as such gaining the synergy effect of these methodologies. At the end of the chapter an example of a simulation is presented for researchers and practitioners to study....

  5. A High-Performance Embedded Hybrid Methodology for Uncertainty Quantification With Applications

    Energy Technology Data Exchange (ETDEWEB)

    Iaccarino, Gianluca

    2014-04-01

    Multiphysics processes modeled by a system of unsteady di erential equations are natu- rally suited for partitioned (modular) solution strategies. We consider such a model where probabilistic uncertainties are present in each module of the system and represented as a set of random input parameters. A straightforward approach in quantifying uncertainties in the predicted solution would be to sample all the input parameters into a single set, and treat the full system as a black-box. Although this method is easily parallelizable and requires minimal modi cations to deterministic solver, it is blind to the modular structure of the underlying multiphysical model. On the other hand, using spectral representations polynomial chaos expansions (PCE) can provide richer structural information regarding the dynamics of these uncertainties as they propagate from the inputs to the predicted output, but can be prohibitively expensive to implement in the high-dimensional global space of un- certain parameters. Therefore, we investigated hybrid methodologies wherein each module has the exibility of using sampling or PCE based methods of capturing local uncertainties while maintaining accuracy in the global uncertainty analysis. For the latter case, we use a conditional PCE model which mitigates the curse of dimension associated with intru- sive Galerkin or semi-intrusive Pseudospectral methods. After formalizing the theoretical framework, we demonstrate our proposed method using a numerical viscous ow simulation and benchmark the performance against a solely Monte-Carlo method and solely spectral method.

  6. Calibration methodology for energy management system of a plug-in hybrid electric vehicle

    International Nuclear Information System (INIS)

    Duan, Benming; Wang, Qingnian; Zeng, Xiaohua; Gong, Yinsheng; Song, Dafeng; Wang, Junnian

    2017-01-01

    Highlights: • Calibration theory of EMS is proposed. • A comprehensive evaluating indicator is constructed by radar chart method. • Optimal Latin hypercube design algorithm is introduced to obtain training data. • An approximation model is established by using a RBF neural network. • Offline calibration methodology improves the actual calibration efficiency. - Abstract: This paper presents a new analytical calibration method for energy management strategy designed for a plug-in hybrid electric vehicle. This method improves the actual calibration efficiency to reach a compromise among the conflicting calibration requirements (e.g. emissions and economy). A comprehensive evaluating indicator covering emissions and economic performance is constructed by using a radar chart method. A radial basis functions (RBFs) neural network model is proposed to establish a precise model among control parameters and the comprehensive evaluation indicator. The optimal Latin hypercube design is introduced to obtain the experimental data to train the RBFs neural network model. And multi-island genetic algorithm is used to solve the optimization model. Finally, an offline calibration example is conducted. Results validate the effectiveness of the proposed calibration approach in improving vehicle performance and calibration efficiency.

  7. Developing emotional intelligence in student nurse leaders: a mixed methodology study

    Science.gov (United States)

    Szeles, Heather M.

    2015-01-01

    Objective: The purpose of this mixed method, exploratory study was to measure the impact of a peer coaching program on the measured emotional intelligence (EI) of a group of student nurse leaders. Methods Participation in the study was offered to nurses in the Student Ambassador program. Students who consented received instruction on EI and its importance in leadership. Participants then took a preintervention EI test (The Mayer-Salovey-Caruso EI Test, version 2 [MSCEIT]) to obtain a baseline EI ability score. Students then participated in a series of peer coaching sessions across a semester. Participants then completed a postintervention MSCEIT test, and also a qualitative survey. Results: The analysis of the paired sample t-test showed that there was not a statistically significant difference in the total group EI scores from pre to posttest, t (8) = 0.036 >0.05; however, 80% of participants reported perceived changes in EI ability due to the intervention and 90% reported that peer coaching was beneficial to their leadership development. Conclusions: This study contributes to the body of EI literature and research on nursing education and leadership development. PMID:27981099

  8. Developing emotional intelligence in student nurse leaders: a mixed methodology study

    Directory of Open Access Journals (Sweden)

    Heather M Szeles

    2015-01-01

    Full Text Available Objective: The purpose of this mixed method, exploratory study was to measure the impact of a peer coaching program on the measured emotional intelligence (EI of a group of student nurse leaders. Methods Participation in the study was offered to nurses in the Student Ambassador program. Students who consented received instruction on EI and its importance in leadership. Participants then took a preintervention EI test (The Mayer-Salovey-Caruso EI Test, version 2 [MSCEIT] to obtain a baseline EI ability score. Students then participated in a series of peer coaching sessions across a semester. Participants then completed a postintervention MSCEIT test, and also a qualitative survey. Results: The analysis of the paired sample t-test showed that there was not a statistically significant difference in the total group EI scores from pre to posttest, t (8 = 0.036 >0.05; however, 80% of participants reported perceived changes in EI ability due to the intervention and 90% reported that peer coaching was beneficial to their leadership development. Conclusions: This study contributes to the body of EI literature and research on nursing education and leadership development.

  9. ANN-PSO Integrated Optimization Methodology for Intelligent Control of MMC Machining

    Science.gov (United States)

    Chandrasekaran, Muthumari; Tamang, Santosh

    2017-08-01

    Metal Matrix Composites (MMC) show improved properties in comparison with non-reinforced alloys and have found increased application in automotive and aerospace industries. The selection of optimum machining parameters to produce components of desired surface roughness is of great concern considering the quality and economy of manufacturing process. In this study, a surface roughness prediction model for turning Al-SiCp MMC is developed using Artificial Neural Network (ANN). Three turning parameters viz., spindle speed ( N), feed rate ( f) and depth of cut ( d) were considered as input neurons and surface roughness was an output neuron. ANN architecture having 3 -5 -1 is found to be optimum and the model predicts with an average percentage error of 7.72 %. Particle Swarm Optimization (PSO) technique is used for optimizing parameters to minimize machining time. The innovative aspect of this work is the development of an integrated ANN-PSO optimization method for intelligent control of MMC machining process applicable to manufacturing industries. The robustness of the method shows its superiority for obtaining optimum cutting parameters satisfying desired surface roughness. The method has better convergent capability with minimum number of iterations.

  10. Hybrid Taguchi DNA Swarm Intelligence for Optimal Inverse Kinematics Redundancy Resolution of Six-DOF Humanoid Robot Arms

    Directory of Open Access Journals (Sweden)

    Hsu-Chih Huang

    2014-01-01

    Full Text Available This paper presents a hybrid Taguchi deoxyribonucleic acid (DNA swarm intelligence for solving the inverse kinematics redundancy problem of six degree-of-freedom (DOF humanoid robot arms. The inverse kinematics problem of the multi-DOF humanoid robot arm is redundant and has no general closed-form solutions or analytical solutions. The optimal joint configurations are obtained by minimizing the predefined performance index in DNA algorithm for real-world humanoid robotics application. The Taguchi method is employed to determine the DNA parameters to search for the joint solutions of the six-DOF robot arms more efficiently. This approach circumvents the disadvantage of time-consuming tuning procedure in conventional DNA computing. Simulation results are conducted to illustrate the effectiveness and merit of the proposed methods. This Taguchi-based DNA (TDNA solver outperforms the conventional solvers, such as geometric solver, Jacobian-based solver, genetic algorithm (GA solver and ant, colony optimization (ACO solver.

  11. 'Intelligent' triggering methodology for improved detectability of wavelength modulation diode laser absorption spectrometry applied to window-equipped graphite furnaces

    International Nuclear Information System (INIS)

    Gustafsson, Joergen; Axner, Ove

    2003-01-01

    The wavelength modulation-diode laser absorption spectrometry (WM-DLAS) technique experiences a limited detectability when window-equipped sample compartments are used because of multiple reflections between components in the optical system (so-called etalon effects). The problem is particularly severe when the technique is used with a window-equipped graphite furnace (GF) as atomizer since the heating of the furnace induces drifts of the thickness of the windows and thereby also of the background signals. This paper presents a new detection methodology for WM-DLAS applied to a window-equipped GF in which the influence of the background signals from the windows is significantly reduced. The new technique, which is based upon a finding that the WM-DLAS background signals from a window-equipped GF are reproducible over a considerable period of time, consists of a novel 'intelligent' triggering procedure in which the GF is triggered at a user-chosen 'position' in the reproducible drift-cycle of the WM-DLAS background signal. The new methodology makes also use of 'higher-than-normal' detection harmonics, i.e. 4f or 6f, since these previously have shown to have a higher signal-to-background ratio than 2f-detection when the background signals originates from thin etalons. The results show that this new combined background-drift-reducing methodology improves the limit of detection of the WM-DLAS technique used with a window-equipped GF by several orders of magnitude as compared to ordinary 2f-detection, resulting in a limit of detection for a window-equipped GF that is similar to that of an open GF

  12. The Weighted Support Vector Machine Based on Hybrid Swarm Intelligence Optimization for Icing Prediction of Transmission Line

    Directory of Open Access Journals (Sweden)

    Xiaomin Xu

    2015-01-01

    Full Text Available Not only can the icing coat on transmission line cause the electrical fault of gap discharge and icing flashover but also it will lead to the mechanical failure of tower, conductor, insulators, and others. It will bring great harm to the people’s daily life and work. Thus, accurate prediction of ice thickness has important significance for power department to control the ice disaster effectively. Based on the analysis of standard support vector machine, this paper presents a weighted support vector machine regression model based on the similarity (WSVR. According to the different importance of samples, this paper introduces the weighted support vector machine and optimizes its parameters by hybrid swarm intelligence optimization algorithm with the particle swarm and ant colony (PSO-ACO, which improves the generalization ability of the model. In the case study, the actual data of ice thickness and climate in a certain area of Hunan province have been used to predict the icing thickness of the area, which verifies the validity and applicability of this proposed method. The predicted results show that the intelligent model proposed in this paper has higher precision and stronger generalization ability.

  13. Swarm Intelligence-Based Smart Energy Allocation Strategy for Charging Stations of Plug-In Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Imran Rahman

    2015-01-01

    Full Text Available Recent researches towards the use of green technologies to reduce pollution and higher penetration of renewable energy sources in the transportation sector have been gaining popularity. In this wake, extensive participation of plug-in hybrid electric vehicles (PHEVs requires adequate charging allocation strategy using a combination of smart grid systems and smart charging infrastructures. Daytime charging stations will be needed for daily usage of PHEVs due to the limited all-electric range. Intelligent energy management is an important issue which has already drawn much attention of researchers. Most of these works require formulation of mathematical models with extensive use of computational intelligence-based optimization techniques to solve many technical problems. In this paper, gravitational search algorithm (GSA has been applied and compared with another member of swarm family, particle swarm optimization (PSO, considering constraints such as energy price, remaining battery capacity, and remaining charging time. Simulation results obtained for maximizing the highly nonlinear objective function evaluate the performance of both techniques in terms of best fitness.

  14. Watermark: An Application and Methodology and Application for Interactive and intelligent Decision Support for Groundwater Systems

    Science.gov (United States)

    Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.

    2016-12-01

    Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.

  15. Recent advances in knowledge-based paradigms and applications enhanced applications using hybrid artificial intelligence techniques

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research , Computational Intelligence and Machine Intelligence including an introduction to  the recent research and models. Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.

  16. Hybrid soft computing approaches research and applications

    CERN Document Server

    Dutta, Paramartha; Chakraborty, Susanta

    2016-01-01

    The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

  17. EINSTEIN - Expert system for an Intelligent Supply of Thermal Energy in Industry. Audit methodology and software tool

    Energy Technology Data Exchange (ETDEWEB)

    Schweiger, Hans; Danov, Stoyan (energyXperts.NET (Spain)); Vannoni, Claudia; Facci, Enrico (Sapienza Univ. of Rome, Dept. of Mechanics and Aeronautics, Rome (Italy)); Brunner, Christoph; Slawitsch, Bettina (Joanneum Research, Inst. of Sustainable Techniques and Systems - JOINTS, Graz (Austria))

    2009-07-01

    For optimising thermal energy supply in industry, a holistic integral approach is required that includes possibilities of demand reduction by heat recovery and process integration, and by an intelligent combination of efficient heat and cold supply technologies. EINSTEIN is a tool-kit for fast and high quality thermal energy audits in industry, composed by an audit guide describing the methodology and by a software tool that guides the auditor through all the audit steps. The main features of EINSTEIN are: (1) a basic questionnaire helps for systematic collection of the necessary information with the possibility to acquire data by distance; (2) special tools allow for fast consistency checking and estimation of missing data, so that already with very few data some first predictions can be made; (3) the data processing is based on standardised models for industrial processes and industrial heat supply systems; (4) semi-automatization: the software tool gives support to decision making for the generation of alternative heat and cold supply proposals, carries out automatically all the necessary calculations, including dynamic simulation of the heat supply system, and creates a standard audit report. The software tool includes modules for benchmarking, automatic design of heat exchanger networks, and design assistants for the heat and cold supply system. The core of the expert system software tool is available for free, as an open source software project. This type of software development has shown to be very efficient for dissemination of knowledge and for the continuous maintenance and improvement thanks to user contributions.

  18. An intelligent switch with back-propagation neural network based hybrid power system

    Science.gov (United States)

    Perdana, R. H. Y.; Fibriana, F.

    2018-03-01

    The consumption of conventional energy such as fossil fuels plays the critical role in the global warming issues. The carbon dioxide, methane, nitrous oxide, etc. could lead the greenhouse effects and change the climate pattern. In fact, 77% of the electrical energy is generated from fossil fuels combustion. Therefore, it is necessary to use the renewable energy sources for reducing the conventional energy consumption regarding electricity generation. This paper presents an intelligent switch to combine both energy resources, i.e., the solar panels as the renewable energy with the conventional energy from the State Electricity Enterprise (PLN). The artificial intelligence technology with the back-propagation neural network was designed to control the flow of energy that is distributed dynamically based on renewable energy generation. By the continuous monitoring on each load and source, the dynamic pattern of the intelligent switch was better than the conventional switching method. The first experimental results for 60 W solar panels showed the standard deviation of the trial at 0.7 and standard deviation of the experiment at 0.28. The second operation for a 900 W of solar panel obtained the standard deviation of the trial at 0.05 and 0.18 for the standard deviation of the experiment. Moreover, the accuracy reached 83% using this method. By the combination of the back-propagation neural network with the observation of energy usage of the load using wireless sensor network, each load can be evenly distributed and will impact on the reduction of conventional energy usage.

  19. Hybrid Modeling and Optimization of Manufacturing Combining Artificial Intelligence and Finite Element Method

    CERN Document Server

    Quiza, Ramón; Davim, J Paulo

    2012-01-01

    Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.

  20. Hybrid neuro-heuristic methodology for simulation and control of dynamic systems over time interval.

    Science.gov (United States)

    Woźniak, Marcin; Połap, Dawid

    2017-09-01

    Simulation and positioning are very important aspects of computer aided engineering. To process these two, we can apply traditional methods or intelligent techniques. The difference between them is in the way they process information. In the first case, to simulate an object in a particular state of action, we need to perform an entire process to read values of parameters. It is not very convenient for objects for which simulation takes a long time, i.e. when mathematical calculations are complicated. In the second case, an intelligent solution can efficiently help on devoted way of simulation, which enables us to simulate the object only in a situation that is necessary for a development process. We would like to present research results on developed intelligent simulation and control model of electric drive engine vehicle. For a dedicated simulation method based on intelligent computation, where evolutionary strategy is simulating the states of the dynamic model, an intelligent system based on devoted neural network is introduced to control co-working modules while motion is in time interval. Presented experimental results show implemented solution in situation when a vehicle transports things over area with many obstacles, what provokes sudden changes in stability that may lead to destruction of load. Therefore, applied neural network controller prevents the load from destruction by positioning characteristics like pressure, acceleration, and stiffness voltage to absorb the adverse changes of the ground. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO

    Directory of Open Access Journals (Sweden)

    Mehdi Neshat

    2015-11-01

    Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.

  2. Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

    Science.gov (United States)

    Salehi, Mojtaba; Bahreininejad, Ardeshir

    2011-08-01

    Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

  3. Northeast Artificial Intelligence Consortium Annual Report. 1988 Interference Techniques for Knowledge Base Maintenance Using Logic Programming Methodologies. Volume 11

    Science.gov (United States)

    1989-10-01

    Northeast Aritificial Intelligence Consortium (NAIC). i Table of Contents Execu tive Sum m ary...o g~nIl ’vLr COPY o~ T- RADC-TR-89-259, Vol XI (of twelve) N Interim Report SOctober 1989 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT...ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (If applicable) Intelligence Consortium (NAIC) . Rome Air Development

  4. Modeling level change in Lake Urmia using hybrid artificial intelligence approaches

    Science.gov (United States)

    Esbati, M.; Ahmadieh Khanesar, M.; Shahzadi, Ali

    2017-06-01

    The investigation of water level fluctuations in lakes for protecting them regarding the importance of these water complexes in national and regional scales has found a special place among countries in recent years. The importance of the prediction of water level balance in Lake Urmia is necessary due to several-meter fluctuations in the last decade which help the prevention from possible future losses. For this purpose, in this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the lake water level balance has been studied. In addition, for the training of the adaptive neuro-fuzzy inference system, particle swarm optimization (PSO) and hybrid backpropagation-recursive least square method algorithm have been used. Moreover, a hybrid method based on particle swarm optimization and recursive least square (PSO-RLS) training algorithm for the training of ANFIS structure is introduced. In order to have a more fare comparison, hybrid particle swarm optimization and gradient descent are also applied. The models have been trained, tested, and validated based on lake level data between 1991 and 2014. For performance evaluation, a comparison is made between these methods. Numerical results obtained show that the proposed methods with a reasonable error have a good performance in water level balance prediction. It is also clear that with continuing the current trend, Lake Urmia will experience more drop in the water level balance in the upcoming years.

  5. Hybrid Scenario Development Methodology and Tool: An Arctic-Oriented Scenario Example

    Science.gov (United States)

    2011-07-01

    Monitoring; Aid to Law Enforcement Authorities ( ALEA ); Environmental Response; Non-combatant Evacuation Operations (NEO) & Disaster Relief; Sea...Approach Doctrine & impact on type of expeditionary Military Mission: Surveillance & Monitoring ALEA Environmental Incident Response SAR (inc CSAR...symbols/abbreviations/acronyms/initialisms ALEA Aid to Law Enforcement Authorities C4ISTAR Command, Control, Communications, Computers, Intelligence

  6. Characterization of the emissions impacts of hybrid excavators with a portable emissions measurement system (PEMS)-based methodology.

    Science.gov (United States)

    Cao, Tanfeng; Russell, Robert L; Durbin, Thomas D; Cocker, David R; Burnette, Andrew; Calavita, Joseph; Maldonado, Hector; Johnson, Kent C

    2018-04-13

    Hybrid engine technology is a potentially important strategy for reduction of tailpipe greenhouse gas (GHG) emissions and other pollutants that is now being implemented for off-road construction equipment. The goal of this study was to evaluate the emissions and fuel consumption impacts of electric-hybrid excavators using a Portable Emissions Measurement System (PEMS)-based methodology. In this study, three hybrid and four conventional excavators were studied for both real world activity patterns and tailpipe emissions. Activity data was obtained using engine control module (ECM) and global positioning system (GPS) logged data, coupled with interviews, historical records, and video. This activity data was used to develop a test cycle with seven modes representing different types of excavator work. Emissions data were collected over this test cycle using a PEMS. The results indicated the HB215 hybrid excavator provided a significant reduction in tailpipe carbon dioxide (CO 2 ) emissions (from -13 to -26%), but increased diesel particulate matter (PM) (+26 to +27%) when compared to a similar model conventional excavator over the same duty cycle. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

    Science.gov (United States)

    Moore, Gwendolyn B.; And Others

    The report describes three advanced technologies--robotics, artificial intelligence, and computer simulation--and identifies the ways in which they might contribute to special education. A hybrid methodology was employed to identify existing technology and forecast future needs. Following this framework, each of the technologies is defined,…

  8. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  9. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  10. A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

    Directory of Open Access Journals (Sweden)

    P. Amudha

    2015-01-01

    Full Text Available Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC with Enhanced Particle Swarm Optimization (EPSO to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup’99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.

  11. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Science.gov (United States)

    Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

  12. 3Es System Optimization under Uncertainty Using Hybrid Intelligent Algorithm: A Fuzzy Chance-Constrained Programming Model

    Directory of Open Access Journals (Sweden)

    Jiekun Song

    2016-01-01

    Full Text Available Harmonious development of 3Es (economy-energy-environment system is the key to realize regional sustainable development. The structure and components of 3Es system are analyzed. Based on the analysis of causality diagram, GDP and industrial structure are selected as the target parameters of economy subsystem, energy consumption intensity is selected as the target parameter of energy subsystem, and the emissions of COD, ammonia nitrogen, SO2, and NOX and CO2 emission intensity are selected as the target parameters of environment system. Fixed assets investment of three industries, total energy consumption, and investment in environmental pollution control are selected as the decision variables. By regarding the parameters of 3Es system optimization as fuzzy numbers, a fuzzy chance-constrained goal programming (FCCGP model is constructed, and a hybrid intelligent algorithm including fuzzy simulation and genetic algorithm is proposed for solving it. The results of empirical analysis on Shandong province of China show that the FCCGP model can reflect the inherent relationship and evolution law of 3Es system and provide the effective decision-making support for 3Es system optimization.

  13. A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals.

    Science.gov (United States)

    Castañón-Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo

    2015-12-02

    The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi-Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

  14. A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

    Directory of Open Access Journals (Sweden)

    Manuel Castañón–Puga

    2015-12-01

    Full Text Available The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs. This approach takes advantage of wireless local area networks (WLANs over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

  15. Power quality control of an autonomous wind-diesel power system based on hybrid intelligent controller.

    Science.gov (United States)

    Ko, Hee-Sang; Lee, Kwang Y; Kang, Min-Jae; Kim, Ho-Chan

    2008-12-01

    Wind power generation is gaining popularity as the power industry in the world is moving toward more liberalized trade of energy along with public concerns of more environmentally friendly mode of electricity generation. The weakness of wind power generation is its dependence on nature-the power output varies in quite a wide range due to the change of wind speed, which is difficult to model and predict. The excess fluctuation of power output and voltages can influence negatively the quality of electricity in the distribution system connected to the wind power generation plant. In this paper, the authors propose an intelligent adaptive system to control the output of a wind power generation plant to maintain the quality of electricity in the distribution system. The target wind generator is a cost-effective induction generator, while the plant is equipped with a small capacity energy storage based on conventional batteries, heater load for co-generation and braking, and a voltage smoothing device such as a static Var compensator (SVC). Fuzzy logic controller provides a flexible controller covering a wide range of energy/voltage compensation. A neural network inverse model is designed to provide compensating control amount for a system. The system can be optimized to cope with the fluctuating market-based electricity price conditions to lower the cost of electricity consumption or to maximize the power sales opportunities from the wind generation plant.

  16. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    Siddique, Nazmul

    2014-01-01

    Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...

  17. HYBRID HUMAN-ARTIFICIAL INTELLIGENCE APPROACH FOR PAVEMENT DISTRESS ASSESSMENT (PICUCHA

    Directory of Open Access Journals (Sweden)

    Reus Salini

    2017-07-01

    Full Text Available The pavement surface condition assessment is a critical component for a proper pavement management system as well as for pavement rehabilitation design. A number of devices were developed to automatically record surface distresses in a continuous survey mode, but the software required for automatic distress identification remains a big challenge. In this study, a new method named PICture Unsupervised Classification with Human Analysis (PICUCHA is proposed to circumvent many of the limitations of existing approaches, based on a combination of human and artificial intelligence. It was designed from scratch to be capable to identify sealed and unsealed cracks, potholes, patches, different types of pavements and others. The self-learning algorithms do not use any distresses predefinition and can process images taken by cameras with different brands, technologies and resolution. This study describes some key aspects of the new method and provides examples in which PICUCHA was tested in real conditions showing accuracy up to 96.9% in image pattern detection and classification.

  18. Prodiag--a hybrid artificial intelligence based reactor diagnostic system for process faults

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E.; Applequist, C. A.; Chasensky, T.M.

    1996-01-01

    Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL) are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA), project to perform feasibility studies on a novel approach to Artificial Intelligence (Al) based diagnostics for component faults in nuclear power plants. Investigations are being performed in the construction of a first-principles physics-based plant level process diagnostic expert system (ES) and the identification of component-level fault patterns through operating component characteristics using artificial neural networks (ANNs). The purpose of the proof-of-concept project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use thermal hydraulic (T-H) signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance.To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. A full-scope operator training simulator representing the Commonwealth Edison Braidwood nuclear power plant is being used both as the source of development data and as the means to evaluate the advantages of the proposed diagnostic system. This is an ongoing multi-year project and this paper presents the results to date of the CRADA phase

  19. Didactical suggestion for a Dynamic Hybrid Intelligent e-Learning Environment (DHILE) applying the PENTHA ID Model

    Science.gov (United States)

    dall'Acqua, Luisa

    2011-08-01

    The teleology of our research is to propose a solution to the request of "innovative, creative teaching", proposing a methodology to educate creative Students in a society characterized by multiple reference points and hyper dynamic knowledge, continuously subject to reviews and discussions. We apply a multi-prospective Instructional Design Model (PENTHA ID Model), defined and developed by our research group, which adopts a hybrid pedagogical approach, consisting of elements of didactical connectivism intertwined with aspects of social constructivism and enactivism. The contribution proposes an e-course structure and approach, applying the theoretical design principles of the above mentioned ID Model, describing methods, techniques, technologies and assessment criteria for the definition of lesson modes in an e-course.

  20. A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

    Science.gov (United States)

    Yang, Wei; Hall, Trevor J.

    2013-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

  1. Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

    Science.gov (United States)

    Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

    1996-01-01

    The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the

  2. Bandwidth based methodology for designing a hybrid energy storage system for a series hybrid electric vehicle with limited all electric mode

    Science.gov (United States)

    Shahverdi, Masood

    The cost and fuel economy of hybrid electrical vehicles (HEVs) are significantly dependent on the power-train energy storage system (ESS). A series HEV with a minimal all-electric mode (AEM) permits minimizing the size and cost of the ESS. This manuscript, pursuing the minimal size tactic, introduces a bandwidth based methodology for designing an efficient ESS. First, for a mid-size reference vehicle, a parametric study is carried out over various minimal-size ESSs, both hybrid (HESS) and non-hybrid (ESS), for finding the highest fuel economy. The results show that a specific type of high power battery with 4.5 kWh capacity can be selected as the winning candidate to study for further minimization. In a second study, following the twin goals of maximizing Fuel Economy (FE) and improving consumer acceptance, a sports car class Series-HEV (SHEV) was considered as a potential application which requires even more ESS minimization. The challenge with this vehicle is to reduce the ESS size compared to 4.5 kWh, because the available space allocation is only one fourth of the allowed battery size in the mid-size study by volume. Therefore, an advanced bandwidth-based controller is developed that allows a hybridized Subaru BRZ model to be realized with a light ESS. The result allows a SHEV to be realized with 1.13 kWh ESS capacity. In a third study, the objective is to find optimum SHEV designs with minimal AEM assumption which cover the design space between the fuel economies in the mid-size car study and the sports car study. Maximizing FE while minimizing ESS cost is more aligned with customer acceptance in the current state of market. The techniques applied to manage the power flow between energy sources of the power-train significantly affect the results of this optimization. A Pareto Frontier, including ESS cost and FE, for a SHEV with limited AEM, is introduced using an advanced bandwidth-based control strategy teamed up with duty ratio control. This controller

  3. Analysis methodology for flow-level evaluation of a hybrid mobile-sensor network

    NARCIS (Netherlands)

    Dimitrova, D.C.; Heijenk, Geert; Braun, T.

    2012-01-01

    Our society uses a large diversity of co-existing wired and wireless networks in order to satisfy its communication needs. A cooper- ation between these networks can benefit performance, service availabil- ity and deployment ease, and leads to the emergence of hybrid networks. This position paper

  4. Numerical methodologies for investigation of moderate-velocity flow using a hybrid computational fluid dynamics - molecular dynamics simulation approach

    International Nuclear Information System (INIS)

    Ko, Soon Heum; Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel; Jha, Shantenu

    2014-01-01

    Numerical approaches are presented to minimize the statistical errors inherently present due to finite sampling and the presence of thermal fluctuations in the molecular region of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) flow solution. Near the fluid-solid interface the hybrid CFD-MD simulation approach provides a more accurate solution, especially in the presence of significant molecular-level phenomena, than the traditional continuum-based simulation techniques. It also involves less computational cost than the pure particle-based MD. Despite these advantages the hybrid CFD-MD methodology has been applied mostly in flow studies at high velocities, mainly because of the higher statistical errors associated with low velocities. As an alternative to the costly increase of the size of the MD region to decrease statistical errors, we investigate a few numerical approaches that reduce sampling noise of the solution at moderate-velocities. These methods are based on sampling of multiple simulation replicas and linear regression of multiple spatial/temporal samples. We discuss the advantages and disadvantages of each technique in the perspective of solution accuracy and computational cost.

  5. Demonstrating Hybrid Heat Transport and Energy Conversion System Performance Characterization Using Intelligent Control Systems

    International Nuclear Information System (INIS)

    Ostrum, Lee; Manic, Milos

    2017-01-01

    The debate continues on the magnitude and validity of climate change caused by human activities. However, there is no debate about the need to make buildings, modes of transportation, factories, and homes as energy efficient as possible. Given that climate change could occur with the wasteful use of fossil fuel and the fact that fossil energy costs could and will swing wildly, it is imperative that every effort be made to utilize energy sources to their fullest. Hybrid energy systems (HES) are two or more separate energy producers used together to produce energy commodities. The HES this report focuses on is the use of nuclear reactor waste heat as a source of further energy utilization. Nuclear reactors use a fluid to cool the core and produce the steam needed for the production of electricity. Traditionally this steam, or coolant, is used to convert the energy then cooled elsewhere. The heat is released into the environment without being used further. By adding technologies to nuclear reactors to use the wasted heat, a system can be developed to make more than just electricity and allow for loading following capabilities.

  6. Demonstrating Hybrid Heat Transport and Energy Conversion System Performance Characterization Using Intelligent Control Systems

    Energy Technology Data Exchange (ETDEWEB)

    Ostrum, Lee [Univ. of Idaho and Idaho Falls Center, Idaho Falls, ID (United States); Manic, Milos [Virginia Commonwealth Univ., Richmond, VA (United States)

    2017-09-28

    The debate continues on the magnitude and validity of climate change caused by human activities. However, there is no debate about the need to make buildings, modes of transportation, factories, and homes as energy efficient as possible. Given that climate change could occur with the wasteful use of fossil fuel and the fact that fossil energy costs could and will swing wildly, it is imperative that every effort be made to utilize energy sources to their fullest. Hybrid energy systems (HES) are two or more separate energy producers used together to produce energy commodities. The HES this report focuses on is the use of nuclear reactor waste heat as a source of further energy utilization. Nuclear reactors use a fluid to cool the core and produce the steam needed for the production of electricity. Traditionally this steam, or coolant, is used to convert the energy then cooled elsewhere. The heat is released into the environment without being used further. By adding technologies to nuclear reactors to use the wasted heat, a system can be developed to make more than just electricity and allow for loading following capabilities.

  7. GIS-based site selection methodology for hybrid renewable energy systems: A case study from western Turkey

    International Nuclear Information System (INIS)

    Aydin, Nazli Yonca; Kentel, Elcin; Sebnem Duzgun, H.

    2013-01-01

    Highlights: ► We proposed a site selection methodology for renewable energy systems. ► Fuzzy logic and geographic information system tools are used. ► Alternative locations are evaluated in terms of economic and environmental criteria. - Abstract: Renewable energy sources are presently being considered as alternatives to fossil fuels, because they are perpetual, environmentally friendly, and release negligible amounts of greenhouse gases to the atmosphere while producing energy. A disadvantage of renewable energy systems, however, is that continuous energy generation is not possible by using only one type of renewable energy system, since renewable energy resources depend on climate and weather conditions. Two or more renewable energy systems can be integrated into a hybrid system to overcome this problem so that when one resource is not available, the other can continue producing energy. Another disadvantage of renewable energy sources is that they are not available at every geographic location. Their use is mostly advantageous at remote locations that often are of high ecological value. Thus, identification of preferable locations for renewable energy systems is a decision-making problem that requires evaluation of the potential of the resource together with economic and environmental limitations. This paper introduces a methodology for site selection of hybrid wind solar–PV renewable energy systems. First, environmental acceptability and economic feasibility objectives are identified through a comprehensive review of the literature, current Turkish laws and legislations, and interviews with the General Directorate of Electrical Power Resources Survey and Development Administration of Turkey. Second, viable locations in terms of environmental acceptability and economic feasibility are determined through a fuzzy decision-making procedure that uses ordered weighted averaging algorithm for aggregating multiple objectives. Then, priority sites are identified

  8. A fast hybrid methodology based on machine learning, quantum methods, and experimental measurements for evaluating material properties

    Science.gov (United States)

    Kong, Chang Sun; Haverty, Michael; Simka, Harsono; Shankar, Sadasivan; Rajan, Krishna

    2017-09-01

    We present a hybrid approach based on both machine learning and targeted ab-initio calculations to determine adhesion energies between dissimilar materials. The goals of this approach are to complement experimental and/or all ab-initio computational efforts, to identify promising materials rapidly and identify in a quantitative manner the relative contributions of the different material attributes affecting adhesion. Applications of the methodology to predict bulk modulus, yield strength, adhesion and wetting properties of copper (Cu) with other materials including metals, nitrides and oxides is discussed in this paper. In the machine learning component of this methodology, the parameters that were chosen can be roughly divided into four types: atomic and crystalline parameters (which are related to specific elements such as electronegativities, electron densities in Wigner-Seitz cells); bulk material properties (e.g. melting point), mechanical properties (e.g. modulus) and those representing atomic characteristics in ab-initio formalisms (e.g. pseudopotentials). The atomic parameters are defined over one dataset to determine property correlation with published experimental data. We then develop a semi-empirical model across multiple datasets to predict adhesion in material interfaces outside the original datasets. Since adhesion is between two materials, we appropriately use parameters which indicate differences between the elements that comprise the materials. These semi-empirical predictions agree reasonably with the trend in chemical work of adhesion predicted using ab-initio techniques and are used for fast materials screening. For the screened candidates, the ab-initio modeling component provides fundamental understanding of the chemical interactions at the interface, and explains the wetting thermodynamics of thin Cu layers on various substrates. Comparison against ultra-high vacuum (UHV) experiments for well-characterized Cu/Ta and Cu/α-Al2O3 interfaces is

  9. Application of Meta-Heuristic Hybrid Artificial Intelligence Techniques for Modeling of Bonding Strength of Plywood Panels

    Directory of Open Access Journals (Sweden)

    Cenk Demirkır

    2014-04-01

    Full Text Available Plywood, which is one of the most important wood based panels, has many usage areas changing from traffic signs to building constructions in many countries. It is known that the high quality plywood panel manufacturing has been achieved with a good bonding under the optimum pressure conditions depending on adhesive type. This is a study of determining the using possibilities of modern meta-heuristic hybrid artificial intelligence techniques such as IKE and AANN methods for prediction of bonding strength of plywood panels. This study has composed of two main parts as experimental and analytical. Scots pine, maritime pine and European black pine logs were used as wood species. The pine veneers peeled at 32°C and 50°C were dried at 110°C, 140°C and 160°C temperatures. Phenol formaldehyde and melamine urea formaldehyde resins were used as adhesive types. EN 314-1 standard was used to determine the bonding shear strength values of plywood panels in experimental part of this study. Then the intuitive k-nearest neighbor estimator (IKE and adaptive artificial neural network (AANN were used to estimate bonding strength of plywood panels. The best estimation performance was obtained from MA metric for k-value=10. The most effective factor on bonding strength was determined as adhesive type. Error rates were determined less than 5% for both of the IKE and AANN. It may be recommended that proposed methods could be used in applying to estimation of bonding strength values of plywood panels.

  10. A hybrid flight control for a simulated raptor-30 v2 helicopter

    International Nuclear Information System (INIS)

    Khizer, A.N.

    2015-01-01

    This paper presents a hybrid flight control system for a single rotor simulated Raptor-30 V2 helicopter. Hybrid intelligent control system, combination of the conventional and intelligent control methodologies, is applied to small model helicopter. The proposed hybrid control used PID as a traditional control and fuzzy as an intelligent control so as to take the maximum advantage of advanced control theory. The helicopter model used; comes from X-Plane flight simulator and their hybrid flight control system was simulated using MATLAB/SIMULINK in a simulation platform. X-Plane is also used to visualize the performance of this proposed autopilot design. Through a series of numerous experiments, the operation of hybrid control system was investigated. Results verified that the proposed hybrid control has an excellent performance at hovering flight mode. (author)

  11. Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

    Science.gov (United States)

    Asaithambi, Sasikumar; Rajappa, Muthaiah

    2018-05-01

    In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

  12. Mixed oxidizer hybrid propulsion system optimization under uncertainty using applied response surface methodology and Monte Carlo simulation

    Science.gov (United States)

    Whitehead, James Joshua

    The analysis documented herein provides an integrated approach for the conduct of optimization under uncertainty (OUU) using Monte Carlo Simulation (MCS) techniques coupled with response surface-based methods for characterization of mixture-dependent variables. This novel methodology provides an innovative means of conducting optimization studies under uncertainty in propulsion system design. Analytic inputs are based upon empirical regression rate information obtained from design of experiments (DOE) mixture studies utilizing a mixed oxidizer hybrid rocket concept. Hybrid fuel regression rate was selected as the target response variable for optimization under uncertainty, with maximization of regression rate chosen as the driving objective. Characteristic operational conditions and propellant mixture compositions from experimental efforts conducted during previous foundational work were combined with elemental uncertainty estimates as input variables. Response surfaces for mixture-dependent variables and their associated uncertainty levels were developed using quadratic response equations incorporating single and two-factor interactions. These analysis inputs, response surface equations and associated uncertainty contributions were applied to a probabilistic MCS to develop dispersed regression rates as a function of operational and mixture input conditions within design space. Illustrative case scenarios were developed and assessed using this analytic approach including fully and partially constrained operational condition sets over all of design mixture space. In addition, optimization sets were performed across an operationally representative region in operational space and across all investigated mixture combinations. These scenarios were selected as representative examples relevant to propulsion system optimization, particularly for hybrid and solid rocket platforms. Ternary diagrams, including contour and surface plots, were developed and utilized to aid in

  13. Prioritization of renewable energy sources for Turkey by using a hybrid MCDM methodology

    International Nuclear Information System (INIS)

    Kabak, Mehmet; Dağdeviren, Metin

    2014-01-01

    Highlights: • The paper proposes a hybrid model to prioritize RE sources for Turkey. • The hybrid model based on BOCR and ANP is proposed under linguistic values. • Strategic criteria are economy, security, wellbeing, technology and global effects. • Nineteen criteria are used to evaluate hydro, geothermal, solar, wind and biomass. - Abstract: Developing countries such as Turkey, with their fast growing population and economy, are facing an increasing demand for energy. Turkey does not possess a sufficient quantity of domestic oil and natural gas resources to support this growing demand. On the other hand, the country does have abundant reserves of renewable energy that can be a major component in providing part of the overall energy supply. The country plans to explore its renewable energy (RE) sources and increase the renewable energy share in near future. With this in mind, this paper proposes a hybrid model based on BOCR (Benefits, Opportunities, Costs and Risks) and ANP (Analytic Network Process) to determine Turkey’s energy status and prioritize alternative RE sources. BOCR analysis provides a strategic analysis and detailed overview of the country’s energy issues. ANP is a practical multi criteria decision making (MCDM) method and offers the advantages of decision making models, based on tangible and intangible factors. 19 criteria are used to evaluate five alternative RE sources (Hydro, Geothermal, Solar, Wind and Biomass). The subsequent results show that the most important strategic criterion is economy; other criteria include security, human wellbeing, technology and global effects. Their weights are 0.485, 0.235, 0.130, 0.097 and 0.053, respectively. In the conclusion of this paper, the authors propose hydro power as the optimal RE source for the country

  14. A systematic framework for effective uncertainty assessment of severe accident calculations; Hybrid qualitative and quantitative methodology

    International Nuclear Information System (INIS)

    Hoseyni, Seyed Mohsen; Pourgol-Mohammad, Mohammad; Tehranifard, Ali Abbaspour; Yousefpour, Faramarz

    2014-01-01

    This paper describes a systematic framework for characterizing important phenomena and quantifying the degree of contribution of each parameter to the output in severe accident uncertainty assessment. The proposed methodology comprises qualitative as well as quantitative phases. The qualitative part so called Modified PIRT, being a robust process of PIRT for more precise quantification of uncertainties, is a two step process for identifying and ranking based on uncertainty importance in severe accident phenomena. In this process identified severe accident phenomena are ranked according to their effect on the figure of merit and their level of knowledge. Analytical Hierarchical Process (AHP) serves here as a systematic approach for severe accident phenomena ranking. Formal uncertainty importance technique is used to estimate the degree of credibility of the severe accident model(s) used to represent the important phenomena. The methodology uses subjective justification by evaluating available information and data from experiments, and code predictions for this step. The quantitative part utilizes uncertainty importance measures for the quantification of the effect of each input parameter to the output uncertainty. A response surface fitting approach is proposed for estimating associated uncertainties with less calculation cost. The quantitative results are used to plan in reducing epistemic uncertainty in the output variable(s). The application of the proposed methodology is demonstrated for the ACRR MP-2 severe accident test facility. - Highlights: • A two stage framework for severe accident uncertainty analysis is proposed. • Modified PIRT qualitatively identifies and ranks uncertainty sources more precisely. • Uncertainty importance measure quantitatively calculates effect of each uncertainty source. • Methodology is applied successfully on ACRR MP-2 severe accident test facility

  15. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    Directory of Open Access Journals (Sweden)

    Yongcheng Li

    Full Text Available Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

  16. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    Science.gov (United States)

    Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

  17. Intelligence analysis – the royal discipline of Competitive Intelligence

    OpenAIRE

    František Bartes

    2011-01-01

    The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in busines...

  18. METHODOLOGY OF THE HYBRID PROPULSION SYSTEM (DMP & DEP FOR TRIMARAN TYPE FAST PATROL BOAT

    Directory of Open Access Journals (Sweden)

    Aulia Widyandari

    2012-04-01

    Full Text Available There are lot of research done to develop a patrol boat, from the modification of hull model until propulsion system equipment. For example the model ship type AMV (Advanced Marine Vehicle was developed starting from the Catamaran, Trimaran and  Pentamaran model. Everything is aimed at obtaining the ship design that has the speed and stability. In addition to achieving high-speed vessel must be equipped with propulsion (Main Power is great, that means the main engine dimensions, auxiliary equipments and fuel tanks is too large. Many Limitations of space on the ship's engine room trimaran vessel is the main obstacle in designing propulsion system. Beside that Patrol boat should have many missions speed, so propulsion system should be designed at that conditions.   Hybrid propulsion is a combination of Diesel Mechanical Propulsion (DMP with Diesel Electric Propulsion (DEP. DMP system is connected directly to the propeller shaft (or through a reduction-gear. DMP has provide more efficiency rate of 95%. While DEP is only able to provide efficiency by 85% - 89% is slightly lower than DMP, but the DEP offers many advantages such as simplicity and suitability in the rotational speed settings, control systems, engine power production Redundancy, Flexibility in the design of equipments layout in engine rooms, noise, vibration and fuel consumption efficiency which affects the lower pollution.   Design of Hybrid Propulsion system can be satisfied and achieved the Power requirements and optimally at all speed condition of patrol boat. Therefore the author made using modeling Maxsurf-11.12 software and carried out various optimization of the choice of main engine, propeller and system conditions for fast patrol boat cruise. 

  19. Hybrid methodology for risk assessment due to uranium in drinking water

    International Nuclear Information System (INIS)

    Pandey, M.; Kumar, Brij; Datta, D.

    2015-01-01

    Uranium is found in ground and surface waters due to its natural occurrence in geological formations. One microgram (μg) of natural uranium has an activity of 0.67 pCi. The average uranium concentrations in surface, ground, and domestic water are 1, 3, and 2 pCi/l respectively. The uranium intake from water is about equal to the total from other dietary components. Although radioactivity of natural uranium is low, and is not likely to cause cancer, yet chances of cancer resulting from an exposure to a radioactive material like uranium cannot be completely ruled out. Numerous studies have reported Sarcomas (disease) in rats injected with metallic uranium in the femoral marrow and in the chest wall. This paper proposes a hybrid method for combining probability and possibility distributions in the estimation of cancer induction risk. The method is first explained, and then applied to estimate the human cancer risk due to Uranium in drinking water (taken from 15 villages of Kullu district of Himachal Pradesh). The hybrid method is a simple answer, from an intuitive viewpoint, to the problem of combining variability and partial ignorance in the estimation of risk. It simply combines random Monte Carlo sampling with fuzzy calculus. For the proposition 'Probability that Excess risk is lower than 3 x 10 -6 per year', the study obtained a probability comprised between 0.945 (Belief value) and 1 (Plausibility value). The proposed risk level i.e. 3 x 10 -6 per year is considered negligible by major toxicological agencies in the field such as EPA, WHO etc. The belief of 94.5 is the minimum credible probability level for the above proposition and suggests that the risk level is definitely minimal. (author)

  20. Designing with computational intelligence

    CERN Document Server

    Lopes, Heitor; Mourelle, Luiza

    2017-01-01

    This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

  1. A novel methodology for non-linear system identification of battery cells used in non-road hybrid electric vehicles

    Science.gov (United States)

    Unger, Johannes; Hametner, Christoph; Jakubek, Stefan; Quasthoff, Marcus

    2014-12-01

    An accurate state of charge (SoC) estimation of a traction battery in hybrid electric non-road vehicles, which possess higher dynamics and power densities than on-road vehicles, requires a precise battery cell terminal voltage model. This paper presents a novel methodology for non-linear system identification of battery cells to obtain precise battery models. The methodology comprises the architecture of local model networks (LMN) and optimal model based design of experiments (DoE). Three main novelties are proposed: 1) Optimal model based DoE, which aims to high dynamically excite the battery cells at load ranges frequently used in operation. 2) The integration of corresponding inputs in the LMN to regard the non-linearities SoC, relaxation, hysteresis as well as temperature effects. 3) Enhancements to the local linear model tree (LOLIMOT) construction algorithm, to achieve a physical appropriate interpretation of the LMN. The framework is applicable for different battery cell chemistries and different temperatures, and is real time capable, which is shown on an industrial PC. The accuracy of the obtained non-linear battery model is demonstrated on cells with different chemistries and temperatures. The results show significant improvement due to optimal experiment design and integration of the battery non-linearities within the LMN structure.

  2. Modelling the Interaction Levels in HCI Using an Intelligent Hybrid System with Interactive Agents: A Case Study of an Interactive Museum Exhibition Module in Mexico

    Directory of Open Access Journals (Sweden)

    Ricardo Rosales

    2018-03-01

    Full Text Available Technology has become a necessity in our everyday lives and essential for completing activities we typically take for granted; technologies can assist us by completing set tasks or achieving desired goals with optimal affect and in the most efficient way, thereby improving our interactive experiences. This paper presents research that explores the representation of user interaction levels using an intelligent hybrid system approach with agents. We evaluate interaction levels of Human-Computer Interaction (HCI with the aim of enhancing user experiences. We consider the description of interaction levels using an intelligent hybrid system to provide a decision-making system to an agent that evaluates interaction levels when using interactive modules of a museum exhibition. The agents represent a high-level abstraction of the system, where communication takes place between the user, the exhibition and the environment. In this paper, we provide a means to measure the interaction levels and natural behaviour of users, based on museum user-exhibition interaction. We consider that, by analysing user interaction in a museum, we can help to design better ways to interact with exhibition modules according to the properties and behaviour of the users. An interaction-evaluator agent is proposed to achieve the most suitable representation of the interaction levels with the aim of improving user interactions to offer the most appropriate directions, services, content and information, thereby improving the quality of interaction experienced between the user-agent and exhibition-agent.

  3. Optimization of hybrid laser - TIG welding of 316LN steel using response surface methodology (RSM)

    Science.gov (United States)

    Ragavendran, M.; Chandrasekhar, N.; Ravikumar, R.; Saxena, Rajesh; Vasudevan, M.; Bhaduri, A. K.

    2017-07-01

    In the present study, the hybrid laser - TIG welding parameters for welding of 316LN austenitic stainless steel have been investigated by combining a pulsed laser beam with a TIG welding heat source at the weld pool. Laser power, pulse frequency, pulse duration, TIG current were presumed as the welding process parameters whereas weld bead width, weld cross-sectional area and depth of penetration (DOP) were considered as the process responses. Central composite design was used to complete the design matrix and welding experiments were conducted based on the design matrix. Weld bead measurements were then carried out to generate the dataset. Multiple regression models correlating the process parameters with the responses have been developed. The accuracy of the models were found to be good. Then, the desirability approach optimization technique was employed for determining the optimum process parameters to obtain the desired weld bead profile. Validation experiments were then carried out from the determined optimum process parameters. There was good agreement between the predicted and measured values.

  4. A Hybrid Methodology for Modeling Risk of Adverse Events in Complex Health-Care Settings.

    Science.gov (United States)

    Kazemi, Reza; Mosleh, Ali; Dierks, Meghan

    2017-03-01

    In spite of increased attention to quality and efforts to provide safe medical care, adverse events (AEs) are still frequent in clinical practice. Reports from various sources indicate that a substantial number of hospitalized patients suffer treatment-caused injuries while in the hospital. While risk cannot be entirely eliminated from health-care activities, an important goal is to develop effective and durable mitigation strategies to render the system "safer." In order to do this, though, we must develop models that comprehensively and realistically characterize the risk. In the health-care domain, this can be extremely challenging due to the wide variability in the way that health-care processes and interventions are executed and also due to the dynamic nature of risk in this particular domain. In this study, we have developed a generic methodology for evaluating dynamic changes in AE risk in acute care hospitals as a function of organizational and nonorganizational factors, using a combination of modeling formalisms. First, a system dynamics (SD) framework is used to demonstrate how organizational-level and policy-level contributions to risk evolve over time, and how policies and decisions may affect the general system-level contribution to AE risk. It also captures the feedback of organizational factors and decisions over time and the nonlinearities in these feedback effects. SD is a popular approach to understanding the behavior of complex social and economic systems. It is a simulation-based, differential equation modeling tool that is widely used in situations where the formal model is complex and an analytical solution is very difficult to obtain. Second, a Bayesian belief network (BBN) framework is used to represent patient-level factors and also physician-level decisions and factors in the management of an individual patient, which contribute to the risk of hospital-acquired AE. BBNs are networks of probabilities that can capture probabilistic relations

  5. Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

    Science.gov (United States)

    Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

  6. A methodological study on organizing an intelligent CAD/CAE system for conceptual design of advanced nuclear reactor system

    International Nuclear Information System (INIS)

    Gofuku, Akio; Yoshikawa, Hidekazu

    1993-01-01

    In order to shorten the time span of design work and enhance both consistency and rationality of design products, the authors are now investigating an intelligent CAD/CAE system to support cooperative works by many specialists by adopting object-oriented approach. In this paper, the cognitive aspect of design activities of specialists in the conceptual design phase of nuclear reactors is discussed. The activities of the specialists in their design analysis process are highly knowledge-based and goal-oriented. The characteristics of the activities are 1) hierarchization of design goal into sub-goals, 2) prioritization of design sub-goals and step-by-step practise of design analysis, and 3) abstraction of real-world space structure into more simplified space structure to cope with theoretical treatment. Based on these consideration, a conceptual design model of specialists' activities composed of attribute modeling and design expertise knowledge base is proposed. The 'principle of functional independence' proposed by Sue is applied to bridge between the attribute modeling and design expertise knowledge base. The intelligent CAD/CAE system is now under development by focusing on the conceptual design of a space power reactor core utilizing thermo-ionic fuel elements as direct thermo-to-electric conversion. A program to calculate thermo-hydraulics of reactor core and thermo-ionic power generation has been developed. An interface has been also developed in order to communicate with the specialists at JAERI by E-mail concerning the interactive calculation between our calculation and the neutronics calculation of reactor core. (orig.)

  7. A methodological study on organizing an intelligent CAD/CAE system for conceptual design of advanced nuclear reactor system

    Energy Technology Data Exchange (ETDEWEB)

    Gofuku, Akio (Inst. of Atomic Energy, Kyoto Univ. (Japan)); Yoshikawa, Hidekazu (Inst. of Atomic Energy, Kyoto Univ. (Japan))

    1993-04-01

    In order to shorten the time span of design work and enhance both consistency and rationality of design products, the authors are now investigating an intelligent CAD/CAE system to support cooperative works by many specialists by adopting object-oriented approach. In this paper, the cognitive aspect of design activities of specialists in the conceptual design phase of nuclear reactors is discussed. The activities of the specialists in their design analysis process are highly knowledge-based and goal-oriented. The characteristics of the activities are 1) hierarchization of design goal into sub-goals, 2) prioritization of design sub-goals and step-by-step practise of design analysis, and 3) abstraction of real-world space structure into more simplified space structure to cope with theoretical treatment. Based on these consideration, a conceptual design model of specialists' activities composed of attribute modeling and design expertise knowledge base is proposed. The 'principle of functional independence' proposed by Sue is applied to bridge between the attribute modeling and design expertise knowledge base. The intelligent CAD/CAE system is now under development by focusing on the conceptual design of a space power reactor core utilizing thermo-ionic fuel elements as direct thermo-to-electric conversion. A program to calculate thermo-hydraulics of reactor core and thermo-ionic power generation has been developed. An interface has been also developed in order to communicate with the specialists at JAERI by E-mail concerning the interactive calculation between our calculation and the neutronics calculation of reactor core. (orig.)

  8. Assessing the quantified impact of a hybrid POGIL methodology on student averages in a forensic science survey course

    Science.gov (United States)

    Meeks, Tyna L.

    A causal-comparative/quasi experimental study examined the effect of incorporating a hybrid teaching methodology that blended lecture with Process Oriented Guided Inquiry Lessons (POGILs) on the overall academic achievement of a diverse student body in a large lecture setting. Additional considerations included student gender, ethnicity, declared major (STEM or non-STEM), and SAT scores. An evaluation of the effect that these characteristics had on student achievement due to differentiating import placed on the use of POGILs as a learning tool was included. This study used data obtained from a longitudinal examination of eight years of student data from an introductory forensic science survey course offered in a R1 northeastern university. This study addressed the effectiveness of applying a proscribed active learning methodology, one proposed effective in collegiate education, to a new environment, forensic science. The methodology employed combined fourteen POGILs, created specifically for the chosen course, with didactic lecture during the entire semester of a forensic science survey course. This quasi-experimental design used the manipulation of the independent variable, the use of a hybrid lecture instead of exclusive use of traditional didactic lectures, on the students' academic achievement on exams given during the course. Participants in this study (N=1436) were undergraduate students enrolled in the single semester introductory science course. A longitudinal study that incorporated eight years of data was completed, 4 years pre-intervention (2007-2010) and 4 years post-intervention (2011-2014). The forensic science survey course, taught by only one professor during the eight-year period, was a science discipline that had yet to integrate an active learning educational model. Findings indicate four variables significantly contributed to explaining nearly 28% of the variation seen in the student class averages earned during the eight-year period: the

  9. Intelligent System for Diagnosis of a Three-Phase Separator

    Directory of Open Access Journals (Sweden)

    Irina Ioniţă

    2016-03-01

    Full Text Available Intelligent systems for diagnosis have been used in a variety of domains: financial evaluation, credit scoring problem, identification of software and hardware problems of mechanical and electronic equipment, medical diagnosis, fault detection in gas-oil production plants etc. The goal of diagnosis systems is to classify the observed symptoms as being caused by some diagnosis class while advising systems perform such a classification and offer corrective remedies (recommendations. The current paper discuss the opportunity to combine more intelligent techniques and methodologies (intelligent agents, data mining and expert systems to increase the accuracy of results obtained from the diagnosis of a three-phase separator. The results indicate that the diagnosis hybrid system benefits from the advantages of each module component: intelligent agent module, data mining module and expert system module.

  10. Pap Smear Diagnosis Using a Hybrid Intelligent Scheme Focusing on Genetic Algorithm Based Feature Selection and Nearest Neighbor Classification

    DEFF Research Database (Denmark)

    Marinakis, Yannis; Dounias, Georgios; Jantzen, Jan

    2009-01-01

    The term pap-smear refers to samples of human cells stained by the so-called Papanicolaou method. The purpose of the Papanicolaou method is to diagnose pre-cancerous cell changes before they progress to invasive carcinoma. In this paper a metaheuristic algorithm is proposed in order to classify t...... other previously applied intelligent approaches....

  11. Structure and weights optimisation of a modified Elman network emotion classifier using hybrid computational intelligence algorithms: a comparative study

    Science.gov (United States)

    Sheikhan, Mansour; Abbasnezhad Arabi, Mahdi; Gharavian, Davood

    2015-10-01

    Artificial neural networks are efficient models in pattern recognition applications, but their performance is dependent on employing suitable structure and connection weights. This study used a hybrid method for obtaining the optimal weight set and architecture of a recurrent neural emotion classifier based on gravitational search algorithm (GSA) and its binary version (BGSA), respectively. By considering the features of speech signal that were related to prosody, voice quality, and spectrum, a rich feature set was constructed. To select more efficient features, a fast feature selection method was employed. The performance of the proposed hybrid GSA-BGSA method was compared with similar hybrid methods based on particle swarm optimisation (PSO) algorithm and its binary version, PSO and discrete firefly algorithm, and hybrid of error back-propagation and genetic algorithm that were used for optimisation. Experimental tests on Berlin emotional database demonstrated the superior performance of the proposed method using a lighter network structure.

  12. A novel optimized hybrid fuzzy logic intelligent PID controller for an interconnected multi-area power system with physical constraints and boiler dynamics.

    Science.gov (United States)

    Gomaa Haroun, A H; Li, Yin-Ya

    2017-11-01

    In the fast developing world nowadays, load frequency control (LFC) is considered to be a most significant role for providing the power supply with good quality in the power system. To deliver a reliable power, LFC system requires highly competent and intelligent control technique. Hence, in this article, a novel hybrid fuzzy logic intelligent proportional-integral-derivative (FLiPID) controller has been proposed for LFC of interconnected multi-area power systems. A four-area interconnected thermal power system incorporated with physical constraints and boiler dynamics is considered and the adjustable parameters of the FLiPID controller are optimized using particle swarm optimization (PSO) scheme employing an integral square error (ISE) criterion. The proposed method has been established to enhance the power system performances as well as to reduce the oscillations of uncertainties due to variations in the system parameters and load perturbations. The supremacy of the suggested method is demonstrated by comparing the simulation results with some recently reported heuristic methods such as fuzzy logic proportional-integral (FLPI) and intelligent proportional-integral-derivative (PID) controllers for the same electrical power system. the investigations showed that the FLiPID controller provides a better dynamic performance and outperform compared to the other approaches in terms of the settling time, and minimum undershoots of the frequency as well as tie-line power flow deviations following a perturbation, in addition to perform appropriate settlement of integral absolute error (IAE). Finally, the sensitivity analysis of the plant is inspected by varying the system parameters and operating load conditions from their nominal values. It is observed that the suggested controller based optimization algorithm is robust and perform satisfactorily with the variations in operating load condition, system parameters and load pattern. Copyright © 2017 ISA. Published by

  13. I2S-LWR Activation Analysis of Heat Exchangers Using Hybrid Shielding Methodology with SCALE6.1

    International Nuclear Information System (INIS)

    Matijevic, M.; Pevec, D.; Jecmenica, R.

    2016-01-01

    The Integral Inherently Safe Light Water Reactor (I2S-LWR) concept developed by Georgia Tech is a novel PWR reactor delivering electric power of 1000 MWe while implementing inherent safety features typical for Generation III+ small modular reactors. The main safety feature is based on integral primary circuit configuration, bringing together compact design of the reactor core with 121 fuel assembly (FA), control rod drive mechanism (CRDM), 8 primary heat exchangers (PHE), 4 passive decay heat removal systems (DHRS), 8 pumps, and other integral components. A high power density core based on silicide fuel is selected to achieve a high thermal power which is extracted with PHEs placed in the annual region between the barrel and the vessel. The complex and integrated design of I2S-LWR leads to activation of integral components, mainly made from stainless steel, so accurate and precise Monte Carlo (MC) simulations are needed to quantify potential dose rates to personnel during routine maintenance operation. This shielding problem is therefore very challenging one, posing a non-trivial neutron flux solution in a phase space. This paper presents the performance of the hybrid shielding methodologies CADIS/FW-CADIS implemented in the MAVRIC sequence of the SCALE6.1 code package. The main objective was to develop a detailed MC shielding model of the I2S-LWR reactor along with effective variance reduction (VR) parameters and to calculate neutron fluence rates inside PHEs. Such results are then utilized to find neutron activation rate distribution via 60Co generation inside of a stack of microchannel heat exchangers (MCHX), which will be periodically withdrawn for the maintenance. 59Co impurities are the main cause of (n,gamma) radiative gamma dose to personnel via neutron activation since 60Co has half-life of 5.27 years and is emitting high energy gamma rays (1.17 MeV and 1.33 MeV). The developed MC model was successfully used to find converged fluxes inside all 8 stacks of

  14. Identification of key factors in consumers' adoption behavior of intelligent medical terminals based on a hybrid modified MADM model for product improvement.

    Science.gov (United States)

    Liu, Yupeng; Chen, Yifei; Tzeng, Gwo-Hshiung

    2017-09-01

    As a new application technology of the Internet of Things (IoT), intelligent medical treatment has attracted the attention of both nations and industries through its promotion of medical informatisation, modernisation, and intelligentisation. Faced with a wide variety of intelligent medical terminals, consumers may be affected by various factors when making purchase decisions. To examine and evaluate the key influential factors (and their interrelationships) of consumer adoption behavior for improving and promoting intelligent medical terminals toward achieving set aspiration level in each dimension and criterion. A hybrid modified Multiple Attribute Decision-Making (MADM) model was used for this study, based on three components: (1) the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique, to build an influential network relationship map (INRM) at both 'dimensions' and 'criteria' levels; (2) the DEMATEL-based analytic network process (DANP) method, to determine the interrelationships and influential weights among the criteria and identify the source-influential factors; and (3) the modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, to evaluate and improve for reducing the performance gaps to meet the consumers' needs for continuous improvement and sustainable products-development. First, a consensus on the influential factors affecting consumers' adoption of intelligent medical terminals was collected from experts' opinion in practical experience. Next, the interrelationships and influential weights of DANP among dimensions/criteria based on the DEMATEL technique were determined. Finally, two intelligent medicine bottles (AdhereTech, A 1 alternative; and Audio/Visual Alerting Pillbox, A 2 alternative) were reviewed as the terminal devices to verify the accuracy of the MADM model and evaluate its performance on each criterion for improving the total certification gaps by systematics according to the modified VIKOR method

  15. 'CosmoCult Card Game': A Methodological Tool to Understand the Hybrid and Peripheral Cultural Consumption of Young People

    Directory of Open Access Journals (Sweden)

    Wilson Roberto Bekesas

    2018-04-01

    Full Text Available This article discusses the authors’ use of a specially designed card game as part of the survey ‘Youth Cosmopolitanisms in Brazil’, a constituent part of the international project ‘Cultures Juveniles à l’ère de la globalization’, developed in France. As part of the challenges encountered in the process of applying this project in a hybrid and post-colonial context, such as that of Brazil, we experienced different manifestations of what Angela Prysthon (2002 has called ‘peripheral cosmopolitanism’. We propose to present the experiences that resulted as contributory material for research on the cultural consumption of young people in such contexts, and to discuss the value of this research tool as a way to reach and understand spontaneous cultural references, within the subjects’ own conceptions, without the bias that a Western-centered perspective might introduce. Concerning the card game as a research tool, it seems that only recently, and still modestly, have games been thought of in a broader sense of learning and research (Girard, Ecalle & Magnan, 2012; Calvillo Gámez et al., 2011. This moves us to consider the potential that it has for our and others’ research that seeks a methodological tool that reduces cultural biases and borders. Among the examples from the 12- to 24-year-old research subjects, the narratives display their relationships with global and local elements, such as the use of a Brazilian song, ‘Atoladinha’, or Harry Potter characters, used to solve situations proposed in the game.

  16. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  17. A hybrid fuzzy-ontology based intelligent system to determine level of severity and treatment recommendation for Benign Prostatic Hyperplasia.

    Science.gov (United States)

    Torshizi, Abolfazl Doostparast; Zarandi, Mohammad Hossein Fazel; Torshizi, Ghazaleh Doostparast; Eghbali, Kamyar

    2014-01-01

    This paper deals with application of fuzzy intelligent systems in diagnosing severity level and recommending appropriate therapies for patients having Benign Prostatic Hyperplasia. Such an intelligent system can have remarkable impacts on correct diagnosis of the disease and reducing risk of mortality. This system captures various factors from the patients using two modules. The first module determines severity level of the Benign Prostatic Hyperplasia and the second module, which is a decision making unit, obtains output of the first module accompanied by some external knowledge and makes an appropriate treatment decision based on its ontology model and a fuzzy type-1 system. In order to validate efficiency and accuracy of the developed system, a case study is conducted by 44 participants. Then the results are compared with the recommendations of a panel of experts on the experimental data. Then precision and accuracy of the results were investigated based on a statistical analysis. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  18. Integration of plug-in hybrid cars for the encouragement of intelligent power distribution structures; Integration von Plug-in-Hybrid Cars zur Foerderung intelligenter Verteilnetzstrukturen. Vorstudie

    Energy Technology Data Exchange (ETDEWEB)

    Horbaty, R.; Rigassi, R.

    2007-11-15

    This preliminary study for the Swiss Federal Office of Energy (SFOE) takes a look at how plug-in hybrid cars could be used to support the electricity supply in Switzerland. This study explains to what extent hybrid cars would be in a position to provide the services needed to regulate the Swiss electricity mains. Core elements of the concept known as 'Vehicle to Grid' (V2G) are presented. The requirements placed on the cars' equipment, including reversible battery chargers and communication equipment, are reviewed. Mains regulation systems are discussed, as are battery storage and the potential advantages offered by such a system. Challenges and hindrances to implementation are examined and initial feasibility studies are analysed. Questions still to be addressed are noted. A comprehensive appendix rounds off the report.

  19. The impact of intelligence on memory and executive functions of children with temporal lobe epilepsy: Methodological concerns with clinical relevance.

    Science.gov (United States)

    Rzezak, Patricia; Guimarães, Catarina A; Guerreiro, Marilisa M; Valente, Kette D

    2017-05-01

    Patients with TLE are prone to have lower IQ scores than healthy controls. Nevertheless, the impact of IQ differences is not usually considered in studies that compared the cognitive functioning of children with and without epilepsy. This study aimed to determine the effect of using IQ as a covariate on memory and attentional/executive functions of children with TLE. Thirty-eight children and adolescents with TLE and 28 healthy controls paired as to age, gender, and sociodemographic factors were evaluated with a comprehensive neuropsychological battery for memory and executive functions. The authors conducted three analyses to verify the impact of IQ scores on the other cognitive domains. First, we compared performance on cognitive tests without controlling for IQ differences between groups. Second, we performed the same analyses, but we included IQ as a confounding factor. Finally, we evaluated the predictive value of IQ on cognitive functioning. Although patients had IQ score in the normal range, they showed lower IQ scores than controls (p = 0.001). When we did not consider IQ in the analyses, patients had worse performance in verbal and visual memory (short and long-term), semantic memory, sustained, divided and selective attention, mental flexibility and mental tracking for semantic information. By using IQ as a covariate, patients showed worse performance only in verbal memory (long-term), semantic memory, sustained and divided attention and in mental flexibility. IQ was a predictor factor of verbal and visual memory (immediate and delayed), working memory, mental flexibility and mental tracking for semantic information. Intelligence level had a significant impact on memory and executive functioning of children and adolescents with TLE without intellectual disability. This finding opens the discussion of whether IQ scores should be considered when interpreting the results of differences in cognitive performance of patients with epilepsy compared to healthy

  20. Intelligent wear mode identification system for marine diesel engines based on multi-level belief rule base methodology

    Science.gov (United States)

    Yan, Xinping; Xu, Xiaojian; Sheng, Chenxing; Yuan, Chengqing; Li, Zhixiong

    2018-01-01

    Wear faults are among the chief causes of main-engine damage, significantly influencing the secure and economical operation of ships. It is difficult for engineers to utilize multi-source information to identify wear modes, so an intelligent wear mode identification model needs to be developed to assist engineers in diagnosing wear faults in diesel engines. For this purpose, a multi-level belief rule base (BBRB) system is proposed in this paper. The BBRB system consists of two-level belief rule bases, and the 2D and 3D characteristics of wear particles are used as antecedent attributes on each level. Quantitative and qualitative wear information with uncertainties can be processed simultaneously by the BBRB system. In order to enhance the efficiency of the BBRB, the silhouette value is adopted to determine referential points and the fuzzy c-means clustering algorithm is used to transform input wear information into belief degrees. In addition, the initial parameters of the BBRB system are constructed on the basis of expert-domain knowledge and then optimized by the genetic algorithm to ensure the robustness of the system. To verify the validity of the BBRB system, experimental data acquired from real-world diesel engines are analyzed. Five-fold cross-validation is conducted on the experimental data and the BBRB is compared with the other four models in the cross-validation. In addition, a verification dataset containing different wear particles is used to highlight the effectiveness of the BBRB system in wear mode identification. The verification results demonstrate that the proposed BBRB is effective and efficient for wear mode identification with better performance and stability than competing systems.

  1. Artificial intelligence methodologies applied to quality control of the positioning services offered by the Red Andaluza de Posicionamiento (RAP network

    Directory of Open Access Journals (Sweden)

    Antonio José Gil

    2012-12-01

    Full Text Available On April 26, 2012, Elena Giménez de Ory defend-ed her Ph.D. thesis at University of Jaén, entitled: “Robust methodologies applied to quality control of the positioning services offered by the Red Andaluza de Posicionamiento (RAP network”. Elena Giménez de Ory defended her dissertation in a publicly open presentation held in the Higher Polytechnic School at the University of Jaén, and was able to comment on every question raised by her thesis committee and the audience. The thesis was supervised by her advisor, Prof. Antonio J. Gil Cruz, and the rest of his thesis committee, Prof. Manuel Sánchez de la Orden, Dr. Antonio Miguel Ruiz Armenteros and Dr. Gracia Rodríguez Caderot. The thesis has been read and approved by his thesis committee, receiving the highest rating. All of them were present at the presentation.

  2. Hybrid Predictive Control for Dynamic Transport Problems

    CERN Document Server

    Núñez, Alfredo A; Cortés, Cristián E

    2013-01-01

    Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

  3. Health Data Entanglement and artificial intelligence-based analysis: a brand new methodology to improve the effectiveness of healthcare services.

    Science.gov (United States)

    Capone, A; Cicchetti, A; Mennini, F S; Marcellusi, A; Baio, G; Favato, G

    2016-01-01

    Healthcare expenses will be the most relevant policy issue for most governments in the EU and in the USA. This expenditure can be associated with two major key categories: demographic and economic drivers. Factors driving healthcare expenditure were rarely recognised, measured and comprehended. An improvement of health data generation and analysis is mandatory, and in order to tackle healthcare spending growth, it may be useful to design and implement an effective, advanced system to generate and analyse these data. A methodological approach relied upon the Health Data Entanglement (HDE) can be a suitable option. By definition, in the HDE a large amount of data sets having several sources are functionally interconnected and computed through learning machines that generate patterns of highly probable future health conditions of a population. Entanglement concept is borrowed from quantum physics and means that multiple particles (information) are linked together in a way such that the measurement of one particle's quantum state (individual health conditions and related economic requirements) determines the possible quantum states of other particles (population health forecasts to predict their impact). The value created by the HDE is based on the combined evaluation of clinical, economic and social effects generated by health interventions. To predict the future health conditions of a population, analyses of data are performed using self-learning AI, in which sequential decisions are based on Bayesian algorithmic probabilities. HDE and AI-based analysis can be adopted to improve the effectiveness of the health governance system in ways that also lead to better quality of care.

  4. Powertrain Matching and Optimization of Dual-Motor Hybrid Driving System for Electric Vehicle Based on Quantum Genetic Intelligent Algorithm

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2014-01-01

    Full Text Available In order to increase the driving range and improve the overall performance of all-electric vehicles, a new dual-motor hybrid driving system with two power sources was proposed. This system achieved torque-speed coupling between the two power sources and greatly improved the high performance working range of the motors; at the same time, continuously variable transmission (CVT was achieved to efficiently increase the driving range. The power system parameters were determined using the “global optimization method”; thus, the vehicle’s dynamics and economy were used as the optimization indexes. Based on preliminary matches, quantum genetic algorithm was introduced to optimize the matching in the dual-motor hybrid power system. Backward simulation was performed on the combined simulation platform of Matlab/Simulink and AVL-Cruise to optimize, simulate, and verify the system parameters of the transmission system. Results showed that quantum genetic algorithms exhibited good global optimization capability and convergence in dealing with multiobjective and multiparameter optimization. The dual-motor hybrid-driving system for electric cars satisfied the dynamic performance and economy requirements of design, efficiently increasing the driving range of the car, having high performance, and reducing energy consumption of 15.6% compared with the conventional electric vehicle with single-speed reducers.

  5. A New Hybrid Model Based on Data Preprocessing and an Intelligent Optimization Algorithm for Electrical Power System Forecasting

    Directory of Open Access Journals (Sweden)

    Ping Jiang

    2015-01-01

    Full Text Available The establishment of electrical power system cannot only benefit the reasonable distribution and management in energy resources, but also satisfy the increasing demand for electricity. The electrical power system construction is often a pivotal part in the national and regional economic development plan. This paper constructs a hybrid model, known as the E-MFA-BP model, that can forecast indices in the electrical power system, including wind speed, electrical load, and electricity price. Firstly, the ensemble empirical mode decomposition can be applied to eliminate the noise of original time series data. After data preprocessing, the back propagation neural network model is applied to carry out the forecasting. Owing to the instability of its structure, the modified firefly algorithm is employed to optimize the weight and threshold values of back propagation to obtain a hybrid model with higher forecasting quality. Three experiments are carried out to verify the effectiveness of the model. Through comparison with other traditional well-known forecasting models, and models optimized by other optimization algorithms, the experimental results demonstrate that the hybrid model has the best forecasting performance.

  6. A systematic approach of bottom-up assessment methodology for an optimal design of hybrid solar/wind energy resources – Case study at middle east region

    International Nuclear Information System (INIS)

    Ifaei, Pouya; Karbassi, Abdolreza; Jacome, Gabriel; Yoo, ChangKyoo

    2017-01-01

    Highlights: • Proposing DaSOSaCa flowchart as a novel hybrid solar/wind assessment approach. • Calculating four key parameters to generate synthetic wind hourly data for Iran. • Proposing technical and economic hybrid solar/wind GIS maps of Iran. • Revising renewable energies management plans of Iran by macroeconomic evaluation. - Abstract: In the current study, an algorithm-based data processing, sizing, optimization, sensitivity analysis and clustering approach (DaSOSaCa) is proposed as an efficient simultaneous solar/wind assessment methodology. Accordingly, data processing is performed to obtain reliable high quality meteorological data among various datasets, which are used for hybrid photovoltaic/wind turbine/storage/converter system optimal design for consequent sites in a large region. The optimal hybrid systems are consequently simulated to meet hourly power demand in various sites. The solar/wind fraction and net present cost of the systems are then used as the technical and economic clustering variables, respectively. The clustering results are finally used as input to obtain novel hybrid solar/wind GIS maps. Iran is selected as the case study to validate the proposed methodology and detail its applicability. Ten minute annual global horizontal radiation, wind speed, and temperature data are analyzed, and the optimal, robust hybrid systems are simulated for various sites in order to classify the country. The generated GIS maps show that Iran can be efficiently clustered into four technical and five economic clusters under optimal conditions. The clustering results prove that Iran is mainly a solar country with approximately 74% solar power fraction under optimum conditions. A macroeconomic evaluation using DaSOSaCa also reveals that the nominal discount rate is recommended to be greater than 20% considering the current economic situation for the renewable energy sector in Iran. An environmental analysis results show that an average 106.68 tonCO 2

  7. Intelligent optimization to integrate a plug-in hybrid electric vehicle smart parking lot with renewable energy resources and enhance grid characteristics

    International Nuclear Information System (INIS)

    Fazelpour, Farivar; Vafaeipour, Majid; Rahbari, Omid; Rosen, Marc A.

    2014-01-01

    Highlights: • The proposed algorithms handled design steps of an efficient parking lot of PHEVs. • Optimizations are performed with 1 h intervals to find optimum charging rates. • Multi-objective optimization is performed to find the optimum size and site of DG. • Optimal sizing of a PV–wind–diesel HRES is attained. • Charging rates are optimized intelligently during peak and off-peak times. - Abstract: Widespread application of plug-in hybrid electric vehicles (PHEVs) as an important part of smart grids requires drivers and power grid constraints to be satisfied simultaneously. We address these two challenges with the presence of renewable energy and charging rate optimization in the current paper. First optimal sizing and siting for installation of a distributed generation (DG) system is performed through the grid considering power loss minimization and voltage enhancement. Due to its benefits, the obtained optimum site is considered as the optimum location for constructing a movie theater complex equipped with a PHEV parking lot. To satisfy the obtained size of DG, an on-grid hybrid renewable energy system (HRES) is chosen. In the next set of optimizations, optimal sizing of the HRES is performed to minimize the energy cost and to find the best number of decision variables, which are the number of the system’s components. Eventually, considering demand uncertainties due to the unpredictability of the arrival and departure times of the vehicles, time-dependent charging rate optimizations of the PHEVs are performed in 1 h intervals for the 24-h of a day. All optimization problems are performed using genetic algorithms (GAs). The outcome of the proposed optimization sets can be considered as design steps of an efficient grid-friendly parking lot of PHEVs. The results indicate a reduction in real power losses and improvement in the voltage profile through the distribution line. They also show the competence of the utilized energy delivery method in

  8. Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.

    Science.gov (United States)

    Wang, K W; Deng, C; Li, J P; Zhang, Y Y; Li, X Y; Wu, M C

    2017-04-01

    Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for the prevention and control of TB. This study proposes a hybrid model combining autoregressive integrated moving average (ARIMA) with a nonlinear autoregressive (NAR) neural network for forecasting the incidence of TB from January 2007 to March 2016. Prediction performance was compared between the hybrid model and the ARIMA model. The best-fit hybrid model was combined with an ARIMA (3,1,0) × (0,1,1)12 and NAR neural network with four delays and 12 neurons in the hidden layer. The ARIMA-NAR hybrid model, which exhibited lower mean square error, mean absolute error, and mean absolute percentage error of 0·2209, 0·1373, and 0·0406, respectively, in the modelling performance, could produce more accurate forecasting of TB incidence compared to the ARIMA model. This study shows that developing and applying the ARIMA-NAR hybrid model is an effective method to fit the linear and nonlinear patterns of time-series data, and this model could be helpful in the prevention and control of TB.

  9. A Novel Supercapacitor/Lithium-Ion Hybrid Energy System with a Fuzzy Logic-Controlled Fast Charging and Intelligent Energy Management System

    Directory of Open Access Journals (Sweden)

    Muhammad Adil Khan

    2018-05-01

    Full Text Available The electric powered wheelchair (EPW is an essential assistive tool for people with serious injuries or disability. This manuscript describes the validation of applied research for reducing the charging time of an electric wheelchair using a hybrid electric system (HES composed of a supercapacitor (SC bank and a lithium-ion battery with a fuzzy logic controller (FLC-based fast charging system for Li-ion batteries and a fuzzy logic-based intelligent energy management system (FLIEMS for controlling the power flow within the HES. The fast charging FLC was designed to drive the voltage difference (Vd among the different cells of a multi-cell battery and the cell voltage (Vc of an individual cell. These parameters (voltage difference and cell voltage were used as input voltages to reduce the charge time and activate a bypass equalization (BPE scheme. BPE was introduced in this paper so that the battery operates within the safe voltage range. For SC/Li-ion HES, the FLIEMS presented in this paper controls the bi-directional power flow to smooth the power extracted from Li-ion batteries. Moreover, a dual active bridge isolated bidirectional DC converter (DAB-IBDC was used for power conversion. The DAB-IBDC presented in this paper has the characteristics of galvanic isolation, and high power conversion efficiency compared to the conventional converter circuits due to the reduced reverse power flow and current stresses.

  10. Social intelligence, human intelligence and niche construction.

    Science.gov (United States)

    Sterelny, Kim

    2007-04-29

    This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence-ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.

  11. Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: methodology and preliminary report.

    Science.gov (United States)

    Fu, Jicheng; Jones, Maria; Jan, Yih-Kuen

    2014-01-01

    Wheelchair tilt and recline functions are two of the most desirable features for relieving seating pressure to decrease the risk of pressure ulcers. The effective guidance on wheelchair tilt and recline usage is therefore critical to pressure ulcer prevention. The aim of this study was to demonstrate the feasibility of using machine learning techniques to construct an intelligent model to provide personalized guidance to individuals with spinal cord injury (SCI). The motivation stems from the clinical evidence that the requirements of individuals vary greatly and that no universal guidance on tilt and recline usage could possibly satisfy all individuals with SCI. We explored all aspects involved in constructing the intelligent model and proposed approaches tailored to suit the characteristics of this preliminary study, such as the way of modeling research participants, using machine learning techniques to construct the intelligent model, and evaluating the performance of the intelligent model. We further improved the intelligent model's prediction accuracy by developing a two-phase feature selection algorithm to identify important attributes. Experimental results demonstrated that our approaches held the promise: they could effectively construct the intelligent model, evaluate its performance, and refine the participant model so that the intelligent model's prediction accuracy was significantly improved.

  12. 2015 Chinese Intelligent Automation Conference

    CERN Document Server

    Li, Hongbo

    2015-01-01

    Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.

  13. Using Emotional Intelligence in Personalized Adaptation

    NARCIS (Netherlands)

    Damjanovic, Violeta; Kravcik, Milos

    2007-01-01

    Damjanovic, V. & Kravcik, M. (2007). Using Emotional Intelligence in Personalized Adaptation. In V. Sugumaran (Ed.), Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications (pp. 1716-1742). IGI Publishing.

  14. A robust hybrid model integrating enhanced inputs based extreme learning machine with PLSR (PLSR-EIELM) and its application to intelligent measurement.

    Science.gov (United States)

    He, Yan-Lin; Geng, Zhi-Qiang; Xu, Yuan; Zhu, Qun-Xiong

    2015-09-01

    In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons and the over-fitting phenomenon. First, a traditional extreme learning machine (ELM) is selected. Second, a method of randomly assigning is applied to the weights between the input layer and the hidden layer, and then the nonlinear transformation for independent variables can be obtained from the output of the hidden layer neurons. Especially, the original input variables are regarded as enhanced inputs; then the enhanced inputs and the nonlinear transformed variables are tied together as the whole independent variables. In this way, the PLSR can be carried out to identify the PLS components not only from the nonlinear transformed variables but also from the original input variables, which can remove the correlation among the whole independent variables and the expected outputs. Finally, the optimal relationship model of the whole independent variables with the expected outputs can be achieved by using PLSR. Thus, the PLSR-EIELM model is developed. Then the PLSR-EIELM model served as an intelligent measurement tool for the key variables of the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. The experimental results show that the predictive accuracy of PLSR-EIELM is stable, which indicate that PLSR-EIELM has good robust character. Moreover, compared with ELM, PLSR, hierarchical ELM (HELM), and PLSR-ELM, PLSR-EIELM can achieve much smaller predicted relative errors in these two applications. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

    Science.gov (United States)

    Asoodeh, Mojtaba; Bagheripour, Parisa

    2012-01-01

    Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone.

  16. An open-source framework for analyzing N-electron dynamics. II. Hybrid density functional theory/configuration interaction methodology.

    Science.gov (United States)

    Hermann, Gunter; Pohl, Vincent; Tremblay, Jean Christophe

    2017-10-30

    In this contribution, we extend our framework for analyzing and visualizing correlated many-electron dynamics to non-variational, highly scalable electronic structure method. Specifically, an explicitly time-dependent electronic wave packet is written as a linear combination of N-electron wave functions at the configuration interaction singles (CIS) level, which are obtained from a reference time-dependent density functional theory (TDDFT) calculation. The procedure is implemented in the open-source Python program detCI@ORBKIT, which extends the capabilities of our recently published post-processing toolbox (Hermann et al., J. Comput. Chem. 2016, 37, 1511). From the output of standard quantum chemistry packages using atom-centered Gaussian-type basis functions, the framework exploits the multideterminental structure of the hybrid TDDFT/CIS wave packet to compute fundamental one-electron quantities such as difference electronic densities, transient electronic flux densities, and transition dipole moments. The hybrid scheme is benchmarked against wave function data for the laser-driven state selective excitation in LiH. It is shown that all features of the electron dynamics are in good quantitative agreement with the higher-level method provided a judicious choice of functional is made. Broadband excitation of a medium-sized organic chromophore further demonstrates the scalability of the method. In addition, the time-dependent flux densities unravel the mechanistic details of the simulated charge migration process at a glance. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  17. An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

    Science.gov (United States)

    Deb, Kalyanmoy; Sinha, Ankur

    2010-01-01

    Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

  18. Performance and Feasibility Analysis of a Grid Interactive Large Scale Wind/PV Hybrid System based on Smart Grid Methodology Case Study South Part – Jordan

    Directory of Open Access Journals (Sweden)

    Qais H. Alsafasfeh

    2015-02-01

    Full Text Available Most recent research on renewable energy resources main one goal to make Jordan less dependent on imported energy with locally developed and produced solar power, this paper discussed the efficient system of Wind/ PV Hybrid System to be than main power sources for south part of Jordan, the proposed hybrid system design based on Smart Grid Methodology,  the solar energy will be installed on top roof of  electricity subscribers across the Governorate of Maan, Tafila, Karak and Aqaba and the wind energy will set in one site by this way the capital cost for project will be reduced also the  simulation result show   the feasibility  is a very competitive and feasible cost . Economics analysis of a proposed renewable energy system was made using HOMER simulation and evaluation was completed with the cost per kilowatt of EDCO company, the net present cost is $2,551,676,416, the cost of energy is 0.07kWhr with a renewable fraction of 86.6 %.

  19. Hybrid response surface methodology-artificial neural network optimization of drying process of banana slices in a forced convective dryer.

    Science.gov (United States)

    Taheri-Garavand, Amin; Karimi, Fatemeh; Karimi, Mahmoud; Lotfi, Valiullah; Khoobbakht, Golmohammad

    2018-06-01

    The aim of the study is to fit models for predicting surfaces using the response surface methodology and the artificial neural network to optimize for obtaining the maximum acceptability using desirability functions methodology in a hot air drying process of banana slices. The drying air temperature, air velocity, and drying time were chosen as independent factors and moisture content, drying rate, energy efficiency, and exergy efficiency were dependent variables or responses in the mentioned drying process. A rotatable central composite design as an adequate method was used to develop models for the responses in the response surface methodology. Moreover, isoresponse contour plots were useful to predict the results by performing only a limited set of experiments. The optimum operating conditions obtained from the artificial neural network models were moisture content 0.14 g/g, drying rate 1.03 g water/g h, energy efficiency 0.61, and exergy efficiency 0.91, when the air temperature, air velocity, and drying time values were equal to -0.42 (74.2 ℃), 1.00 (1.50 m/s), and -0.17 (2.50 h) in the coded units, respectively.

  20. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  1. Compression of Born ratio for fluorescence molecular tomography/x-ray computed tomography hybrid imaging: methodology and in vivo validation.

    Science.gov (United States)

    Mohajerani, Pouyan; Ntziachristos, Vasilis

    2013-07-01

    The 360° rotation geometry of the hybrid fluorescence molecular tomography/x-ray computed tomography modality allows for acquisition of very large datasets, which pose numerical limitations on the reconstruction. We propose a compression method that takes advantage of the correlation of the Born-normalized signal among sources in spatially formed clusters to reduce the size of system model. The proposed method has been validated using an ex vivo study and an in vivo study of a nude mouse with a subcutaneous 4T1 tumor, with and without inclusion of a priori anatomical information. Compression rates of up to two orders of magnitude with minimum distortion of reconstruction have been demonstrated, resulting in large reduction in weight matrix size and reconstruction time.

  2. Intelligent Energy Management for Plug-in Hybrid Electric Vehicles: The Role of ITS Infrastructure in Vehicle Electrification Gestion énergétique intelligente pour véhicules électriques hybrides rechargeables : rôle de l’infrastructure de systèmes de transport intelligents (STI dans l’électrification des véhicules

    Directory of Open Access Journals (Sweden)

    Marano V.

    2012-08-01

    Full Text Available The desire to reduce carbon emissions due to transportation sources has led over the past decade to the development of new propulsion technologies, focused on vehicle electrification (including hybrid, plug-in hybrid and battery electric vehicles. These propulsion technologies, along with advances in telecommunication and computing power, have the potential of making passenger and commercial vehicles more energy efficient and environment friendly. In particular, energy management algorithms are an integral part of plug-in vehicles and are very important for achieving the performance benefits. The optimal performance of energy management algorithms depends strongly on the ability to forecast energy demand from the vehicle. Information available about environment (temperature, humidity, wind, road grade, etc. and traffic (traffic density, traffic lights, etc., is very important in operating a vehicle at optimal efficiency. This article outlines some current technologies that can help achieving this optimum efficiency goal. In addition to information available from telematic and geographical information systems, knowledge of projected vehicle charging demand on the power grid is necessary to build an intelligent energy management controller for future plug-in hybrid and electric vehicles. The impact of charging millions of vehicles from the power grid could be significant, in the form of increased loading of power plants, transmission and distribution lines, emissions and economics (information are given and discussed for the US case. Therefore, this effect should be considered in an intelligent way by controlling/scheduling the charging through a communication based distributed control. Le désir de réduire les émissions de carbone issues des sources de transport a conduit durant la dernière décennie au développement de nouvelles technologies de propulsion, axées sur l’électrification des véhicules (comprenant les véhicules

  3. Intelligent Systems for Aerospace Engineering - An Overview

    National Research Council Canada - National Science Library

    Krishnakumar, K

    2003-01-01

    Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends...

  4. Intelligence analysis – the royal discipline of Competitive Intelligence

    Directory of Open Access Journals (Sweden)

    František Bartes

    2011-01-01

    Full Text Available The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in business practice, is the “forecasting of the future”. That is forecasting about the future, which forms the basis for strategic decisions made by the company’s top management. To implement that requirement in corporate practice, the author perceives Competitive Intelligence as a systemic application discipline. This approach allows him to propose a “Work Plan” for Competitive Intelligence as a fundamental standardized document to steer Competitive Intelligence team activities. The author divides the Competitive Intelligence team work plan into five basic parts. Those parts are derived from the five-stage model of the intelligence cycle, which, in the author’s opinion, is more appropriate for complicated cases of Competitive Intelligence.

  5. A States of Matter Search-Based Approach for Solving the Problem of Intelligent Power Allocation in Plug-in Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Arturo Valdivia-Gonzalez

    2017-01-01

    Full Text Available Recently, many researchers have proved that the electrification of the transport sector is a key for reducing both the emissions of green-house pollutants and the dependence on oil for transportation. As a result, Plug-in Hybrid Electric Vehicles (or PHEVs are receiving never before seen increased attention. Consequently, large-scale penetration of PHEVs into the market is expected to take place in the near future, however, an unattended increase in the PHEVs needs may cause several technical problems which could potentially compromise the stability of power systems. As a result of the growing necessity for addressing such issues, topics related to the optimization of PHEVs’ charging infrastructures have captured the attention of many researchers. Related to this, several state-of-the-art swarm optimization methods (such as the well-known Particle Swarm Optimization (PSO or the recently proposed Gravitational Search Algorithm (GSA approach have been successfully applied in the optimization of the average State of Charge (SoC, which represents one of the most important performance indicators in the context of PHEVs’ intelligent power allocation. Many of these swarm optimization methods, however, are known to be subject to several critical flaws, including premature convergence and a lack of balance between the exploration and exploitation of solutions. Such problems are usually related to the evolutionary operators employed by each of the methods on the exploration and exploitation of new solutions. In this paper, the recently proposed States of Matter Search (SMS swarm optimization method is proposed for maximizing the average State of Charge of PHEVs within a charging station. In our experiments, several different scenarios consisting on different numbers of PHEVs were considered. To test the feasibility of the proposed approach, comparative experiments were performed against other popular PHEVs’ State of Charge maximization approaches

  6. The impact of economic growth on environmental efficiency of the electricity sector: A hybrid window DEA methodology for the USA.

    Science.gov (United States)

    Halkos, George E; Polemis, Michael L

    2018-04-01

    This paper estimates the efficiency of the power generation sector in the USA by using Window Data Envelopment Analysis (W-DEA). We integrate radial and non-radial efficiency measurements in DEA using the hybrid measure while we extend the proposed model by considering good and undesirable outputs as separable and non separable. Then in the second stage, we perform parametric and non-parametric econometric techniques in order to model the relationship between the calculated environmental efficiencies and economic growth in attaining sustainability. Our empirical findings indicate a stable N-shape relationship between environmental efficiency and regional economic growth in the case of global and total pollutants but an inverted N-shape in the case of local pollutants. This implies that attention is required when considering local and global pollutants and the extracted environmental efficiency scores. A clear message to policy makers and government officials is that climate change which calls for economic, environmental and social concern should be analyzed according to its dispersion and regional dimension. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. Hybrid causal methodology and software platform for probabilistic risk assessment and safety monitoring of socio-technical systems

    International Nuclear Information System (INIS)

    Groth, Katrina; Wang Chengdong; Mosleh, Ali

    2010-01-01

    This paper introduces an integrated framework and software platform for probabilistic risk assessment (PRA) and safety monitoring of complex socio-technical systems. An overview of the three-layer hybrid causal logic (HCL) modeling approach and corresponding algorithms, implemented in the Trilith software platform, are provided. The HCL approach enhances typical PRA methods by quantitatively including the influence of soft causal factors introduced by human and organizational aspects of a system. The framework allows different modeling techniques to be used for different aspects of the socio-technical system. The HCL approach combines the power of traditional event sequence diagram (ESD)event tree (ET) and fault tree (FT) techniques for modeling deterministic causal paths, with the flexibility of Bayesian belief networks for modeling non-deterministic cause-effect relationships among system elements (suitable for modeling human and organizational influences). Trilith enables analysts to construct HCL models and perform quantitative risk assessment and management of complex systems. The risk management capabilities included are HCL-based risk importance measures, hazard identification and ranking, precursor analysis, safety indicator monitoring, and root cause analysis. This paper describes the capabilities of the Trilith platform and power of the HCL algorithm by use of example risk models for a type of aviation accident (aircraft taking off from the wrong runway).

  8. Hybrid causal methodology and software platform for probabilistic risk assessment and safety monitoring of socio-technical systems

    Energy Technology Data Exchange (ETDEWEB)

    Groth, Katrina, E-mail: kgroth@umd.ed [Center for Risk and Reliability, 0151 Glenn L. Martin Hall, University of Maryland, College Park, MD 20742 (United States); Wang Chengdong; Mosleh, Ali [Center for Risk and Reliability, 0151 Glenn L. Martin Hall, University of Maryland, College Park, MD 20742 (United States)

    2010-12-15

    This paper introduces an integrated framework and software platform for probabilistic risk assessment (PRA) and safety monitoring of complex socio-technical systems. An overview of the three-layer hybrid causal logic (HCL) modeling approach and corresponding algorithms, implemented in the Trilith software platform, are provided. The HCL approach enhances typical PRA methods by quantitatively including the influence of soft causal factors introduced by human and organizational aspects of a system. The framework allows different modeling techniques to be used for different aspects of the socio-technical system. The HCL approach combines the power of traditional event sequence diagram (ESD)event tree (ET) and fault tree (FT) techniques for modeling deterministic causal paths, with the flexibility of Bayesian belief networks for modeling non-deterministic cause-effect relationships among system elements (suitable for modeling human and organizational influences). Trilith enables analysts to construct HCL models and perform quantitative risk assessment and management of complex systems. The risk management capabilities included are HCL-based risk importance measures, hazard identification and ranking, precursor analysis, safety indicator monitoring, and root cause analysis. This paper describes the capabilities of the Trilith platform and power of the HCL algorithm by use of example risk models for a type of aviation accident (aircraft taking off from the wrong runway).

  9. Business intelligence for insurance companies

    OpenAIRE

    IGNATIUK A.

    2016-01-01

    The current state and future trends for the world and domestic insurance markets are analyzed. The description of business intelligence methodology, tools and their practical implication for insurance companies are provided.

  10. BUSINESS INTELLIGENCE FOR INSURANCE COMPANIES

    Directory of Open Access Journals (Sweden)

    A. Ignatiuk

    2016-06-01

    Full Text Available The current state and future trends for the world and domestic insurance markets are analyzed. The description of business intelligence methodology, tools and their practical implication for insurance companies are provided.

  11. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  12. Intelligent mechatronics; Intelligent mechatronics

    Energy Technology Data Exchange (ETDEWEB)

    Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

    1995-10-01

    Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

  13. Process optimization for microcystin-LR degradation by Response Surface Methodology and mechanism analysis in gas-liquid hybrid discharge system.

    Science.gov (United States)

    Zhang, Yi; Wei, Hanyu; Xin, Qing; Wang, Mingang; Wang, Qi; Wang, Qiang; Cong, Yanqing

    2016-12-01

    A gas-liquid hybrid discharge system was applied to microcystin-LR (MC-LR) degradation. MC-LR degradation was completed after 1 min under a pulsed high voltage of 16 kV, gas-liquid interface gap of 10 mm and oxygen flow rate of 160 L/h. The Box-Behnken Design was proposed in Response Surface Methodology to evaluate the influence of pulsed high voltage, electrode distance and oxygen flow rate on MC-LR removal efficiency. Multiple regression analysis, focused on multivariable factors, was employed and a reduced cubic model was developed. The ANOVA analysis shows that the model is significant and the model prediction on MC-LR removal was also validated with experimental data. The optimum conditions for the process are obtained at pulsed voltage of 16 kV, gas-liquid interface gap of 10 mm and oxygen flow rate of 120 L/h with ta removal efficiency of MC-LR of 96.6%. The addition of catalysts (TiO 2 or Fe 2+ ) in the gas-liquid hybrid discharge system was found to enhance the removal of MC-LR. The intermediates of MC-LR degradation were analyzed by liquid chromatography/mass spectrometry. The degradation pathway proposed envisaged the oxidation of hydroxyl radicals and ozone, and attack of high-energy electrons on the unsaturated double bonds of Adda and Mdha, with MC-LR finally decomposing into small molecular products. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Artificial Intelligence and Moral intelligence

    OpenAIRE

    Laura Pana

    2008-01-01

    We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

  15. Intelligent Systems For Aerospace Engineering: An Overview

    Science.gov (United States)

    KrishnaKumar, K.

    2003-01-01

    Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

  16. Hybrid Arrays for Chemical Sensing

    Science.gov (United States)

    Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

    In recent years, multisensory approaches to environment monitoring for chemical detection as well as other forms of situational awareness have become increasingly popular. A hybrid sensor is a multimodal system that incorporates several sensing elements and thus produces data that are multivariate in nature and may be significantly increased in complexity compared to data provided by single-sensor systems. Though a hybrid sensor is itself an array, hybrid sensors are often organized into more complex sensing systems through an assortment of network topologies. Part of the reason for the shift to hybrid sensors is due to advancements in sensor technology and computational power available for processing larger amounts of data. There is also ample evidence to support the claim that a multivariate analytical approach is generally superior to univariate measurements because it provides additional redundant and complementary information (Hall, D. L.; Linas, J., Eds., Handbook of Multisensor Data Fusion, CRC, Boca Raton, FL, 2001). However, the benefits of a multisensory approach are not automatically achieved. Interpretation of data from hybrid arrays of sensors requires the analyst to develop an application-specific methodology to optimally fuse the disparate sources of data generated by the hybrid array into useful information characterizing the sample or environment being observed. Consequently, multivariate data analysis techniques such as those employed in the field of chemometrics have become more important in analyzing sensor array data. Depending on the nature of the acquired data, a number of chemometric algorithms may prove useful in the analysis and interpretation of data from hybrid sensor arrays. It is important to note, however, that the challenges posed by the analysis of hybrid sensor array data are not unique to the field of chemical sensing. Applications in electrical and process engineering, remote sensing, medicine, and of course, artificial

  17. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

    Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Ap

  18. Artificial intelligence in nanotechnology.

    Science.gov (United States)

    Sacha, G M; Varona, P

    2013-11-15

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  19. Artificial intelligence in nanotechnology

    Science.gov (United States)

    Sacha, G. M.; Varona, P.

    2013-11-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  20. Artificial intelligence in nanotechnology

    International Nuclear Information System (INIS)

    Sacha, G M; Varona, P

    2013-01-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines. (topical review)

  1. 2013 Chinese Intelligent Automation Conference

    CERN Document Server

    Deng, Zhidong

    2013-01-01

    Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation.   Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

  2. 2013 Chinese Intelligent Automation Conference

    CERN Document Server

    Deng, Zhidong

    2013-01-01

    Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation. Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

  3. Hybrid cognitive engine for radio systems adaptation

    KAUST Repository

    Alqerm, Ismail

    2017-07-20

    Network efficiency and proper utilization of its resources are essential requirements to operate wireless networks in an optimal fashion. Cognitive radio aims to fulfill these requirements by exploiting artificial intelligence techniques to create an entity called cognitive engine. Cognitive engine exploits awareness about the surrounding radio environment to optimize the use of radio resources and adapt relevant transmission parameters. In this paper, we propose a hybrid cognitive engine that employs Case Based Reasoning (CBR) and Decision Trees (DTs) to perform radio adaptation in multi-carriers wireless networks. The engine complexity is reduced by employing DTs to improve the indexing methodology used in CBR cases retrieval. The performance of our hybrid engine is validated using software defined radios implementation and simulation in multi-carrier environment. The system throughput, signal to noise and interference ratio, and packet error rate are obtained and compared with other schemes in different scenarios.

  4. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  5. Competitive Intelligence.

    Science.gov (United States)

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

    Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

  6. Artificial intelligence executive summary

    International Nuclear Information System (INIS)

    Wamsley, S.J.; Purvis, E.E. III

    1984-01-01

    Artificial intelligence (AI) is a high technology field that can be used to provide problem solving diagnosis, guidance and for support resolution of problems. It is not a stand alone discipline, but can also be applied to develop data bases for retention of the expertise that is required for its own knowledge base. This provides a way to retain knowledge that otherwise may be lost. Artificial Intelligence Methodology can provide an automated construction management decision support system, thereby restoring the manager's emphasis to project management

  7. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

    As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.

  8. Intelligence Ethics:

    DEFF Research Database (Denmark)

    Rønn, Kira Vrist

    2016-01-01

    Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

  9. Methodology to optimize the cost of deployment of a wind-solar hybrid system; Metodologia para otimizar o custo da implantacao de um sistema hibrido eolico-solar

    Energy Technology Data Exchange (ETDEWEB)

    Nogueira, Jose Wilson Lage [Universidade Federal do Rio Grande Norte (UERN), Natal, RN (Brazil). Dept. de Engenharia Mecanica], e-mail: wilson@ufrnet.br; Rocha, Brismark Goes da [Universidade do Estado do Rio Grande do Norte (UERN), Patu, RN (Brazil). Dept. de Matematica], e-mail: brismarkrocha@uern.br

    2008-07-01

    Purposes the application of a methodology to optimize the implantation cost of an wind-solar hybrid system, to potencies between 2.250 W and 3.750 W. The developed mathematical model was obtained through the Multiple Linear Regression technique, on the basis of the previous knowledge of variables: necessary capacity of storage, total daily energy demand, wind power, module power and module number. These variables are gotten by means of sizing. Parametric statistical: T-student tests had been used to detect the significant difference in the average of total cost to being considered the diameter of the wind. Parametric statistical T-student tests had been used to detect the significant difference in the average of total cost to being considered the diameter of the wind, F-Snedecor in the variance analysis to test if the coefficients of the considered model are significantly different of zero and test not-parametric statistical by Friedman, to verify if there is difference in the total cost, by being considered the photovoltaic module powers. In decision of hypothesis tests was considered a 5%-significant level. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 3 HP. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 5 HP only to wind speed of 4 m/s and 6 m/s in wind of 3 m, 4 m and 5 m of diameter. There was not significant difference in costs to diameters of winds of 3 m and 4 m. A computational program was developed to assist the study of several configurations that optimizes the implantation cost of an wind-solar through considered mathematical model. (author)

  10. Intelligence Naturelle et Intelligence Artificielle

    OpenAIRE

    Dubois, Daniel

    2011-01-01

    Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

  11. Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoothing and Artificial Intelligence Models (ANN, SVM: The Case of Greek Electricity Market

    Directory of Open Access Journals (Sweden)

    George P. Papaioannou

    2016-08-01

    Full Text Available In this work we propose a new hybrid model, a combination of the manifold learning Principal Components (PC technique and the traditional multiple regression (PC-regression, for short and medium-term forecasting of daily, aggregated, day-ahead, electricity system-wide load in the Greek Electricity Market for the period 2004–2014. PC-regression is shown to effectively capture the intraday, intraweek and annual patterns of load. We compare our model with a number of classical statistical approaches (Holt-Winters exponential smoothing of its generalizations Error-Trend-Seasonal, ETS models, the Seasonal Autoregressive Moving Average with exogenous variables, Seasonal Autoregressive Integrated Moving Average with eXogenous (SARIMAX model as well as with the more sophisticated artificial intelligence models, Artificial Neural Networks (ANN and Support Vector Machines (SVM. Using a number of criteria for measuring the quality of the generated in-and out-of-sample forecasts, we have concluded that the forecasts of our hybrid model outperforms the ones generated by the other model, with the SARMAX model being the next best performing approach, giving comparable results. Our approach contributes to studies aimed at providing more accurate and reliable load forecasting, prerequisites for an efficient management of modern power systems.

  12. 2nd International Conference on Intelligent Computing, Communication & Devices

    CERN Document Server

    Popentiu-Vladicescu, Florin

    2017-01-01

    The book presents high quality papers presented at 2nd International Conference on Intelligent Computing, Communication & Devices (ICCD 2016) organized by Interscience Institute of Management and Technology (IIMT), Bhubaneswar, Odisha, India, during 13 and 14 August, 2016. The book covers all dimensions of intelligent sciences in its three tracks, namely, intelligent computing, intelligent communication and intelligent devices. intelligent computing track covers areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. Intelligent communication covers communication and network technologies, including mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. This covers communication hardware, soft...

  13. A business intelligence approach using web search tools and online data reduction techniques to examine the value of product-enabled services

    DEFF Research Database (Denmark)

    Tanev, Stoyan; Liotta, Giacomo; Kleismantas, Andrius

    2015-01-01

    in Canada and Europe. It adopts an innovative methodology based on online textual data that could be implemented in advanced business intelligence tools aiming at the facilitation of innovation, marketing and business decision making. Combinations of keywords referring to different aspects of service value......-service innovation as a competitive advantage on the marketplace. On the other hand, the focus of EU firms on innovative hybrid offerings is not explicitly related to business differentiation and competitiveness....

  14. Intelligent instrumentation principles and applications

    CERN Document Server

    Bhuyan, Manabendra

    2011-01-01

    With the advent of microprocessors and digital-processing technologies as catalyst, classical sensors capable of simple signal conditioning operations have evolved rapidly to take on higher and more specialized functions including validation, compensation, and classification. This new category of sensor expands the scope of incorporating intelligence into instrumentation systems, yet with such rapid changes, there has developed no universal standard for design, definition, or requirement with which to unify intelligent instrumentation. Explaining the underlying design methodologies of intelligent instrumentation, Intelligent Instrumentation: Principles and Applications provides a comprehensive and authoritative resource on the scientific foundations from which to coordinate and advance the field. Employing a textbook-like language, this book translates methodologies to more than 80 numerical examples, and provides applications in 14 case studies for a complete and working understanding of the material. Beginn...

  15. IDM-PhyChm-Ens: intelligent decision-making ensemble methodology for classification of human breast cancer using physicochemical properties of amino acids.

    Science.gov (United States)

    Ali, Safdar; Majid, Abdul; Khan, Asifullah

    2014-04-01

    Development of an accurate and reliable intelligent decision-making method for the construction of cancer diagnosis system is one of the fast growing research areas of health sciences. Such decision-making system can provide adequate information for cancer diagnosis and drug discovery. Descriptors derived from physicochemical properties of protein sequences are very useful for classifying cancerous proteins. Recently, several interesting research studies have been reported on breast cancer classification. To this end, we propose the exploitation of the physicochemical properties of amino acids in protein primary sequences such as hydrophobicity (Hd) and hydrophilicity (Hb) for breast cancer classification. Hd and Hb properties of amino acids, in recent literature, are reported to be quite effective in characterizing the constituent amino acids and are used to study protein foldings, interactions, structures, and sequence-order effects. Especially, using these physicochemical properties, we observed that proline, serine, tyrosine, cysteine, arginine, and asparagine amino acids offer high discrimination between cancerous and healthy proteins. In addition, unlike traditional ensemble classification approaches, the proposed 'IDM-PhyChm-Ens' method was developed by combining the decision spaces of a specific classifier trained on different feature spaces. The different feature spaces used were amino acid composition, split amino acid composition, and pseudo amino acid composition. Consequently, we have exploited different feature spaces using Hd and Hb properties of amino acids to develop an accurate method for classification of cancerous protein sequences. We developed ensemble classifiers using diverse learning algorithms such as random forest (RF), support vector machines (SVM), and K-nearest neighbor (KNN) trained on different feature spaces. We observed that ensemble-RF, in case of cancer classification, performed better than ensemble-SVM and ensemble-KNN. Our

  16. Intellectual technologies in the problems of thermal power engineering control: formalization of fuzzy information processing results using the artificial intelligence methodology

    Science.gov (United States)

    Krokhin, G.; Pestunov, A.

    2017-11-01

    Exploitation conditions of power stations in variable modes and related changes of their technical state actualized problems of creating models for decision-making and state recognition basing on diagnostics using the fuzzy logic for identification their state and managing recovering processes. There is no unified methodological approach for obtaining the relevant information is a case of fuzziness and inhomogeneity of the raw information about the equipment state. The existing methods for extracting knowledge are usually unable to provide the correspondence between of the aggregates model parameters and the actual object state. The switchover of the power engineering from the preventive repair to the one, which is implemented according to the actual technical state, increased the responsibility of those who estimate the volume and the duration of the work. It may lead to inadequacy of the diagnostics and the decision-making models if corresponding methodological preparations do not take fuzziness into account, because the nature of the state information is of this kind. In this paper, we introduce a new model which formalizes the equipment state using not only exact information, but fuzzy as well. This model is more adequate to the actual state, than traditional analogs, and may be used in order to increase the efficiency and the service period of the power installations.

  17. Configurable intelligent optimization algorithm design and practice in manufacturing

    CERN Document Server

    Tao, Fei; Laili, Yuanjun

    2014-01-01

    Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorit

  18. A Proposed Business Intelligent Framework for Recommender Systems

    Directory of Open Access Journals (Sweden)

    Sitalakshmi Venkatraman

    2017-11-01

    Full Text Available In this Internet age, recommender systems (RS have become popular, offering new opportunities and challenges to the business world. With a continuous increase in global competition, e-businesses, information portals, social networks and more, websites are required to become more user-centric and rely on the presence and role of RS in assisting users in better decision making. However, with continuous changes in user interests and consumer behavior patterns that are influenced by easy access to vast information and social factors, raising the quality of recommendations has become a challenge for recommender systems. There is a pressing need for exploring hybrid models of the five main types of RS, namely collaborative, demographic, utility, content and knowledge based approaches along with advancements in Big Data (BD to become more context-aware of the technology and social changes and to behave intelligently. There is a gap in literature with a research focus in this direction. This paper takes a step to address this by exploring a new paradigm of applying business intelligence (BI concepts to RS for intelligently responding to user changes and business complexities. A BI based framework adopting a hybrid methodology for RS is proposed with a focus on enhancing the RS performance. Such a business intelligent recommender system (BIRS can adopt On-line Analytical Processing (OLAP tools and performance monitoring metrics using data mining techniques of BI to enhance its own learning, user profiling and predictive models for making a more useful set of personalised recommendations to its users. The application of the proposed framework to a B2C e-commerce case example is presented.

  19. Cultural intelligence: A research landscape

    DEFF Research Database (Denmark)

    Alon, Ilan; Lankut, Erik; Richter, Nicole Franziska

    Purpose: This study identifies reviews the most influential literature streams to cultural intelligence by a bibliometric citation analysis and provides recommendations for future research. Design/methodology/approach: Three bibliometric citation tools are used to analyse a sample of 357 articles...... by 823 scholars in 199 different journals published between 1992-2017. Findings: The analysis reveals 10 research clusters within the topic of cultural intelligence and anables the identification of future research within and at the intercept of clusters....

  20. Integration of plug-in hybrid cars in the promotion of intelligent distribution networks; Integration von Plug-in-Hybrid Cars zur Foerderung intelligenter Verteilnetzstrukturen (Vorstudie) - Schlussbericht / 2 2008

    Energy Technology Data Exchange (ETDEWEB)

    Horbaty, R.; Rigassi, R.

    2008-08-15

    This final report for the Swiss Federal Office of Energy (SFOE) reviews work done as part of a preliminary study concerning the use of plug-in hybrid cars as part of a system for the regulation of energy in electricity supply grids. The 'Vehicle to Grid' concept is discussed. This involves hybrid vehicles with higher accumulator capacities, reversible charger units as well as appropriate connector technologies and communication systems. This 'smart grid' concept is looked at and the players involved are introduced. The advantages and disadvantages of such a system are discussed.

  1. One-Pot Facile Methodology to Synthesize Chitosan-ZnO-Graphene Oxide Hybrid Composites for Better Dye Adsorption and Antibacterial Activity

    Directory of Open Access Journals (Sweden)

    Anandhavelu Sanmugam

    2017-11-01

    Full Text Available Novel chitosan–ZnO–graphene oxide hybrid composites were prepared using a one-pot chemical strategy, and their dye adsorption characteristics and antibacterial activity were demonstrated. The prepared chitosan and the hybrids such as chitosan–ZnO and chitosan–ZnO–graphene oxide were characterized by UV-Vis absorption spectroscopy, X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, and transmission electron microscopy. The thermal and mechanical properties indicate a significant improvement over chitosan in the hybrid composites. Dye adsorption experiments were carried out using methylene blue and chromium complex as model pollutants with the function of dye concentration. The antibacterial properties of chitosan and the hybrids were tested against Gram-positive and Gram-negative bacterial species, which revealed minimum inhibitory concentrations (MICs of 0.1 µg/mL.

  2. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  3. Intelligent Design

    DEFF Research Database (Denmark)

    Hjorth, Poul G.

    2005-01-01

    Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig.......Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig....

  4. A new methodology for recognizing features in rotational parts using ...

    African Journals Online (AJOL)

    user

    An intelligent interface between CAD and CAPP systems is imperative because the ..... The Feature recognition methodology discussed in this work has several advantages over other ... Applied Artificial Intelligence, Vol.16, No.4, pp.303–331.

  5. International Conference on Computational Intelligence 2015

    CERN Document Server

    Saha, Sujan

    2017-01-01

    This volume comprises the proceedings of the International Conference on Computational Intelligence 2015 (ICCI15). This book aims to bring together work from leading academicians, scientists, researchers and research scholars from across the globe on all aspects of computational intelligence. The work is composed mainly of original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of computational intelligence. Specifically, the major topics covered include classical computational intelligence models and artificial intelligence, neural networks and deep learning, evolutionary swarm and particle algorithms, hybrid systems optimization, constraint programming, human-machine interaction, computational intelligence for the web analytics, robotics, computational neurosciences, neurodynamics, bioinspired and biomorphic algorithms, cross disciplinary topics and applications. The contents of this volume will be of use to researchers and professionals alike....

  6. Leading to Learning and Competitive Intelligence

    Science.gov (United States)

    Luu, Trong Tuan

    2013-01-01

    Purpose: This research aims to examine whether there is the chain effect from corporate social responsibility (CSR) and emotional intelligence (EI) to organizational learning and competitive intelligence in chemical companies in a Vietnam business setting. Design/methodology/approach: Structural equation modeling (SEM) approach was used to analyze…

  7. Intelligent model-based diagnostics for vehicle health management

    Science.gov (United States)

    Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

    2003-08-01

    The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

  8. Intelligent playgrounds

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2009-01-01

    This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

  9. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  10. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  11. Research and Application of a Novel Hybrid Model Based on Data Selection and Artificial Intelligence Algorithm for Short Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Wendong Yang

    2017-01-01

    Full Text Available Machine learning plays a vital role in several modern economic and industrial fields, and selecting an optimized machine learning method to improve time series’ forecasting accuracy is challenging. Advanced machine learning methods, e.g., the support vector regression (SVR model, are widely employed in forecasting fields, but the individual SVR pays no attention to the significance of data selection, signal processing and optimization, which cannot always satisfy the requirements of time series forecasting. By preprocessing and analyzing the original time series, in this paper, a hybrid SVR model is developed, considering periodicity, trend and randomness, and combined with data selection, signal processing and an optimization algorithm for short-term load forecasting. Case studies of electricity power data from New South Wales and Singapore are regarded as exemplifications to estimate the performance of the developed novel model. The experimental results demonstrate that the proposed hybrid method is not only robust but also capable of achieving significant improvement compared with the traditional single models and can be an effective and efficient tool for power load forecasting.

  12. Intelligent Advertising

    OpenAIRE

    Díaz Pinedo, Edilfredo Eliot

    2012-01-01

    Intelligent Advertisement diseña e implementa un sistema de publicidad para dispositivos móviles en un centro comercial, donde los clientes reciben publicidad de forma pasiva en sus dispositivos mientras están dentro.

  13. BUSINESS INTELLIGENCE

    OpenAIRE

    Bogdan Mohor Dumitrita

    2011-01-01

    The purpose of this work is to present business intelligence systems. These systems can be extremely complex and important in modern market competition. Its effectiveness also reflects in price, so we have to exlore their financial potential before investment. The systems have 20 years long history and during that time many of such tools have been developed, but they are rarely still in use. Business intelligence system consists of three main areas: Data Warehouse, ETL tools and tools f...

  14. Intelligent indexing

    International Nuclear Information System (INIS)

    Farkas, J.

    1992-01-01

    In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space ι 2 to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs

  15. Intelligent indexing

    Energy Technology Data Exchange (ETDEWEB)

    Farkas, J

    1993-12-31

    In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space {iota}{sup 2} to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs.

  16. Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS)

    CSIR Research Space (South Africa)

    Xing, B

    2009-12-01

    Full Text Available This work focuses on the design and control of a novel hybrid manufacturing system: Reconfigurable Cellular Manufacturing System (RCMS) by using Artificial Intelligence (AI) approach. It is hybrid as it combines the advantages of Cellular...

  17. Foundations of Intelligent Systems : Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering

    CERN Document Server

    Li, Tianrui

    2012-01-01

    Proceedings of The Sixth International Conference on Intelligent System and Knowledge Engineering presents selected papers from the conference ISKE 2011, held December 15-17 in Shanghai, China. This proceedings doesn’t only examine original research and approaches in the broad areas of intelligent systems and knowledge engineering, but also present new methodologies and practices in intelligent computing paradigms. The book introduces the current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, information retrieval, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, natural-language processing, etc. Furthermore, new computing methodologies are presented, including cloud computing, service computing and pervasive computing with traditional intelligent methods. The proceedings will be beneficial for both researchers and practitioners who want to utilize intelligent methods in their specific resea...

  18. Business Sustainability and Collective Intelligence

    Science.gov (United States)

    Garrido, Paulo

    2009-01-01

    Purpose: The purpose of this paper is to analyze to which point collective intelligence (CI) concepts and ideas, as applied to organizations, can contribute to enlarge the conceptual basis for business sustainability (BS). Design/methodology/approach: The paper is written from an engineer-minded, systemic and cybernetic perspective. It begins by…

  19. Fostering collective intelligence education

    Directory of Open Access Journals (Sweden)

    Jaime Meza

    2016-06-01

    Full Text Available New educational models are necessary to update learning environments to the digitally shared communication and information. Collective intelligence is an emerging field that already has a significant impact in many areas and will have great implications in education, not only from the side of new methodologies but also as a challenge for education. This paper proposes an approach to a collective intelligence model of teaching using Internet to combine two strategies: idea management and real time assessment in the class. A digital tool named Fabricius has been created supporting these two elements to foster the collaboration and engagement of students in the learning process. As a result of the research we propose a list of KPI trying to measure individual and collective performance. We are conscious that this is just a first approach to define which aspects of a class following a course can be qualified and quantified.

  20. Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibilitgy modeling in a high-frequency tropical cyclone area using GIS

    Science.gov (United States)

    Tien Bui, Dieu; Pradhan, Biswajeet; Nampak, Haleh; Bui, Quang-Thanh; Tran, Quynh-An; Nguyen, Quoc-Phi

    2016-09-01

    This paper proposes a new artificial intelligence approach based on neural fuzzy inference system and metaheuristic optimization for flood susceptibility modeling, namely MONF. In the new approach, the neural fuzzy inference system was used to create an initial flood susceptibility model and then the model was optimized using two metaheuristic algorithms, Evolutionary Genetic and Particle Swarm Optimization. A high-frequency tropical cyclone area of the Tuong Duong district in Central Vietnam was used as a case study. First, a GIS database for the study area was constructed. The database that includes 76 historical flood inundated areas and ten flood influencing factors was used to develop and validate the proposed model. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Receiver Operating Characteristic (ROC) curve, and area under the ROC curve (AUC) were used to assess the model performance and its prediction capability. Experimental results showed that the proposed model has high performance on both the training (RMSE = 0.306, MAE = 0.094, AUC = 0.962) and validation dataset (RMSE = 0.362, MAE = 0.130, AUC = 0.911). The usability of the proposed model was evaluated by comparing with those obtained from state-of-the art benchmark soft computing techniques such as J48 Decision Tree, Random Forest, Multi-layer Perceptron Neural Network, Support Vector Machine, and Adaptive Neuro Fuzzy Inference System. The results show that the proposed MONF model outperforms the above benchmark models; we conclude that the MONF model is a new alternative tool that should be used in flood susceptibility mapping. The result in this study is useful for planners and decision makers for sustainable management of flood-prone areas.

  1. 3rd Workshop on "Combinations of Intelligent Methods and Applications"

    CERN Document Server

    Palade, Vasile

    2013-01-01

    The combination of different intelligent methods is a very active research area in Artificial Intelligence (AI). The aim is to create integrated or hybrid methods that benefit from each of their components.  The 3rd Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2012) was intended to become a forum for exchanging experience and ideas among researchers and practitioners who are dealing with combining intelligent methods either based on first principles or in the context of specific applications. CIMA 2012 was held in conjunction with the 22nd European Conference on Artificial Intelligence (ECAI 2012).This volume includes revised versions of the papers presented at CIMA 2012.  .

  2. Indications and Warning Methodology for Strategic Intelligence

    Science.gov (United States)

    2017-12-01

    congestion and flaring tempers while New York City leadership began planning transportation alternatives. The tourism industry would be affected as well...revenue from the tourism industry that would have a ripple effect on the food service industry, among others. The financial district would not be

  3. An Intelligent Clustering Based Methodology for Confusable ...

    African Journals Online (AJOL)

    Journal of the Nigerian Association of Mathematical Physics ... The system assigns patients with severity levels in all the clusters. ... The system compares favorably with diagnosis arrived at by experienced physicians and also provides patients' level of severity in each confusable disease and the degree of confusability of ...

  4. Emergent web intelligence advanced information retrieval

    CERN Document Server

    Badr, Youakim; Abraham, Ajith; Hassanien, Aboul-Ella

    2010-01-01

    Web Intelligence explores the impact of artificial intelligence and advanced information technologies representing the next generation of Web-based systems, services, and environments, and designing hybrid web systems that serve wired and wireless users more efficiently. Multimedia and XML-based data are produced regularly and in increasing way in our daily digital activities, and their retrieval must be explored and studied in this emergent web-based era. 'Emergent Web Intelligence: Advanced information retrieval, provides reviews of the related cutting-edge technologies and insights. It is v

  5. Intelligent systems

    CERN Document Server

    Irwin, J David

    2011-01-01

    Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system

  6. Intelligent Universe

    Energy Technology Data Exchange (ETDEWEB)

    Hoyle, F

    1983-01-01

    The subject is covered in chapters, entitled: chance and the universe (synthesis of proteins; the primordial soup); the gospel according to Darwin (discussion of Darwin theory of evolution); life did not originate on earth (fossils from space; life in space); the interstellar connection (living dust between the stars; bacteria in space falling to the earth; interplanetary dust); evolution by cosmic control (microorganisms; genetics); why aren't the others here (a cosmic origin of life); after the big bang (big bang and steady state); the information rich universe; what is intelligence up to; the intelligent universe.

  7. Artificial intelligence

    International Nuclear Information System (INIS)

    Perret-Galix, D.

    1992-01-01

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  8. Artificial Intelligence and Moral intelligence

    Directory of Open Access Journals (Sweden)

    Laura Pana

    2008-07-01

    Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

  9. Plant intelligence

    Science.gov (United States)

    Lipavská, Helena; Žárský, Viktor

    2009-01-01

    The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094

  10. Speech Intelligibility

    Science.gov (United States)

    Brand, Thomas

    Speech intelligibility (SI) is important for different fields of research, engineering and diagnostics in order to quantify very different phenomena like the quality of recordings, communication and playback devices, the reverberation of auditoria, characteristics of hearing impairment, benefit using hearing aids or combinations of these things.

  11. Methodology for monitoring the behaviour of wind-photovoltaic hybrid system in the conditions of Cuba; Metodologia para el monitoreo del comportamiento de un sistema hibrido eolico-fotovoltaico en las condiciones de Cuba

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez G, Maria; Nunez, Ariel; Marquez M, Soe del C [Centro de Investigaciones de Energia Solar, Santiago de Cuba (Cuba)

    2000-07-01

    The proposal of a methodology is shown in the work that allows monitoring the behaviour of wind-photovoltaic hybrid system beginning with the study of the energy resources (wind and solar) of the known place, designed and put into operation a hybrid installation, using Text Processing techniques could obtained operation curves of the system daily, monthly and annual, to configure the reading for port series of the parameters measured during the evaluation of the system a denominated software HYBSYS was developed in Lab View for Windows 3.1 or superior. [Spanish] Se muestra la propuesta de una metodologia que permite monitorear el comportamiento de un sistema hibrido eolico-fotovoltaico, comenzando con el estudio de los recursos energeticos (eolico y solar) de un sitio conocido se diseno y puso en funcionamiento una instalacion hibrida, usando las tecnicas de un procesador se pudieron obtener las curvas de funcionamiento diaria, mensual y anual del sistema, para configurar la lectura por puerto serie de los parametros medidos durante la evaluacion del sistema se desarrollo un software denominado HYBSYS en Lab View para Windows 3.1 o superior.

  12. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lee-Ing Tong

    2012-02-01

    Full Text Available Solar energy has become an important energy source in recent years as it generates less pollution than other energies. A photovoltaic (PV system, which typically has many components, converts solar energy into electrical energy. With the development of advanced engineering technologies, the transfer efficiency of a PV system has been increased from low to high. The combination of components in a PV system influences its transfer efficiency. Therefore, when predicting the transfer efficiency of a PV system, one must consider the relationship among system components. This work accurately predicts whether transfer efficiency of a PV system is high or low using a novel hybrid model that combines rough set theory (RST, data envelopment analysis (DEA, and genetic programming (GP. Finally, real data-set are utilized to demonstrate the accuracy of the proposed method.

  13. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  14. Soft computing for business intelligence

    CERN Document Server

    Pérez, Rafael; Cobo, Angel; Marx, Jorge; Valdés, Ariel

    2014-01-01

    The book Soft Computing for Business Intelligence is the remarkable output of a program based on the idea of joint trans-disciplinary research as supported by the Eureka Iberoamerica Network and the University of Oldenburg. It contains twenty-seven papers allocated to three sections: Soft Computing, Business Intelligence and Knowledge Discovery, and Knowledge Management and Decision Making. Although the contents touch different domains they are similar in so far as they follow the BI principle “Observation and Analysis” while keeping a practical oriented theoretical eye on sound methodologies, like Fuzzy Logic, Compensatory Fuzzy Logic (CFL), Rough Sets and other softcomputing elements. The book tears down the traditional focus on business, and extends Business Intelligence techniques in an impressive way to a broad range of fields like medicine, environment, wind farming, social collaboration and interaction, car sharing and sustainability.

  15. Intelligent Tutor

    Science.gov (United States)

    1990-01-01

    NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.

  16. Architecture for Business Intelligence in the Healthcare Sector

    Science.gov (United States)

    Lee, Sang Young

    2018-03-01

    Healthcare environment is growing to include not only the traditional information systems, but also a business intelligence platform. For executive leaders, consultants, and analysts, there is no longer a need to spend hours in design and develop of typical reports or charts, the entire solution can be completed through using Business Intelligence software. The current paper highlights the advantages of big data analytics and business intelligence in the healthcare industry. In this paper, In this paper we focus our discussion around intelligent techniques and methodologies which are recently used for business intelligence in healthcare.

  17. Perceived Intelligence Is Associated with Measured Intelligence in Men but Not Women

    Science.gov (United States)

    Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

    2014-01-01

    Background The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. Methodology/Principal Findings We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. Conclusions These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape. PMID:24651120

  18. Intelligent interaction based on holographic personalized portal

    Directory of Open Access Journals (Sweden)

    Yadong Huang

    2017-06-01

    Full Text Available Purpose – The purpose of this paper is to study the architecture of holographic personalized portal, user modeling, commodity modeling and intelligent interaction. Design/methodology/approach – In this paper, the authors propose crowd-science industrial ecological system based on holographic personalized portal and its interaction. The holographic personality portal is based on holographic enterprises, commodities and consumers, and the personalized portal consists of accurate ontology, reliable supply, intelligent demand and smart cyberspace. Findings – The personalized portal can realize the information acquisition, characteristic analysis and holographic presentation. Then, the intelligent interaction, e.g. demand decomposition, personalized search, personalized presentation and demand prediction, will be implemented within the personalized portal. Originality/value – The authors believe that their work on intelligent interaction based on holographic personalized portal, which has been first proposed in this paper, is innovation focusing on the interaction between intelligence and convenience.

  19. Intelligent Design and Intelligent Failure

    Science.gov (United States)

    Jerman, Gregory

    2015-01-01

    Good Evening, my name is Greg Jerman and for nearly a quarter century I have been performing failure analysis on NASA's aerospace hardware. During that time I had the distinct privilege of keeping the Space Shuttle flying for two thirds of its history. I have analyzed a wide variety of failed hardware from simple electrical cables to cryogenic fuel tanks to high temperature turbine blades. During this time I have found that for all the time we spend intelligently designing things, we need to be equally intelligent about understanding why things fail. The NASA Flight Director for Apollo 13, Gene Kranz, is best known for the expression "Failure is not an option." However, NASA history is filled with failures both large and small, so it might be more accurate to say failure is inevitable. It is how we react and learn from our failures that makes the difference.

  20. Intelligent computing for sustainable energy and environment

    Energy Technology Data Exchange (ETDEWEB)

    Li, Kang [Queen' s Univ. Belfast (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Li, Shaoyuan; Li, Dewei [Shanghai Jiao Tong Univ., Shanghai (China). Dept. of Automation; Niu, Qun (eds.) [Shanghai Univ. (China). School of Mechatronic Engineering and Automation

    2013-07-01

    Fast track conference proceedings. State of the art research. Up to date results. This book constitutes the refereed proceedings of the Second International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2012, held in Shanghai, China, in September 2012. The 60 full papers presented were carefully reviewed and selected from numerous submissions and present theories and methodologies as well as the emerging applications of intelligent computing in sustainable energy and environment.

  1. Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling

    Directory of Open Access Journals (Sweden)

    Banjanovic-Mehmedovic Lejla

    2016-01-01

    Full Text Available Accurate prediction of traffic information is important in many applications in relation to Intelligent Transport systems (ITS, since it reduces the uncertainty of future traffic states and improves traffic mobility. There is a lot of research done in the field of traffic information predictions such as speed, flow and travel time. The most important research was done in the domain of cooperative intelligent transport system (C-ITS. The goal of this paper is to introduce the novel cooperation behaviour profile prediction through the example of flexible Road Trains useful road cooperation parameter, which contributes to the improvement of traffic mobility in Intelligent Transportation Systems. This paper presents an approach towards the control and cooperation behaviour modelling of vehicles in the flexible Road Train based on hybrid automaton and neuro-fuzzy (ANFIS prediction of cooperation profile of the flexible Road Train. Hybrid automaton takes into account complex dynamics of each vehicle as well as discrete cooperation approach. The ANFIS is a particular class of the ANN family with attractive estimation and learning potentials. In order to provide statistical analysis, RMSE (root mean square error, coefficient of determination (R2 and Pearson coefficient (r, were utilized. The study results suggest that ANFIS would be an efficient soft computing methodology, which could offer precise predictions of cooperative interactions between vehicles in Road Train, which is useful for prediction mobility in Intelligent Transport systems.

  2. The Predictive Aspect of Business Process Intelligence

    DEFF Research Database (Denmark)

    Pérez, Moisés Lima; Møller, Charles

    2007-01-01

    This paper presents the arguments for a research proposal on predicting business events in a Business Process Intelligence (BPI) context. The paper argues that BPI holds a potential for leveraging enterprise benefits by supporting real-time processes. However, based on the experiences from past...... business intelligence projects the paper argues that it is necessary to establish a new methodology to mine and extract the intelligence on the business level which is different from that, which will improve a business process in an enterprise. In conclusion the paper proposes a new research project aimed...

  3. Intelligent system for accident identification in NPP

    International Nuclear Information System (INIS)

    Hernandez, J.L.

    1998-01-01

    Accidental situations in NPP are great concern for operators, the facility, regulatory bodies and the environmental. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre-operational Probabilistic safety Assessment and the Thermal hydraulic Safety Analysis of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid from the combination of the artificial intelligence techniques fuzzy logic and artificial neural networks. The system works with variables from the process of the first circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

  4. Epistasis analysis using artificial intelligence.

    Science.gov (United States)

    Moore, Jason H; Hill, Doug P

    2015-01-01

    Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

  5. Event Sequence Analysis of the Air Intelligence Agency Information Operations Center Flight Operations

    National Research Council Canada - National Science Library

    Larsen, Glen

    1998-01-01

    This report applies Event Sequence Analysis, methodology adapted from aircraft mishap investigation, to an investigation of the performance of the Air Intelligence Agency's Information Operations Center (IOC...

  6. Business Intelligence

    OpenAIRE

    Petersen, Anders

    2001-01-01

    Cílem této bakalářské práce je seznámení s Business Intelligence a zpracování vývojového trendu, který ovlivňuje podobu řešení Business Intelligence v podniku ? Business Activity Monitoring. Pro zpracování tohoto tématu byla použita metoda studia odborných pramenů, a to jak v českém, tak v anglickém jazyce. Hlavním přínosem práce je ucelený, v českém jazyce zpracovaný materiál pojednávající o Business Activity Monitoring. Práce je rozdělena do šesti hlavních kapitol. Prvních pět je věnováno p...

  7. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  8. Practical Applications of Intelligent Systems : Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering

    CERN Document Server

    Li, Tianrui

    2012-01-01

    Proceedings of The Sixth International Conference on Intelligent System and Knowledge Engineering presents selected papers from the conference ISKE 2011, held December 15-17 in Shanghai, China. This proceedings doesn’t only examine original research and approaches in the broad areas of intelligent systems and knowledge engineering, but also present new methodologies and practices in intelligent computing paradigms. The book introduces the current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, information retrieval, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, natural-language processing, etc. Furthermore, new computing methodologies are presented, including cloud computing, service computing and pervasive computing with traditional intelligent methods. The proceedings will be beneficial for both researchers and practitioners who want to utilize intelligent methods in their specific res...

  9. The 1990 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  10. Towards Intelligently - Sustainable Cities?

    Directory of Open Access Journals (Sweden)

    Luca Salvati

    2013-04-01

    Full Text Available In the quest for achieving sustainable cities, Intelligent and Knowledge City Programmes (ICPs and KCPs represent cost-efficient strategies for improving the overall performance of urban systems. However, even though nobody argues on the desirability of making cities “smarter”, the fundamental questions of how and to what extent can ICPs and KCPs contribute to the achievement of urban sustainability lack a precise answer. In the attempt of providing a structured answer to these interrogatives, this paper presents a methodology developed for investigating the modalities through which ICPs and KCPs contribute to the achievement or urban sustainability. Results suggest that ICPs and KCPs efficacy lies in supporting cities achieve a sustainable urban metabolism through optimization, innovation and behavior changes.

  11. Artificial Intelligence and brain.

    Science.gov (United States)

    Shapshak, Paul

    2018-01-01

    From the start, Kurt Godel observed that computer and brain paradigms were considered on a par by researchers and that researchers had misunderstood his theorems. He hailed with displeasure that the brain transcends computers. In this brief article, we point out that Artificial Intelligence (AI) comprises multitudes of human-made methodologies, systems, and languages, and implemented with computer technology. These advances enhance development in the electron and quantum realms. In the biological realm, animal neurons function, also utilizing electron flow, and are products of evolution. Mirror neurons are an important paradigm in neuroscience research. Moreover, the paradigm shift proposed here - 'hall of mirror neurons' - is a potentially further productive research tactic. These concepts further expand AI and brain research.

  12. Intelligence and negotiating

    International Nuclear Information System (INIS)

    George, D.G.

    1990-01-01

    This paper discusses the role of US intelligence during arms control negotiations between 1982 and 1987. It also covers : the orchestration of intelligence projects; an evaluation of the performance of intelligence activities; the effect intelligence work had on actual arms negotiations; and suggestions for improvements in the future

  13. Intelligent products : A survey

    NARCIS (Netherlands)

    Meyer, G.G.; Främling, K.; Holmström, J.

    This paper presents an overview of the field of Intelligent Products. As Intelligent Products have many facets, this paper is mainly focused on the concept behind Intelligent Products, the technical foundations, and the achievable practical goals of Intelligent Products. A novel classification of

  14. Intelligence Issues for Congress

    Science.gov (United States)

    2013-04-23

    open source information— osint (newspapers...by user agencies. Section 1052 of the Intelligence Reform Act expressed the sense of Congress that there should be an open source intelligence ...center to coordinate the collection, analysis, production, and dissemination of open source intelligence to other intelligence agencies. An Open Source

  15. The Potential Role of Artificial Intelligence Technology in Education.

    Science.gov (United States)

    Salem, Abdel-Badeeh M.

    The field of Artificial Intelligence (AI) and Education has traditionally a technology-based focus, looking at the ways in which AI can be used in building intelligent educational software. In addition AI can also provide an excellent methodology for learning and reasoning from the human experiences. This paper presents the potential role of AI in…

  16. Race of Examiner Effects and the Validity of Intelligence Tests.

    Science.gov (United States)

    Graziano, William G.; And Others

    1982-01-01

    Recent empirical evidence for the influence of examiner's race on examinee's performance on intelligence tests is reviewed. The current literature, 1966 through 1980, offers little support for the hypothesis that examiner's race has a systematic effect on examinee's performance on intelligence tests. Conceptual and methodological issues are…

  17. Intelligent Governmentality

    Directory of Open Access Journals (Sweden)

    Willem de Lint

    2008-10-01

    Full Text Available Recently, within liberal democracies, the post-Westphalian consolidation of security and intelligence has ushered in the normalization not only of security in ‘securitization’ but also of intelligence in what is proposed here as ‘intelligencification.’ In outlining the features of intelligencified governance, my aim is to interrogate the view that effects or traces, and productivity rather than negation is as persuasive as commonly thought by the constructivists. After all, counter-intelligence is both about purging and reconstructing the archive for undisclosed values. In practice, what is being normalized is the authorized and legalized use of release and retention protocols of politically actionable information. The intelligencification of governmentality affords a sovereignty shell-game or the instrumentalization of sovereign power by interests that are dependent on, yet often inimical to, the power of state, national, and popular sovereignty. On voit le politique et le social comme dépendant de contingences exclusives. Récemment, au sein des démocraties libérales, la consolidation de la sécurité et des services de renseignements de sécurité qui a suivi les traités de la Westphalie a donné lieu à la normalisation non seulement de la sécurité en «sécurisation» mais aussi des services de renseignements de sécurité en ce qui est proposé ici comme «intelligencification» [terme anglais créé par l’auteur, dérivé du mot anglais «intelligence» dans le sens de renseignements des écurité]. En particulier, ce que l’on normalise dans le but de contourner des contingences exclusives est l’utilisation autorisée et légalisée de protocoles de communication et de rétention d’information qui, politiquement, pourrait mener à des poursuites. En esquissant les traits de la gouvernance «intelligencifiée», mon but est d’interroger le point de vue que les effets ou les traces, et la productivité plutôt que la

  18. Pathogen intelligence

    Directory of Open Access Journals (Sweden)

    Michael eSteinert

    2014-01-01

    Full Text Available Different species inhabit different sensory worlds and thus have evolved diverse means of processing information, learning and memory. In the escalated arms race with host defense, each pathogenic bacterium not only has evolved its individual cellular sensing and behaviour, but also collective sensing, interbacterial communication, distributed information processing, joint decision making, dissociative behaviour, and the phenotypic and genotypic heterogeneity necessary for epidemiologic success. Moreover, pathogenic populations take advantage of dormancy strategies and rapid evolutionary speed, which allow them to save co-generated intelligent traits in a collective genomic memory. This review discusses how these mechanisms add further levels of complexity to bacterial pathogenicity and transmission, and how mining for these mechanisms could help to develop new anti-infective strategies.

  19. Intelligent Routines

    CERN Document Server

    Anastassiou, George A

    Intelligent Routines II: Solving Linear Algebra and Differential Geometry with Sage” contains numerous of examples and problems as well as many unsolved problems. This book extensively applies the successful software Sage, which can be found free online http://www.sagemath.org/. Sage is a recent and popular software for mathematical computation, available freely and simple to use. This book is useful to all applied scientists in mathematics, statistics and engineering, as well for late undergraduate and graduate students of above subjects. It is the first such book in solving symbolically with Sage problems in Linear Algebra and Differential Geometry. Plenty of SAGE applications are given at each step of the exposition.

  20. Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

    Science.gov (United States)

    al-Rifaie, Mohammad Majid; Aber, Ahmed; Hemanth, Duraiswamy Jude

    2015-12-01

    This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality is investigated by running the swarms on sample CT images and X-rays whose status have been determined by senior radiologists. In addition, a hybrid swarm intelligence-learning vector quantisation (LVQ) approach is proposed in the context of magnetic resonance (MR) brain image segmentation. The particle swarm optimisation is used to train the LVQ which eliminates the iteration-dependent nature of LVQ. The proposed methodology is used to detect the tumour regions in the abnormal MR brain images.

  1. Business intelligence and performance management theory, systems and industrial applications

    CERN Document Server

    2013-01-01

    This book covers all the basic concepts of business intelligence and performance management including strategic support, business applications, methodologies and technologies from the field, and thoroughly explores the benefits, issues and challenges of each.

  2. Special Operations Reconnaissance (SOR) Scenario: Intelligence Analysis and Mission Planning

    National Research Council Canada - National Science Library

    Warner, Norman; Burkman, Lisa; Biron, H. C

    2008-01-01

    ...) scenario and the methodology used to generate and validate the scenario. The face of military team collaboration has changed due to gathering intelligence from broader and more diverse sources...

  3. A Study on a Hybrid Approach for Diagnosing Faults in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Yang, M.; Zhang, Z.J.; Peng, M.J.; Yan, S.Y.; Wang, H.; Ouyang, J.

    2006-01-01

    Proper and rapid identification of malfunctions is of premier importance for the safe operation of Nuclear Power Plants (NPP). Many monitoring or/and diagnosis methodologies based on artificial and computational intelligence have been proposed to aid operator to understand system problems, perform trouble-shooting action and reduce human error under serious pressure. However, because no single method is adequate to handle all requirements for diagnostic system, hybrid approaches where different methods work in conjunction to solve parts of the problem interest researchers greatly. In this study, Multilevel Flow Models (MFM) and Artificial Neural Network (ANN) are proposed and employed to develop a fault diagnosis system with the intention of improving the success rate of recognition on the one hand, and improving the understandability of diagnostic process and results on the other hand. Several simulation cases were conducted for evaluating the performance of the proposed diagnosis system. The simulation results validated the effectiveness of the proposed hybrid approach. (authors)

  4. Intelligence: Real or artificial?

    OpenAIRE

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

  5. Seventh International Conference on Intelligent Systems and Knowledge Engineering - Foundations and Applications of Intelligent Systems

    CERN Document Server

    Li, Tianrui; Li, Hongbo

    2014-01-01

    These proceedings present technical papers selected from the 2012 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2012), held on December 15-17 in Beijing. The aim of this conference is to bring together experts from different fields of expertise to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new findings and perspectives on future developments. The proceedings introduce current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, knowledge engineering, information retrieval, information theory, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, and natural-language processing, etc. Furthermore they include papers on new intelligent computing paradigms, which combine new computing methodologies, e.g., cloud computing, service computing and pervasive computing with traditional intelligent methods. By presenting new method...

  6. Building the competitive intelligence knowledge: processes and activities in a corporate organisation

    OpenAIRE

    Sreenivasulu, V.

    1999-01-01

    This paper discusses the process of building and developing comprehensive tools, techniques, support systems, and better methods of harnessing the competitive intelligence knowledge processes. The author stresses the need for building sophisticated methodological competitive intelligence knowledge acquisition, systematic collection of competitive intelligence knowledge from various sources for critical analysis, process, organization, synthesis, assessment, screening, filtering and interpreta...

  7. Web survey methodology

    CERN Document Server

    Callegaro, Mario; Vehovar, Asja

    2015-01-01

    Web Survey Methodology guides the reader through the past fifteen years of research in web survey methodology. It both provides practical guidance on the latest techniques for collecting valid and reliable data and offers a comprehensive overview of research issues. Core topics from preparation to questionnaire design, recruitment testing to analysis and survey software are all covered in a systematic and insightful way. The reader will be exposed to key concepts and key findings in the literature, covering measurement, non-response, adjustments, paradata, and cost issues. The book also discusses the hottest research topics in survey research today, such as internet panels, virtual interviewing, mobile surveys and the integration with passive measurements, e-social sciences, mixed modes and business intelligence. The book is intended for students, practitioners, and researchers in fields such as survey and market research, psychological research, official statistics and customer satisfaction research.

  8. Handling Diagnosis of Schizophrenia by a Hybrid Method

    Directory of Open Access Journals (Sweden)

    Luciano Comin Nunes

    2015-01-01

    Full Text Available Psychotics disorders, most commonly known as schizophrenia, have incapacitated professionals in different sectors of activities. Those disorders have caused damage in a microlevel to the individual and his/her family and in a macrolevel to the economic and production system of the country. The lack of early and sometimes very late diagnosis has provided reactive measures, when the professional is already showing psychological signs of incapacity to work. This study aims to help the early diagnosis of psychotics’ disorders with a hybrid proposal of an expert system that is integrated to structured methodologies in decision support (multicriteria decision analysis: MCDA and knowledge structured representations into production rules and probabilities (artificial intelligence: AI.

  9. Disturbance observer-based adaptive sliding mode hybrid projective ...

    Indian Academy of Sciences (India)

    Ayub Khan

    2018-04-21

    Apr 21, 2018 ... systems, the effect of external disturbances, energy fluc- tuation and other such ...... When we apply the above proposed strategy to achieve hybrid projective ..... ory and intelligent control (Springer, 2016) pp. 681–. 697.

  10. Computational intelligence, medicine and biology selected links

    CERN Document Server

    Zaitseva, Elena

    2015-01-01

    This book contains an interesting and state-of the art collection of chapters presenting several examples of attempts to developing modern tools utilizing computational intelligence in different real life problems encountered by humans. Reasoning, prediction, modeling, optimization, decision making, etc. need modern, soft and intelligent algorithms, methods and methodologies to solve, in the efficient ways, problems appearing in human activity. The contents of the book is divided into two parts. Part I, consisting of four chapters, is devoted to selected links of computational intelligence, medicine, health care and biomechanics. Several problems are considered: estimation of healthcare system reliability, classification of ultrasound thyroid images, application of fuzzy logic to measure weight status and central fatness, and deriving kinematics directly from video records. Part II, also consisting of four chapters, is devoted to selected links of computational intelligence and biology. The common denominato...

  11. Hybrid perturbation methods based on statistical time series models

    Science.gov (United States)

    San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario

    2016-04-01

    In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.

  12. Creating Business Intelligence from Course Management Systems

    Science.gov (United States)

    van Dyk, Liezl; Conradie, Pieter

    2007-01-01

    Purpose: This article seeks to address the interface between individual learning facilitators that use course management systems (CMS) data to support decision-making and course design and institutional infrastructure providers that are responsible for institutional business intelligence. Design/methodology/approach: The design of a data warehouse…

  13. Intelligent methods for cyber warfare

    CERN Document Server

    Reformat, Marek; Alajlan, Naif

    2015-01-01

    Cyberwarfare has become an important concern for governmental agencies as well businesses of various types.  This timely volume, with contributions from some of the internationally recognized, leaders in the field, gives readers a glimpse of the new and emerging ways that Computational Intelligence and Machine Learning methods can be applied to address problems related to cyberwarfare. The book includes a number of chapters that can be conceptually divided into three topics: chapters describing different data analysis methodologies with their applications to cyberwarfare, chapters presenting a number of intrusion detection approaches, and chapters dedicated to analysis of possible cyber attacks and their impact. The book provides the readers with a variety of methods and techniques, based on computational intelligence, which can be applied to the broad domain of cyberwarfare.

  14. Educational Programs for Intelligence Professionals.

    Science.gov (United States)

    Miller, Jerry P.

    1994-01-01

    Discusses the need for education programs for competitive intelligence professionals. Highlights include definitions of intelligence functions, focusing on business intelligence; information utilization by decision makers; information sources; competencies for intelligence professionals; and the development of formal education programs. (38…

  15. A New Dimension of Business Intelligence: Location-based Intelligence

    OpenAIRE

    Zeljko Panian

    2012-01-01

    Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

  16. Intelligent Extruder

    Energy Technology Data Exchange (ETDEWEB)

    AlperEker; Mark Giammattia; Paul Houpt; Aditya Kumar; Oscar Montero; Minesh Shah; Norberto Silvi; Timothy Cribbs

    2003-04-24

    ''Intelligent Extruder'' described in this report is a software system and associated support services for monitoring and control of compounding extruders to improve material quality, reduce waste and energy use, with minimal addition of new sensors or changes to the factory floor system components. Emphasis is on process improvements to the mixing, melting and de-volatilization of base resins, fillers, pigments, fire retardants and other additives in the :finishing'' stage of high value added engineering polymer materials. While GE Plastics materials were used for experimental studies throughout the program, the concepts and principles are broadly applicable to other manufacturers materials. The project involved a joint collaboration among GE Global Research, GE Industrial Systems and Coperion Werner & Pleiderer, USA, a major manufacturer of compounding equipment. Scope of the program included development of a algorithms for monitoring process material viscosity without rheological sensors or generating waste streams, a novel detection scheme for rapid detection of process upsets and an adaptive feedback control system to compensate for process upsets where at line adjustments are feasible. Software algorithms were implemented and tested on a laboratory scale extruder (50 lb/hr) at GE Global Research and data from a production scale system (2000 lb/hr) at GE Plastics was used to validate the monitoring and detection software. Although not evaluated experimentally, a new concept for extruder process monitoring through estimation of high frequency drive torque without strain gauges is developed and demonstrated in simulation. A plan to commercialize the software system is outlined, but commercialization has not been completed.

  17. Cross-disciplinarity and hybrid methodologies

    DEFF Research Database (Denmark)

    Ribeiro, Gustavo; Knudsen, Jakob

    This paper describes experiences with a multidisciplinary course where architecture students worked together with urban planning and engineering students looking at urban developments in peri-urban areas in Gaborone. Added to a multidisciplinary approach the course also invilved an international ...

  18. Intelligent Mission Controller Node

    National Research Council Canada - National Science Library

    Perme, David

    2002-01-01

    The goal of the Intelligent Mission Controller Node (IMCN) project was to improve the process of translating mission taskings between real-world Command, Control, Communications, Computers, and Intelligence (C41...

  19. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Verhaegh, W.F.J.; Aarts, E.H.L.; Korst, J.H.M.

    2004-01-01

    In this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.

  20. Advanced intelligent systems

    CERN Document Server

    Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

    2014-01-01

    Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

  1. Non-Newtonian Aspects of Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2016-05-01

    The challenge of this work is to connect physics with the concept of intelligence. By intelligence we understand a capability to move from disorder to order without external resources, i.e., in violation of the second law of thermodynamics. The objective is to find such a mathematical object described by ODE that possesses such a capability. The proposed approach is based upon modification of the Madelung version of the Schrodinger equation by replacing the force following from quantum potential with non-conservative forces that link to the concept of information. A mathematical formalism suggests that a hypothetical intelligent particle, besides the capability to move against the second law of thermodynamics, acquires such properties like self-image, self-awareness, self-supervision, etc. that are typical for Livings. However since this particle being a quantum-classical hybrid acquires non-Newtonian and non-quantum properties, it does not belong to the physics matter as we know it: the modern physics should be complemented with the concept of the information force that represents a bridge to intelligent particle. As a follow-up of the proposed concept, the following question is addressed: can artificial intelligence (AI) system composed only of physical components compete with a human? The answer is proven to be negative if the AI system is based only on simulations, and positive if digital devices are included. It has been demonstrated that there exists such a quantum neural net that performs simulations combined with digital punctuations. The universality of this quantum-classical hybrid is in capability to violate the second law of thermodynamics by moving from disorder to order without external resources. This advanced capability is illustrated by examples. In conclusion, a mathematical machinery of the perception that is the fundamental part of a cognition process as well as intelligence is introduced and discussed.

  2. Artificial Intelligence Project

    Science.gov (United States)

    1990-01-01

    Symposium on Aritificial Intelligence and Software Engineering Working Notes, March 1989. Blumenthal, Brad, "An Architecture for Automating...Artificial Intelligence Project Final Technical Report ARO Contract: DAAG29-84-K-OGO Artificial Intelligence LaboratO"ry The University of Texas at...Austin N>.. ~ ~ JA 1/I 1991 n~~~ Austin, Texas 78712 ________k A,.tificial Intelligence Project i Final Technical Report ARO Contract: DAAG29-84-K-0060

  3. Orchestrating Multiple Intelligences

    Science.gov (United States)

    Moran, Seana; Kornhaber, Mindy; Gardner, Howard

    2006-01-01

    Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

  4. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Weber, W.; Rabaey, J.M.; Aarts, E.

    2005-01-01

    We briefly review the concept of ambient intelligence and discuss its relation with the domain of intelligent algorithms. By means of four examples of ambient intelligent systems, we argue that new computing methods and quantification measures are needed to bridge the gap between the class of

  5. Reflection on robotic intelligence

    NARCIS (Netherlands)

    Bartneck, C.

    2006-01-01

    This paper reflects on the development or robots, both their physical shape as well as their intelligence. The later strongly depends on the progress made in the artificial intelligence (AI) community which does not yet provide the models and tools necessary to create intelligent robots. It is time

  6. [Artificial intelligence in psychiatry-an overview].

    Science.gov (United States)

    Meyer-Lindenberg, A

    2018-06-18

    Artificial intelligence and the underlying methods of machine learning and neuronal networks (NN) have made dramatic progress in recent years and have allowed computers to reach superhuman performance in domains that used to be thought of as uniquely human. In this overview, the underlying methodological developments that made this possible are briefly delineated and then the applications to psychiatry in three domains are discussed: precision medicine and biomarkers, natural language processing and artificial intelligence-based psychotherapeutic interventions. In conclusion, some of the risks of this new technology are mentioned.

  7. Videogames: Multisensory Incentives Boosting Multiple Intelligences in Primary Education

    Science.gov (United States)

    del Moral-Pérez, Mª Esther; Fernández-García, Laura Carlota; Guzmán-Duque, Alba Patricia

    2015-01-01

    Introduction: Our research focused on studying the extent to which the planned, systematic use of educational videogames can result in the generation of learning contexts conducive to developing Multiple Intelligences (MIs) amongst schoolchildren. Methodology: A twofold methodological approach was adopted: a) qualitative: previous assessment and…

  8. Crowd wisdom drives intelligent manufacturing

    Directory of Open Access Journals (Sweden)

    Jiaqi Lu

    2017-03-01

    Full Text Available Purpose – A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process. Design/methodology/approach – Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B, crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing. Findings – This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process. Originality/value – The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.

  9. Business Intelligence in Process Control

    Science.gov (United States)

    Kopčeková, Alena; Kopček, Michal; Tanuška, Pavol

    2013-12-01

    The Business Intelligence technology, which represents a strong tool not only for decision making support, but also has a big potential in other fields of application, is discussed in this paper. Necessary fundamental definitions are offered and explained to better understand the basic principles and the role of this technology for company management. Article is logically divided into five main parts. In the first part, there is the definition of the technology and the list of main advantages. In the second part, an overview of the system architecture with the brief description of separate building blocks is presented. Also, the hierarchical nature of the system architecture is shown. The technology life cycle consisting of four steps, which are mutually interconnected into a ring, is described in the third part. In the fourth part, analytical methods incorporated in the online analytical processing and data mining used within the business intelligence as well as the related data mining methodologies are summarised. Also, some typical applications of the above-mentioned particular methods are introduced. In the final part, a proposal of the knowledge discovery system for hierarchical process control is outlined. The focus of this paper is to provide a comprehensive view and to familiarize the reader with the Business Intelligence technology and its utilisation.

  10. Quality control of intelligence research

    International Nuclear Information System (INIS)

    Lu Yan; Xin Pingping; Wu Jian

    2014-01-01

    Quality control of intelligence research is the core issue of intelligence management, is a problem in study of information science This paper focuses on the performance of intelligence to explain the significance of intelligence research quality control. In summing up the results of the study on the basis of the analysis, discusses quality control methods in intelligence research, introduces the experience of foreign intelligence research quality control, proposes some recommendations to improve quality control in intelligence research. (authors)

  11. Separation of BSA through FAU-type zeolite ceramic composite membrane formed on tubular ceramic support: Optimization of process parameters by hybrid response surface methodology and biobjective genetic algorithm.

    Science.gov (United States)

    Vinoth Kumar, R; Ganesh Moorthy, I; Pugazhenthi, G

    2017-08-09

    In this study, Faujasite (FAU) zeolite was coated on low-cost tubular ceramic support as a separating layer through hydrothermal route. The mixture of silicate and aluminate solutions was used to create a zeolitic separation layer on the support. The prepared zeolite ceramic composite membrane was characterized using X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), particle size distribution (PSD), field emission scanning electron microscopy (FESEM), and zeta potential measurements. The porosity of ceramic support (53%) was reduced by the deposition of FAU (43%) zeolite layer. The pore size and water permeability of the membrane were evaluated as 0.179 µm and 1.62 × 10 -7  m 3 /m 2  s kPa, respectively, which are lower than that of the support (pore size of 0.309 µm and water permeability of 5.93 × 10 -7  m 3 /m 2  s kPa). The permeate flux and rejection potential of the prepared membrane were evaluated by microfiltration of bovine serum albumin (BSA). To study the influences of three independent variables such as operating pressure (68.94-275.79 kPa), concentration of BSA (100-500 ppm), and solution pH (2-4) on permeate flux and percentage of rejection, the response surface methodology (RSM) was used. The predicted models for permeate flux and rejection were further subjected to biobjective genetic algorithm (GA). The hybrid RSM-GA approach resulted in a maximum permeate flux of 2.66 × 10 -5  m 3 /m 2  s and BSA rejection of 88.02%, at which the optimum conditions were attained as 100 ppm BSA concentration, 2 pH solution, and 275.79 kPa applied pressure. In addition, the separation efficiency was compared with other membranes applied for BSA separation to know the potential of the fabricated FAU zeolite ceramic composite membrane.

  12. A novel fusion methodology to bridge GPS outages for land vehicle positioning

    International Nuclear Information System (INIS)

    Chen, Wei; Li, Xu; Song, Xiang; Xu, Qimin; Li, Bin; Song, Xianghui

    2015-01-01

    Many intelligent transportation system applications require accurate, reliable, and continuous vehicle position information whether in open-sky environments or in Global Positioning System (GPS) denied environments. However, there remains a challenging task for land vehicles to achieve such positioning performance using low-cost sensors, especially microelectromechanical system (MEMS) sensors. In this paper, a novel and cost-effective fusion methodology to bridge GPS outages is proposed and applied in the Inertial Navigation System (INS)/GPS/ compass integrated positioning system. In the implementation of the proposed methodology, a key data preprocessing algorithm is first developed to eliminate the noise in inertial sensors in order to provide more accurate information for subsequent modeling. Then, a novel hybrid strategy incorporating the designed autoregressive model (AR model)-based forward estimator (ARFE) with Kalman filter (KF) is presented to predict the INS position errors during GPS outages. To verify the feasibility and effectiveness of the proposed methodology, real road tests with various scenarios were performed. The proposed methodology illustrates significant improvement in positioning accuracy during GPS outages. (paper)

  13. Brain Intelligence: Go Beyond Artificial Intelligence

    OpenAIRE

    Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

    2017-01-01

    Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

  14. Methodological Naturalism Under Attack | Ruse | South African ...

    African Journals Online (AJOL)

    Recently the Intelligent Design movement has been arguing against methodological naturalism, and in this project they have been joined by the Christian philosopher Alvin Plantinga. In this paper I examine Plantinga\\'s arguments and conclude not only that they are not well taken, but that he does no good service to his ...

  15. Analytical, Practical and Emotional Intelligence and Line Manager Competencies

    Directory of Open Access Journals (Sweden)

    Anna Baczyńska

    2015-12-01

    Full Text Available Purpose: The research objective was to examine to what extent line manager competencies are linked to intelligence, and more specifically, three types of intelligence: analytical (fluid, practical and emotional. Methodology: The research was carried out with line managers (N=98 who took part in 12 Assessment Centre sessions and completed tests measuring analytical, practical and emotional intelligence. The adopted hypotheses were tested using a multiple regression. In the regression model, the dependent variable was a managerial competency (management and striving for results, social skills, openness to change, problem solving, employee development and the explanatory variables were the three types of intelligence. Five models, each for a separate management competency, were tested in this way. Findings: In the study, it was hypothesized that practical intelligence relates to procedural tacit knowledge and is the strongest indicator of managerial competency. Analysis of the study results testing this hypothesis indicated that practical intelligence largely accounts for the level of competency used in managerial work (from 21% to 38%. The study findings suggest that practical intelligence is a better indicator of managerial competencies among line managers than traditionally measured IQ or emotional intelligence. Originality: This research fills an important gap in the literature on the subject, indicating the links between major contemporary selection indicators (i.e., analytical, practical and emotional intelligence and managerial competencies presented in realistic work simulations measured using the Assessment Centre process.

  16. Business intelligence making decisions through data analytics

    CERN Document Server

    Surma, Jerzy

    2014-01-01

    This book is about using business intelligence as a management information system for supporting managerial decision making. It concentrates primarily on practical business issues and demonstrates how to apply data warehousing and data analytics to support business decision making. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. All examples are based on the most recent achievements in business intelligence. Finally this book outlines an overview of a methodology that takes into account the complexity of developing applications in an integrated business intelligence environment. This book is written for managers, business consultants, and undergraduate and postgraduates students in business administration.

  17. Methodology for determining the value of complexity parameter for emergency situation during driving of the train

    Directory of Open Access Journals (Sweden)

    O. M. Horobchenko

    2015-12-01

    Full Text Available Purpose. During development of intelligent control systems for locomotive there is a need in the evaluation of the current train situation in the terms of traffic safety. In order to estimate the probability of the development of various emergency situations in to the traffic accidents, it is necessary to determine their complexity. The purpose of this paper is to develop the methodology for determining the complexity of emergency situations during the locomotive operation. Methodology. To achieve this purpose the statistical material of traffic safety violations was accumulated. The causes of violations are divided into groups: technical factors, human factors and external influences. Using the theory of hybrid networks it was obtained a model that gives the output complexity parameter of the emergency situation. Network type: multilayer perceptron with hybrid neurons of the first layer and the sigmoid activation function. The methods of the probability theory were used for the analysis of the results. Findings. The approach to the formalization of manufacturing situations that can only be described linguistically was developed, that allowed to use them as input data to the model for emergency situation. It was established and proved that the exponent of complexity for emergency situation during driving the train is a random quantity and obeys to the normal distribution law. It was obtained the graph of the cumulative distribution function, which identified the areas for safe operation and an increased risk of accident. Originality. It was proposed theoretical basis for determining the complexity of emergency situations in the train work and received the maximum complexity value of emergency situations that can be admitted in the operating conditions. Practical value. Constant monitoring of this value allows not only respond to the threat of danger, but also getting it in numerical form and use it as one of the input parameters for the

  18. Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence.

    Science.gov (United States)

    Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

    2016-01-01

    We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

  19. On methodology

    DEFF Research Database (Denmark)

    Cheesman, Robin; Faraone, Roque

    2002-01-01

    This is an English version of the methodology chapter in the authors' book "El caso Berríos: Estudio sobre información errónea, desinformación y manipulación de la opinión pública".......This is an English version of the methodology chapter in the authors' book "El caso Berríos: Estudio sobre información errónea, desinformación y manipulación de la opinión pública"....

  20. Multi-objective swarm intelligence theoretical advances and applications

    CERN Document Server

    Jagadev, Alok; Panda, Mrutyunjaya

    2015-01-01

    The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.       

  1. Quo Vadis, Artificial Intelligence?

    OpenAIRE

    Berrar, Daniel; Sato, Naoyuki; Schuster, Alfons

    2010-01-01

    Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervou...

  2. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  3. Intelligence of programs

    Energy Technology Data Exchange (ETDEWEB)

    Novak, D

    1982-01-01

    A general discussion about the level of artificial intelligence in computer programs is presented. The suitability of various languages for the development of complex, intelligent programs is discussed, considering fourth-generation language as well as the well established structured COBOL language. It is concluded that the success of automation in many administrative fields depends to a large extent on the development of intelligent programs.

  4. 7th International Conference on Intelligent Systems and Knowledge Engineering

    CERN Document Server

    Li, Tianrui; Li, Hongbo

    2014-01-01

    These proceedings present technical papers selected from the 2012 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2012), held on December 15-17 in Beijing. The aim of this conference is to bring together experts from different fields of expertise to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new findings and perspectives on future developments. The proceedings introduce current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, knowledge engineering, information retrieval, information theory, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, and natural-language processing, etc. Furthermore they include papers on new intelligent computing paradigms, which combine new computing methodologies, e.g., cloud computing, service computing and pervasive computing with traditional intelligent methods. By presenting new method...

  5. Intelligent Design and Earth History

    Science.gov (United States)

    Elders, W. A.

    2001-05-01

    clumsy, wasteful works of nature as seen in the suffering caused by parasites and in the delight in cruelty shown by some predators when catching and playing with their prey". The positions of other contemporary proponents of ID are far from uniform. Some, while rejecting unguided evolution, appear to accept the concepts of common descent and an Earth 4.6 billion years old. However, within the ID movement there has been very little discussion of its implications for Earth history. For example, is it valid to ask, "Were the Himalayas intelligently designed?" Or should the question be, "Is the physics of plate tectonics intelligently designed?" As well as contingency in the history of life, there are strong elements of contingency in the history of the Earth, in the history of the solar system and in the history of the cosmos. Does ID matter? From a purely operational viewpoint, the rock record could equally well be interpreted in pattern-based investigations as being the product of either naturalistic processes, or as a sequence of intelligently designed events. For example, in correlating horizons between adjacent oil wells using micropaleontology, or in doing seismic stratigraphy, it makes little difference whether foraminifera or unconformities formed by natural or supernatural agencies. However, ID is an anathema for process-based research and its cultural implications are enormous. While we must be careful in our work to separate methodological naturalism from culturally bound philosophical naturalism, methodological naturalism has been an enormously successful approach in the advancement of knowledge. We have moved from the "demon-haunted" world to the world of the human genome. We must take ID seriously; it is a retrograde step.

  6. Machine listening intelligence

    Science.gov (United States)

    Cella, C. E.

    2017-05-01

    This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

  7. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    Science.gov (United States)

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  8. Intelligent Optics Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Intelligent Optics Laboratory supports sophisticated investigations on adaptive and nonlinear optics; advancedimaging and image processing; ground-to-ground and...

  9. Intelligence and childlessness.

    Science.gov (United States)

    Kanazawa, Satoshi

    2014-11-01

    Demographers debate why people have children in advanced industrial societies where children are net economic costs. From an evolutionary perspective, however, the important question is why some individuals choose not to have children. Recent theoretical developments in evolutionary psychology suggest that more intelligent individuals may be more likely to prefer to remain childless than less intelligent individuals. Analyses of the National Child Development Study show that more intelligent men and women express preference to remain childless early in their reproductive careers, but only more intelligent women (not more intelligent men) are more likely to remain childless by the end of their reproductive careers. Controlling for education and earnings does not at all attenuate the association between childhood general intelligence and lifetime childlessness among women. One-standard-deviation increase in childhood general intelligence (15 IQ points) decreases women's odds of parenthood by 21-25%. Because women have a greater impact on the average intelligence of future generations, the dysgenic fertility among women is predicted to lead to a decline in the average intelligence of the population in advanced industrial nations. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. Comparative Analysis of the Main Business Intelligence Solutions

    OpenAIRE

    Alexandra RUSANEANU

    2013-01-01

    Nowadays, Business Intelligence solutions are the main tools for analyzing and monitoring the company’s performance at any organizational level. This paper presents a comparative analysis of the most powerful Business Intelligence solutions using a set of technical features such as infrastructure of the platform, development facilities, complex analysis tools, interactive dashboards and scorecards, mobile integration and complex implementation of performance management methodologies.

  11. The role of trait emotional intelligence in predicting networking behavior

    OpenAIRE

    Teresa Torres-Coronas; María-Arántzazu Vidal-Blasco

    2017-01-01

    Objective – The purpose of this paper is to obtain evidence of the relation between entrepreneur proactive networking behavior and trait emotional intelligence to support transition towards entrepreneurial careers. Design/methodology/approach – The Trait Emotional Intelligence Questionnaire-Short form (TEIQue-SF), developed by Cooper and Petrides (2010), was used to test hypotheses on the factors that define a proactive use of a professional network and their relationship with the indivi...

  12. Theoretical concepts about "Intelligence" - practices and standards in democratic societies

    OpenAIRE

    Mr.Sc. Bahri Gashi

    2013-01-01

    My thesis consists of theoretical analysis on the need for recognition of academic concepts to shape and design research field intelligence community activity, careful analysis of the terms and concepts that are strongly linked to intelligence work methodology, theoretical aspects description given practice best to regulate this specific area in our academic studies, has made the study to take proper shape with bold shades of comparative empirical analysis. My study aims to summarize, to ...

  13. International Conference on Frontiers of Intelligent Computing : Theory and Applications

    CERN Document Server

    Bhateja, Vikrant; Udgata, Siba; Pattnaik, Prasant

    2017-01-01

    The book is a collection of high-quality peer-reviewed research papers presented at International Conference on Frontiers of Intelligent Computing: Theory and applications (FICTA 2016) held at School of Computer Engineering, KIIT University, Bhubaneswar, India during 16 – 17 September 2016. The book presents theories, methodologies, new ideas, experiences and applications in all areas of intelligent computing and its applications to various engineering disciplines like computer science, electronics, electrical and mechanical engineering.

  14. Routledge companion to intelligence studies

    CERN Document Server

    Dover, Robert; Hillebrand, Claudia

    2013-01-01

    The Routledge Companion to Intelligence Studies provides a broad overview of the growing field of intelligence studies. The recent growth of interest in intelligence and security studies has led to an increased demand for popular depictions of intelligence and reference works to explain the architecture and underpinnings of intelligence activity. Divided into five comprehensive sections, this Companion provides a strong survey of the cutting-edge research in the field of intelligence studies: Part I: The evolution of intelligence studies; Part II: Abstract approaches to intelligence; Part III: Historical approaches to intelligence; Part IV: Systems of intelligence; Part V: Contemporary challenges. With a broad focus on the origins, practices and nature of intelligence, the book not only addresses classical issues, but also examines topics of recent interest in security studies. The overarching aim is to reveal the rich tapestry of intelligence studies in both a sophisticated and accessible way. This Companion...

  15. Corporate Education in perspective of Organizational Intelligence

    Directory of Open Access Journals (Sweden)

    Kelly Cristina Wilhelm de Toni

    2016-12-01

    Full Text Available Introduction: To meet the challenges of competitiveness and achieve the conditions for generation of innovation is necessary to ensure that the workforce remains highly qualified. In this context, corporate education is an alternative. Objective: To develop a method to analyze the relationship between process approaches Organizational Intelligence and Corporate Education. Methodology: Theoretical construction performed based on literature review.Construction a methodological approach linked to the problem of this research. Results: Identification of a set of common elements between the approaches: the"Capture" and "Sharing" of knowledge and experience, the "meaning" shared and "Culture" of individual and organizational learning. Conclusions: There is a real connection between the approaches of the study. The proposed method can be seen as a tool to explain and evaluate the process of education in the enterprise from the perspective of organizational intelligence

  16. Hybrid platform. Economical hybrid drive for commercial vehicles; Hybrid Plattform. Wirtschaftlicher Hybridantrieb fuer Nutzfahrzeuge

    Energy Technology Data Exchange (ETDEWEB)

    Wallner, S.; Lamke, M.; Mohr, M.; Sedlacek, M.; Speck, F.D. [ZF Friedrichshafen AG, Friedrichshafen (Germany)

    2011-07-01

    Up to now, hybrid systems have been adapted to their specific requirements in the various applications for trucks, buses as well as mobile and building machines. From a technical point of view, this does indeed result in optimized hybrid drives for each single vehicle application, but due to small volumes, such single developments are critical from a business point of view. ZF Friedrichshafen AG is providing a solution to the technical and economical requirements of the cost-sensitive CV segment in the form of a modular CV parallel hybrid platform composed of a hybrid module system, an inverter, a battery system, and a hybrid software integrated into the overall vehicle. Thanks to the intelligent combination of assemblies and the use of as many identical parts as possible, platforms are realized which cover power ranges between 60 and 120 kW, voltage ranges between 350 and 650 V, and battery capacities between 2 and 4 kWh. The dimensions of the platform elements are such that integration into the diverse commercial vehicle applications is made easy. The hybrid software required for the vehicle-specific functions is also configurable for the mentioned CV applications. (orig.)

  17. Artificial Consciousness or Artificial Intelligence

    OpenAIRE

    Spanache Florin

    2017-01-01

    Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

  18. 2015 Chinese Intelligent Systems Conference

    CERN Document Server

    Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

    2016-01-01

    This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

  19. Correlation between crystallographic computing and artificial intelligence research

    Energy Technology Data Exchange (ETDEWEB)

    Feigenbaum, E A [Stanford Univ., CA; Engelmore, R S; Johnson, C K

    1977-01-01

    Artificial intelligence research, as a part of computer science, has produced a variety of programs of experimental and applications interest: programs for scientific inference, chemical synthesis, planning robot control, extraction of meaning from English sentences, speech understanding, interpretation of visual images, and so on. The symbolic manipulation techniques used in artificial intelligence provide a framework for analyzing and coding the knowledge base of a problem independently of an algorithmic implementation. A possible application of artificial intelligence methodology to protein crystallography is described. 2 figures, 2 tables.

  20. The brain triuno and the ethical intelligence: fundamental counterfoil of the multifocal intelligence

    Directory of Open Access Journals (Sweden)

    C. Seijo

    2013-10-01

    Full Text Available This study has for aim offer an analysis as for the brain triuno and the ethical intelligence: fundamental Counterfoil of the multifocal intelligence, taking in tells one of the theories that it sustains her like they are the different types of multiple intelligences established by Beauport and Cury (2004. The theoretical sustenance, it is based on the contents of Martin (2005, Belohlavek (2007, Galicians (2002, Beauport and Cury (2004, between others, being realized under a symbolic interpretive approach, across a qualitative methodology, type descriptive and not experimental design, by means of a documentary analysis. In this regard, it is found that the ethical intelligence is a mental mechanism that constructs the structural preconceptos and the rules of game with which an individual approaches the reality, that is to say, it is the capacity of the general formation, predicting the behavior for the achievement of aims organizacionales. As for the final considerations they focused in obtaining the most wide knowledge inside the organizations, allowing to reflect before the weaknesses that they present thinking about the brain triuno applying the multifocal intelligence, fundamental counterfoil of the ethical intelligence and of what way the rationing visualizes the strengths, nevertheless of the weaknesses that they present. 

  1. The intelligent system for accident identification in nuclear power plant

    International Nuclear Information System (INIS)

    Hernandez, Jorge Luis.

    1998-01-01

    Accidental situations in NPP are of greet concern for operators, the facility, regulatory bodies and the environment. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making when initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre operational Probabilistic Safety Assessment and the Thermal hydraulic Safety Analyses of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid system from the combination of the artificial intelligence techniques: fussy logic and artificial neural networks. The system works with variables from the process of the firsts circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

  2. The intelligent system for accident identification in NPP

    International Nuclear Information System (INIS)

    Hernandez, Jorge Luis.

    1998-01-01

    Accidental situations in NPP are of greet concern for operators, the facility, regulatory bodies and the environment. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making when initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre operational Probabilistic Safety Assessment and the Thermal hydraulic Safety Analyses of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid system from the combination of the artificial intelligence techniques: fussy logic and artificial neural networks. The system works with variables from the process of the firsts circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

  3. 4th Workshop on Combinations of Intelligent Methods and Applications

    CERN Document Server

    Palade, Vasile; Prentzas, Jim

    2016-01-01

    This volume includes extended and revised versions of the papers presented at the 4th Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2014) which was intended to become a forum for exchanging experience and ideas among researchers and practitioners dealing with combinations of different intelligent methods in Artificial Intelligence. The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing presented efforts combine soft computing methods (fuzzy logic, neural networks and genetic algorithms). Another stream of efforts integrates case-based reasoning or machine learning with soft-computing methods. Some of the combinations have been more widely explored, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. CIMA 2014 was held in conjunction with the 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014). .

  4. Intelligent engineering and technology for nuclear power plant operation

    International Nuclear Information System (INIS)

    Wang, P.P.; Gu, X.

    1996-01-01

    The Three-Mile-Island accident has drawn considerable attention by the engineering, scientific, management, financial, and political communities as well as society at large. This paper surveys possible causes of the accident studied by various groups. Research continues in this area with many projects aimed at specifically improving the performance and operation of a nuclear power plant using the contemporary technologies available. In addition to the known cause of the accident and suggest a strategy for coping with these problems in the future. With the increased use of intelligent methodologies called computational intelligence or soft-computing, a substantially larger collection of powerful tools are now available for our designers to use in order to tackle these sensitive and difficult issues. These intelligent methodologies consists of fuzzy logic, genetic algorithms, neural networks, artificial intelligence and expert systems, pattern recognition, machine intelligence, and fuzzy constraint networks. Using the Three-Mile-Island experience, this paper offers a set of specific recommendations for future designers to take advantage of the powerful tools of intelligent technologies that we are now able to master and encourages the adoption of a novel methodology called fuzzy constraint network

  5. Artificial Intelligence and Virology - quo vadis.

    Science.gov (United States)

    Shapshak, Paul; Somboonwit, Charurut; Sinnott, John T

    2017-01-01

    Artificial Intelligence (AI), robotics, co-robotics (cobots), quantum computers (QC), include surges of scientific endeavor to produce machines (mechanical and software) among numerous types and constructions that are accelerating progress to defeat infectious diseases. There is a plethora of additional applications and uses of these methodologies and technologies for the understanding of biomedicine through bioinformation discovery. Therefore, we briefly outline the use of such techniques in virology.

  6. Methodological approaches in the research of organizational culture

    Directory of Open Access Journals (Sweden)

    Janićijević Nebojša

    2011-01-01

    Full Text Available In the thirty-years-long research of organizational culture, two mutually opposed methodological approaches have emerged: objectivistic quantitative and subjectivistic-qualitative. These two approaches are based on opposite ontological and epistemological assumptions: they include different types of research, and use opposite, quantitative vs. qualitative, methods of research. Each of the methodological approaches has its advantages and disadvantages. For this reason a hybrid approach emerges as a legitimate choice in organizational culture research methodology. It combines elements of both subjectivistic and objectivistic methodological approaches, according to the goals, content, and context of the research and preferences of the researcher himself/herself. Since it is possible to combine the two principal methodological approaches in various ways, there are several possible hybrid methodologies in organizational culture research. After the review of objectivistic quantitative and subjectivistic-qualitative methodological approaches, one of possible hybrid approaches in the research of organizational culture is presented in this paper.

  7. Methodological guidelines

    International Nuclear Information System (INIS)

    Halsnaes, K.; Callaway, J.M.; Meyer, H.J.

    1999-01-01

    The guideline document establishes a general overview of the main components of climate change mitigation assessment. This includes an outline of key economic concepts, scenario structure, common assumptions, modelling tools and country study assumptions. The guidelines are supported by Handbook Reports that contain more detailed specifications of calculation standards, input assumptions and available tools. The major objectives of the project have been provided a methodology, an implementing framework and a reporting system which countries can follow in meeting their future reporting obligations under the FCCC and for GEF enabling activities. The project builds upon the methodology development and application in the UNEP National Abatement Coasting Studies (UNEP, 1994a). The various elements provide countries with a road map for conducting climate change mitigation studies and submitting national reports as required by the FCCC. (au) 121 refs

  8. Methodological guidelines

    Energy Technology Data Exchange (ETDEWEB)

    Halsnaes, K.; Callaway, J.M.; Meyer, H.J.

    1999-04-01

    The guideline document establishes a general overview of the main components of climate change mitigation assessment. This includes an outline of key economic concepts, scenario structure, common assumptions, modelling tools and country study assumptions. The guidelines are supported by Handbook Reports that contain more detailed specifications of calculation standards, input assumptions and available tools. The major objectives of the project have been provided a methodology, an implementing framework and a reporting system which countries can follow in meeting their future reporting obligations under the FCCC and for GEF enabling activities. The project builds upon the methodology development and application in the UNEP National Abatement Coasting Studies (UNEP, 1994a). The various elements provide countries with a road map for conducting climate change mitigation studies and submitting national reports as required by the FCCC. (au) 121 refs.

  9. Distributed intelligence in CAMAC

    International Nuclear Information System (INIS)

    Kunz, P.F.

    1977-01-01

    The CAMAC digital interface standard has served us well since 1969. During this time there have been enormous advances in digital electronics. In particular, low cost microprocessors now make it feasible to consider use of distributed intelligence even in simple data acquisition systems. This paper describes a simple extension of the CAMAC standard which allows distributed intelligence at the crate level

  10. Intelligent design som videnskab?

    DEFF Research Database (Denmark)

    Klausen, Søren Harnow

    2007-01-01

    Diskuterer hvorvidt intelligent design kan betegnes som videnskab; argumenterer for at dette grundet fraværet af klare demarkationskriterier næppe kan afvises.......Diskuterer hvorvidt intelligent design kan betegnes som videnskab; argumenterer for at dette grundet fraværet af klare demarkationskriterier næppe kan afvises....

  11. Distributed intelligence in CAMAC

    International Nuclear Information System (INIS)

    Kunz, P.F.

    1977-01-01

    A simple extension of the CAMAC standard is described which allows distributed intelligence at the crate level. By distributed intelligence is meant that there is more than one source of control in a system. This standard is just now emerging from the NIM Dataway Working Group and its European counterpart. 1 figure

  12. Intelligence and treaty ratification

    International Nuclear Information System (INIS)

    Cahn, A.H.

    1990-01-01

    This paper reports that there are two sets of questions applicable to the ratification phase: what is the role of intelligence in the ratification process? What effect did intelligence have on that process. The author attempts to answer these and other questions

  13. Applying Multiple Intelligences

    Science.gov (United States)

    Christodoulou, Joanna A.

    2009-01-01

    The ideas of multiple intelligences introduced by Howard Gardner of Harvard University more than 25 years ago have taken form in many ways, both in schools and in other sometimes-surprising settings. The silver anniversary of Gardner's learning theory provides an opportunity to reflect on the ways multiple intelligences theory has taken form and…

  14. Next generation Emotional Intelligence

    Science.gov (United States)

    J. Saveland

    2012-01-01

    Emotional Intelligence has been a hot topic in leadership training since Dan Goleman published his book on the subject in 1995. Emotional intelligence competencies are typically focused on recognition and regulation of emotions in one's self and social situations, yielding four categories: self-awareness, self-management, social awareness and relationship...

  15. Intelligence by consent

    DEFF Research Database (Denmark)

    Diderichsen, Adam; Rønn, Kira Vrist

    2017-01-01

    This article contributes to the current discussions concerning an adequate framework for intelligence ethics. The first part critically scrutinises the use of Just War Theory in intelligence ethics with specific focus on the just cause criterion. We argue that using self-defence as justifying cau...

  16. Intelligence and Physical Attractiveness

    Science.gov (United States)

    Kanazawa, Satoshi

    2011-01-01

    This brief research note aims to estimate the magnitude of the association between general intelligence and physical attractiveness with large nationally representative samples from two nations. In the United Kingdom, attractive children are more intelligent by 12.4 IQ points (r=0.381), whereas in the United States, the correlation between…

  17. Intelligence and treaty ratification

    International Nuclear Information System (INIS)

    Naftzinger, J.E.

    1990-01-01

    This paper describes the atmosphere leading up to the Senate INF hearings and then surveys the broad issues they raised. After that, the author highlights several aspects of the intelligence community's involvement and discusses the specific intelligence-related issues as the Senate committees saw them, notes their impact on the outcome, and finally draws several conclusions and lessons pertinent to the future

  18. Intelligence, Race, and Genetics

    Science.gov (United States)

    Sternberg, Robert J.; Grigorenko, Elena L.; Kidd, Kenneth K.

    2005-01-01

    In this article, the authors argue that the overwhelming portion of the literature on intelligence, race, and genetics is based on folk taxonomies rather than scientific analysis. They suggest that because theorists of intelligence disagree as to what it is, any consideration of its relationships to other constructs must be tentative at best. They…

  19. Multiple Intelligences in Action.

    Science.gov (United States)

    Campbell, Bruce

    1992-01-01

    Describes the investigation of the effects of a four-step model program used with third through fifth grade students to implement Gardener's concepts of seven human intelligences--linguistic, logical/mathematical, visual/spatial, musical, kinesthetic, intrapersonal, and interpersonal intelligence--into daily learning. (BB)

  20. The Reproduction of Intelligence

    Science.gov (United States)

    Meisenberg, Gerhard

    2010-01-01

    Although a negative relationship between fertility and education has been described consistently in most countries of the world, less is known about the relationship between intelligence and reproductive outcomes. Also the paths through which intelligence influences reproductive outcomes are uncertain. The present study uses the NLSY79 to analyze…

  1. Intelligent robot action planning

    Energy Technology Data Exchange (ETDEWEB)

    Vamos, T; Siegler, A

    1982-01-01

    Action planning methods used in intelligent robot control are discussed. Planning is accomplished through environment understanding, environment representation, task understanding and planning, motion analysis and man-machine communication. These fields are analysed in detail. The frames of an intelligent motion planning system are presented. Graphic simulation of the robot's environment and motion is used to support the planning. 14 references.

  2. Computational Intelligence in Intelligent Data Analysis

    CERN Document Server

    Nürnberger, Andreas

    2013-01-01

    Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intell...

  3. Intelligence and Prosocial Behavior

    DEFF Research Database (Denmark)

    Han, Ru; Shi, Jiannong; Yong, W.

    2012-01-01

    Results of prev ious studies of the relationship between prosocial behav ior and intelligence hav e been inconsistent. This study attempts to distinguish the dif f erences between sev eral prosocial tasks, and explores the way s in which cognitiv e ability inf luences prosocial behav ior. In Study...... One and Two, we reexamined the relationship between prosocial behav ior and intelligence by employ ing a costly signaling theory with f our games. The results rev ealed that the prosocial lev el of smarter children is higher than that of other children in more complicated tasks but not so in simple...... tasks. In Study Three, we tested the moderation ef f ect of the av erage intelligence across classes, and the results did not show any group intelligence ef f ect on the relationship between intelligence and prosocial behav ior....

  4. Business Intelligence Systems

    Directory of Open Access Journals (Sweden)

    Bogdan NEDELCU

    2014-02-01

    Full Text Available The aim of this article is to show the importance of business intelligence and its growing influence. It also shows when the concept of business intelligence was used for the first time and how it evolved over time. The paper discusses the utility of a business intelligence system in any organization and its contribution to daily activities. Furthermore, we highlight the role and the objectives of business intelligence systems inside an organization and the needs to grow the incomes and reduce the costs, to manage the complexity of the business environment and to cut IT costs so that the organization survives in the current competitive climate. The article contains information about architectural principles of a business intelligence system and how such a system can be achieved.

  5. Ability-versus skill-based assessment of emotional intelligence.

    Science.gov (United States)

    Bradberry, Travis R; Su, Lac D

    2006-01-01

    Emotional intelligence has received an intense amount of attention in leadership circles during the last decade and continuing debate exists concerning the best method for measuring this construct. This study analyzed leader emotional intelligence scores, measured via skill and ability methodologies, against leader job performance. Two hundred twelve employees from three organizations participated in this study. Scores on the Emotional Intelligence Appraisal, a skill-based assessment, were positively, though not significantly, correlated with scores on the MSCEIT, an ability-based assessment of emotional intelligence. Scores on the MSCEIT did not have a significant relationship with job performance in this study, whereas, scores on the Emotional Intelligence Appraisal had a strong link to leader job performance. The four subcomponents of the Emotional Intelligence Appraisal were examined against job performance. Relationship management was a stronger predictor of leader job performance than the other three subcomponents. Social awareness was the single emotional intelligence skill that did not have a significant link to leader job performance. Factor analyses yielded a two-component model of emotional intelligence encompassing personal and social competence, rather than confirmation of a four-part taxonomy.

  6. Hybrid reactors

    International Nuclear Information System (INIS)

    Moir, R.W.

    1980-01-01

    The rationale for hybrid fusion-fission reactors is the production of fissile fuel for fission reactors. A new class of reactor, the fission-suppressed hybrid promises unusually good safety features as well as the ability to support 25 light-water reactors of the same nuclear power rating, or even more high-conversion-ratio reactors such as the heavy-water type. One 4000-MW nuclear hybrid can produce 7200 kg of 233 U per year. To obtain good economics, injector efficiency times plasma gain (eta/sub i/Q) should be greater than 2, the wall load should be greater than 1 MW.m -2 , and the hybrid should cost less than 6 times the cost of a light-water reactor. Introduction rates for the fission-suppressed hybrid are usually rapid

  7. Strategic Management Model with Lens of Knowledge Management and Competitive Intelligence: A Review Approach

    OpenAIRE

    Shujahat, Muhammad; Hussain, Saddam; Javed, Sammar; Muhammad, Imran Malik; Thursamy, Ramayah; Ali, Junaid

    2017-01-01

    Purpose:\\ud First purpose of this study is to discuss the synergic and separate use of knowledge and\\ud intelligence, via knowledge management and competitive intelligence, in each stage of strategic\\ud management process. Second purpose is to discuss the implications of each stage of strategic\\ud management process for knowledge management and competitive intelligence and vice versa.\\ud Methodology/Design/Approach:\\ud A systematic literature review was performed within timeframe of 2000 to 2...

  8. Space applications of artificial intelligence; 1990 Goddard Conference, Greenbelt, MD, May 1, 2, 1990, Selected Papers

    Science.gov (United States)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  9. [An encounter with extraterrestrial intelligence].

    Science.gov (United States)

    Hisabayashi, Hisashi

    2003-12-01

    It is much easier to find extraterrestrial intelligence than to detect simple organisms living on other planets. However, it is hard to communicate with such intelligence without the mutual understanding of inter-stellar communication protocol. The radio SETI (The Search for Extra-Terrestrial Intelligence) was initiated with the pioneering work of F. Drake in 1960, one year after the historical SETI paper by Cocconi and Morrison. This talk explains that SETI evolves with two bases of science; the understanding of our universe and the development of technology. Since SETI has had strong connection with radio astronomy from its early beginning, the impacts of radio astronomical findings and technological breakthrough can be seen in many aspects of the SETI history. Topics of this talk include the detection of microwave 3 K background radiation in the universe. Interstellar atomic and molecular lines found in radio-wave spectra provide the evidence of pre-biotic chemical evolution in such region. Radio telescope imaging and spectral technique are closely associated with methodology of SETI. Topics of the talk extend to new Allen Telescope Array and projected Square Kilometer Array. Recent optical SETI and the discoveries of extra solar planets are also explained. In the end, the recent understanding of our universe is briefly introduced in terms of matter, dark matter and dark energy. Even our understanding of the universe has been evolutionarily revolved and accumulated after 1960, we must recognize that our universe is still poorly understood and that astronomy and SETI are required to proceed hand in hand.

  10. Computational intelligence in automotive applications

    Energy Technology Data Exchange (ETDEWEB)

    Prokhorov, Danil (ed.) [Toyota Motor Engineering and Manufacturing (TEMA), Ann Arbor, MI (United States). Toyota Technical Center

    2008-07-01

    What is computational intelligence (CI)? Traditionally, CI is understood as a collection of methods from the fields of neural networks (NN), fuzzy logic and evolutionary computation. This edited volume is the first of its kind, suitable to automotive researchers, engineers and students. It provides a representative sample of contemporary CI activities in the area of automotive technology. The volume consists of 13 chapters, including but not limited to these topics: vehicle diagnostics and vehicle system safety, control of vehicular systems, quality control of automotive processes, driver state estimation, safety of pedestrians, intelligent vehicles. All chapters contain overviews of state of the art, and several chapters illustrate their methodologies on examples of real-world systems. About the Editor: Danil Prokhorov began his technical career in St. Petersburg, Russia, after graduating with Honors from Saint Petersburg State University of Aerospace Instrumentation in 1992 (MS in Robotics). He worked as a research engineer in St. Petersburg Institute for Informatics and Automation, one of the institutes of the Russian Academy of Sciences. He came to the US in late 1993 for Ph.D. studies. He became involved in automotive research in 1995 when he was a Summer intern at Ford Scientific Research Lab in Dearborn, MI. Upon his graduation from the EE Department of Texas Tech University, Lubbock, in 1997, he joined Ford to pursue application-driven research on neural networks and other machine learning algorithms. While at Ford, he took part in several production-bound projects including neural network based engine misfire detection. Since 2005 he is with Toyota Technical Center, Ann Arbor, MI, overseeing important mid- and long-term research projects in computational intelligence. (orig.)

  11. MIRD methodology

    International Nuclear Information System (INIS)

    Rojo, Ana M.; Gomez Parada, Ines

    2004-01-01

    The MIRD (Medical Internal Radiation Dose) system was established by the Society of Nuclear Medicine of USA in 1960 to assist the medical community in the estimation of the dose in organs and tissues due to the incorporation of radioactive materials. Since then, 'MIRD Dose Estimate Report' (from the 1 to 12) and 'Pamphlets', of great utility for the dose calculations, were published. The MIRD system was planned essentially for the calculation of doses received by the patients during nuclear medicine diagnostic procedures. The MIRD methodology for the absorbed doses calculations in different tissues is explained

  12. PSA methodology

    Energy Technology Data Exchange (ETDEWEB)

    Magne, L

    1997-12-31

    The purpose of this text is first to ask a certain number of questions on the methods related to PSAs. Notably we will explore the positioning of the French methodological approach - as applied in the EPS 1300{sup 1} and EPS 900{sup 2} PSAs - compared to other approaches (Part One). This reflection leads to more general reflection: what contents, for what PSA? This is why, in Part Two, we will try to offer a framework for definition of the criteria a PSA should satisfy to meet the clearly identified needs. Finally, Part Three will quickly summarize the questions approached in the first two parts, as an introduction to the debate. 15 refs.

  13. PSA methodology

    International Nuclear Information System (INIS)

    Magne, L.

    1996-01-01

    The purpose of this text is first to ask a certain number of questions on the methods related to PSAs. Notably we will explore the positioning of the French methodological approach - as applied in the EPS 1300 1 and EPS 900 2 PSAs - compared to other approaches (Part One). This reflection leads to more general reflection: what contents, for what PSA? This is why, in Part Two, we will try to offer a framework for definition of the criteria a PSA should satisfy to meet the clearly identified needs. Finally, Part Three will quickly summarize the questions approached in the first two parts, as an introduction to the debate. 15 refs

  14. Artificial Intelligence and Information Management

    Science.gov (United States)

    Fukumura, Teruo

    After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

  15. Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects

    National Research Council Canada - National Science Library

    Kemp, Charles C

    2002-01-01

    ... with them. Duo is a human/wearable hybrid that is designed to learn about this important domain of human intelligence by interacting with natural manipulable objects in unconstrained environments...

  16. Intelligent Power Control of DC Microgrid

    DEFF Research Database (Denmark)

    Hajizadeh, Amin; N. Soltani, Mohsen; Norum, Lars

    2017-01-01

    In this paper, an intelligent power management strategy is proposed for hybrid DC microgrid, including wind turbine, fuel cell and battery energy storage. The considered wind turbine has a permanent magnet synchronous generator (PMSG). In the considered structure, wind turbine operates as the main...... condition and fuel cell will not generate excessive power. The proposed control scheme is based on the fuzzy algorithm. All simulations in variant operational modes are performed by MATLAB/Simulink and results show the effectiveness of the proposed control strategy....

  17. Business Intelligence & Analytical Intelligence: hou het zakelijk

    OpenAIRE

    Van Nieuwenhuyse, Dries

    2013-01-01

    Technologie democratiseert, de markt consolideert, terwijl de hoeveelheid data explodeert. Het lijkt een ideale voedingsbodem voor projecten rond business intelligence en analytics. “Hoe minder de technologie het verschil zal maken, hoe prominenter de business aanwezig zal zijn.”

  18. Social Intelligence Design in Ambient Intelligence

    NARCIS (Netherlands)

    Nijholt, Antinus; Stock, Oliviero; Stock, O.; Nishida, T.; Nishida, Toyoaki

    2009-01-01

    This Special Issue of AI and Society contains a selection of papers presented at the 6th Social Intelligence Design Workshop held at ITC-irst, Povo (Trento, Italy) in July 2007. Being the 6th in a series means that there now is a well-established and also a growing research area. The interest in

  19. Spiritual Intelligence, Emotional Intelligence and Auditor’s Performance

    OpenAIRE

    Hanafi, Rustam

    2010-01-01

    The objective of this research was to investigate empirical evidence about influence audi-tor spiritual intelligence on the performance with emotional intelligence as a mediator variable. Linear regression models are developed to examine the hypothesis and path analysis. The de-pendent variable of each model is auditor performance, whereas the independent variable of model 1 is spiritual intelligence, of model 2 are emotional intelligence and spiritual intelligence. The parameters were estima...

  20. Naturalist Intelligence Among the Other Multiple Intelligences [In Bulgarian

    Directory of Open Access Journals (Sweden)

    R. Genkov

    2007-09-01

    Full Text Available The theory of multiple intelligences was presented by Gardner in 1983. The theory was revised later (1999 and among the other intelligences a naturalist intelligence was added. The criteria for distinguishing of the different types of intelligences are considered. While Gardner restricted the analysis of the naturalist intelligence with examples from the living nature only, the present paper considered this problem on wider background including objects and persons of the natural sciences.

  1. Intelligence and treaty ratification

    International Nuclear Information System (INIS)

    Sojka, G.L.

    1990-01-01

    What did the intelligence community and the Intelligence Committee di poorly in regard to the treaty ratification process for arms control? We failed to solve the compartmentalization problem/ This is a second-order problem, and, in general, analysts try to be very open; but there are problems nevertheless. There are very few, if any, people within the intelligence community who are cleared for everything relevant to our monitoring capability emdash short of probably the Director of Central Intelligence and the president emdash and this is a major problem. The formal monitoring estimates are drawn up by individuals who do not have access to all the information to make the monitoring judgements. This paper reports that the intelligence community did not present a formal document on either Soviet incentives of disincentives to cheat or on the possibility of cheating scenarios, and that was a mistake. However, the intelligence community was very responsive in producing those types of estimates, and, ultimately, the evidence behind them in response to questions. Nevertheless, the author thinks the intelligence community would do well to address this issue up front before a treaty is submitted to the Senate for advice and consent

  2. Intelligence for Human-Assistant Planetary Surface Robots

    Science.gov (United States)

    Hirsh, Robert; Graham, Jeffrey; Tyree, Kimberly; Sierhuis, Maarten; Clancey, William J.

    2006-01-01

    The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area.

  3. The Epistemic Status of Intelligence

    DEFF Research Database (Denmark)

    Rønn, Kira Vrist; Høffding, Simon

    2012-01-01

    We argue that the majority of intelligence definitions fail to recognize that the normative epistemic status of intelligence is knowledge and not an inferior alternative. We refute the counter-arguments that intelligence ought not to be seen as knowledge because of 1) its action-oriented scope...... and robustness of claims to intelligence-knowledge can be assessed....

  4. Moral Intelligence in the Schools

    Science.gov (United States)

    Clarken, Rodney H.

    2009-01-01

    Moral intelligence is newer and less studied than the more established cognitive, emotional and social intelligences, but has great potential to improve our understanding of learning and behavior. Moral intelligence refers to the ability to apply ethical principles to personal goals, values and actions. The construct of moral intelligence consists…

  5. Differentiating for Multiple Intelligences: A Study of Students' Understandings through the Use of Aesthetic Representations

    Science.gov (United States)

    Crim, Courtney L.; Kennedy, Kimberley D.; Thornton, Jenifer S.

    2013-01-01

    This article reviews the relevant literature in regard to differentiation, multiple intelligences, and aesthetic representations. Next, it presents the methodology, reports findings, and discusses themes related to the authors' research questions. Finally, it concludes that tapping into students' multiple intelligence strength(s) is an excellent…

  6. Using Students' Knowledge to Generate Individual Feedback: Concept for an Intelligent Educational System on Logistics.

    Science.gov (United States)

    Ziems, Dietrich; Neumann, Gaby

    1997-01-01

    Discusses a methods kit for interactive problem-solving exercises in engineering education as well as a methodology for intelligent evaluation of solutions. The quality of a system teaching logistics thinking can be improved using artificial intelligence. Embedding a rule-based diagnosis module that evaluates the student's knowledge actively…

  7. Basic research on intelligent robotic systems operating in hostile environments: New developments at ORNL

    International Nuclear Information System (INIS)

    Barhen, J.; Babcock, S.M.; Hamel, W.R.; Oblow, E.M.; Saridis, G.N.; deSaussure, G.; Solomon, A.D.; Weisbin, C.R.

    1984-01-01

    Robotics and artificial intelligence research carried out within the Center for Engineering Systems Advanced Research (CESAR) is presented. Activities focus on the development and demonstration of a comprehensive methodological framework for intelligent machines operating in unstructured hostile environments. Areas currently being addressed include mathematical modeling of robot dynamics, real-time control, ''world'' modeling, machine perception and strategy planning

  8. An Intelligent Support System for Energy Resources in the United States.

    Science.gov (United States)

    Rosenberg, S.

    Based on artificial intelligence research, the frame based system for reasoning described in this paper is one of the components of an intelligent decision support system for an information system on petroleum resources and use which is being designed by the Information Methodology Research Project as the first step in the development of a…

  9. The Role of Emotional Intelligence in Mediating the Relationship between Emerging Adulthood and Academic Achievement

    Science.gov (United States)

    Noor, Farukh; Hanafi, Zahyah

    2017-01-01

    Purpose: Academic achievement of students can be fostered and improved if they learn to apply emotional intelligence in their emerging adulthood. The core objective of this research is to test the relationship between emerging adulthood and academic achievement by taking emotional intelligence as a mediator. Methodology: The sample comprises 90…

  10. Competitive Intelligence and Regional Development within the Framework of Indonesian Provincial Autonomy

    Science.gov (United States)

    Dou, Henri; Manullang, Sri Damayanty

    2004-01-01

    Teaching methodologies and uses of competitive intelligence and competitive technical intelligence in countries where the culture and the technological level are very different from the western world cannot be implemented without a cultural understanding of the tacit local knowledge and cultural behavior of people. As an example of…

  11. Advanced intelligence and mechanism approach

    Institute of Scientific and Technical Information of China (English)

    ZHONG Yixin

    2007-01-01

    Advanced intelligence will feature the intelligence research in next 50 years.An understanding of the concept of advanced intelligence as well as its importance will be provided first,and detailed analysis on an approach,the mechanism approach.suitable to the advanced intelligence research will then be flolowed.And the mutual relationship among mechanism approach,traditional approaches existed in artificial intelligence research,and the cognitive informatics will be discussed.It is interesting to discover that mechanism approach is a good one to the Advanced Intelligence research and a tmified form of the existed approaches to artificial intelligence.

  12. Intelligent environmental sensing

    CERN Document Server

    Mukhopadhyay, Subhas

    2015-01-01

    Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

  13. Is Intelligence Artificial?

    OpenAIRE

    Greer, Kieran

    2014-01-01

    Our understanding of intelligence is directed primarily at the level of human beings. This paper attempts to give a more unifying definition that can be applied to the natural world in general. The definition would be used more to verify a degree of intelligence, not to quantify it and might help when making judgements on the matter. A version of an accepted test for AI is then put forward as the 'acid test' for Artificial Intelligence itself. It might be what a free-thinking program or robot...

  14. Multiple Intelligences and quotient spaces

    OpenAIRE

    Malatesta, Mike; Quintana, Yamilet

    2006-01-01

    The Multiple Intelligence Theory (MI) is one of the models that study and describe the cognitive abilities of an individual. In [7] is presented a referential system which allows to identify the Multiple Intelligences of the students of a course and to classify the level of development of such Intelligences. Following this tendency, the purpose of this paper is to describe the model of Multiple Intelligences as a quotient space, and also to study the Multiple Intelligences of an individual in...

  15. Business Intelligence using Software Agents

    OpenAIRE

    Ana-Ramona BOLOGA; Razvan BOLOGA

    2011-01-01

    This paper presents some ideas about business intelligence today and the importance of developing real time business solutions. The authors make an exploration of links between business intelligence and artificial intelligence and focuses specifically on the implementation of software agents-based systems in business intelligence. There are briefly presented some of the few solutions proposed so far that use software agents properties for the benefit of business intelligence. The authors then...

  16. Hybrid composites

    CSIR Research Space (South Africa)

    Jacob John, Maya

    2009-04-01

    Full Text Available mixed short sisal/glass hybrid fibre reinforced low density polyethylene composites was investigated by Kalaprasad et al [25].Chemical surface modifications such as alkali, acetic anhydride, stearic acid, permanganate, maleic anhydride, silane...

  17. Hybrid intermediaries

    OpenAIRE

    Cetorelli, Nicola

    2014-01-01

    I introduce the concept of hybrid intermediaries: financial conglomerates that control a multiplicity of entity types active in the "assembly line" process of modern financial intermediation, a system that has become known as shadow banking. The complex bank holding companies of today are the best example of hybrid intermediaries, but I argue that financial firms from the "nonbank" space can just as easily evolve into conglomerates with similar organizational structure, thus acquiring the cap...

  18. Hybrid Turbine Electric Vehicle

    Science.gov (United States)

    Viterna, Larry A.

    1997-01-01

    Hybrid electric power trains may revolutionize today's ground passenger vehicles by significantly improving fuel economy and decreasing emissions. The NASA Lewis Research Center is working with industry, universities, and Government to develop and demonstrate a hybrid electric vehicle. Our partners include Bowling Green State University, the Cleveland Regional Transit Authority, Lincoln Electric Motor Division, the State of Ohio's Department of Development, and Teledyne Ryan Aeronautical. The vehicle will be a heavy class urban transit bus offering double the fuel economy of today's buses and emissions that are reduced to 1/10th of the Environmental Protection Agency's standards. At the heart of the vehicle's drive train is a natural-gas-fueled engine. Initially, a small automotive engine will be tested as a baseline. This will be followed by the introduction of an advanced gas turbine developed from an aircraft jet engine. The engine turns a high-speed generator, producing electricity. Power from both the generator and an onboard energy storage system is then provided to a variable-speed electric motor attached to the rear drive axle. An intelligent power-control system determines the most efficient operation of the engine and energy storage system.

  19. Engineering general intelligence

    CERN Document Server

    Goertzel, Ben; Geisweiller, Nil

    2014-01-01

    The work outlines a novel conceptual and theoretical framework for understanding Artificial General Intelligence and based on this framework outlines a practical roadmap for the development of AGI with capability at the human level and ultimately beyond.

  20. Understanding US National Intelligence

    DEFF Research Database (Denmark)

    Leander, Anna

    2014-01-01

    In July 2010, the Washington Post (WP) published the results of a project on “Top Secret America” on which twenty investigative journalists had been working for two years. The project drew attention to the change and growth in National Intelligence following 9/11 (Washington Post 2010a......). The initial idea had been to work on intelligence generally, but given that this proved overwhelming, the team narrowed down to focus only on intelligence qualified as “top secret.” Even so, the growth in this intelligence activity is remarkable. This public is returning, or in this case expanding...... at an impressive speed confirming the general contention of this volume. Between 2001 and 2010 the budget had increased by 250 percent, reaching $75 billion (the GDP of the Czech Republic). Thirty-three building complexes for top secret work had been or were under construction in the Washington area; 1...

  1. Engineering general intelligence

    CERN Document Server

    Goertzel, Ben; Geisweiller, Nil

    2014-01-01

    The work outlines a detailed blueprint for the creation of an Artificial General Intelligence system with capability at the human level and ultimately beyond, according to the Cog Prime AGI design and the Open Cog software architecture.

  2. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best, Jr, Richard A

    2007-01-01

    To address the challenges facing the U.S. Intelligence Community in the 21st century, congressional and executive branch initiatives have sought to improve coordination among the different agencies and to encourage better analysis...

  3. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best, Jr, Richard A

    2006-01-01

    To address the challenges facing the U.S. Intelligence Community in the 21st Century, congressional and executive branch initiatives have sought to improve coordination among the different agencies and to encourage better analysis...

  4. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best, Jr, Richard A

    2008-01-01

    To address the challenges facing the U.S. Intelligence Community in the 21st century, congressional and executive branch initiatives have sought to improve coordination among the different agencies and to encourage better analysis...

  5. Intelligent Information Systems Institute

    National Research Council Canada - National Science Library

    Gomes, Carla

    2004-01-01

    ...) at Cornell during the first three years of operation. IISI's mandate is threefold: To perform and stimulate research in computational and data-intensive methods for intelligent decision making systems...

  6. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

    Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

  7. Bibliography: Artificial Intelligence.

    Science.gov (United States)

    Smith, Richard L.

    1986-01-01

    Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

  8. Handbook of Intelligent Vehicles

    CERN Document Server

    2012-01-01

    The Handbook of Intelligent Vehicles provides a complete coverage of the fundamentals, new technologies, and sub-areas essential to the development of intelligent vehicles; it also includes advances made to date, challenges, and future trends. Significant strides in the field have been made to date; however, so far there has been no single book or volume which captures these advances in a comprehensive format, addressing all essential components and subspecialties of intelligent vehicles, as this book does. Since the intended users are engineering practitioners, as well as researchers and graduate students, the book chapters do not only cover fundamentals, methods, and algorithms but also include how software/hardware are implemented, and demonstrate the advances along with their present challenges. Research at both component and systems levels are required to advance the functionality of intelligent vehicles. This volume covers both of these aspects in addition to the fundamentals listed above.

  9. Genes, evolution and intelligence.

    Science.gov (United States)

    Bouchard, Thomas J

    2014-11-01

    I argue that the g factor meets the fundamental criteria of a scientific construct more fully than any other conception of intelligence. I briefly discuss the evidence regarding the relationship of brain size to intelligence. A review of a large body of evidence demonstrates that there is a g factor in a wide range of species and that, in the species studied, it relates to brain size and is heritable. These findings suggest that many species have evolved a general-purpose mechanism (a general biological intelligence) for dealing with the environments in which they evolved. In spite of numerous studies with considerable statistical power, we know of very few genes that influence g and the effects are very small. Nevertheless, g appears to be highly polygenic. Given the complexity of the human brain, it is not surprising that that one of its primary faculties-intelligence-is best explained by the near infinitesimal model of quantitative genetics.

  10. Modelling intelligent behavior

    Science.gov (United States)

    Green, H. S.; Triffet, T.

    1993-01-01

    An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

  11. Emotional Intelligence: Requiring Attention

    Directory of Open Access Journals (Sweden)

    Monica Tudor

    2016-01-01

    Full Text Available This article aims to highlight the need for emotional intelligence. Two methods of measurementare presented in this research, in order to better understand the necessity of a correct result. Theresults of research can lead to recommendations for improving levels of emotional intelligence andare useful for obtaining data to better compare past and present result. The papers presented inthis research are significant for future study of this subject. The first paper presents the evolutionof emotional intelligence in the past two years, more specifically its decrease concerning certaincharacteristics. The second one presents a research on the differences between generations. Thethird one shows a difference in emotional intelligence levels of children from rural versus urbanenvironments and the obstacles that they encounter in their own development.

  12. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best. Jr, Richard A

    2006-01-01

    To address the challenges facing the U.S. Intelligence Community in the 21st century, congressional and executive branch initiatives have sought to improve coordination among the different agencies and to encourage better analysis...

  13. Towards Intelligent Supply Chains

    DEFF Research Database (Denmark)

    Siurdyban, Artur; Møller, Charles

    2012-01-01

    applied to the context of organizational processes can increase the success rate of business operations. The framework is created using a set of theoretical based constructs grounded in a discussion across several streams of research including psychology, pedagogy, artificial intelligence, learning...... of deploying inapt operations leading to deterioration of profits. To address this problem, we propose a unified business process design framework based on the paradigm of intelligence. Intelligence allows humans and human-designed systems cope with environmental volatility, and we argue that its principles......, business process management and supply chain management. It outlines a number of system tasks combined in four integrated management perspectives: build, execute, grow and innovate, put forward as business process design propositions for Intelligent Supply Chains....

  14. Business Intelligence Integrated Solutions

    Directory of Open Access Journals (Sweden)

    Cristescu Marian Pompiliu

    2017-01-01

    Full Text Available This paper shows how businesses make decisions better and faster in terms of customers, partners and operations by turning data into valuable business information. The paper describes how to bring together people's and business intelligence information to achieve successful business strategies. There is the possibility of developing business intelligence projects in large and medium-sized organizations only with the Microsoft product described in the paper, and possible alternatives can be discussed according to the required features.

  15. Artificial intelligence in medicine.

    OpenAIRE

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of ...

  16. Artificial Intelligence Study (AIS).

    Science.gov (United States)

    1987-02-01

    ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

  17. Artificial Intelligence in Astronomy

    Science.gov (United States)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  18. Minimally Naturalistic Artificial Intelligence

    OpenAIRE

    Hansen, Steven Stenberg

    2017-01-01

    The rapid advancement of machine learning techniques has re-energized research into general artificial intelligence. While the idea of domain-agnostic meta-learning is appealing, this emerging field must come to terms with its relationship to human cognition and the statistics and structure of the tasks humans perform. The position of this article is that only by aligning our agents' abilities and environments with those of humans do we stand a chance at developing general artificial intellig...

  19. Artificial intelligence in cardiology

    OpenAIRE

    Bonderman, Diana

    2017-01-01

    Summary Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiol...

  20. Intelligent distributed computing

    CERN Document Server

    Thampi, Sabu

    2015-01-01

    This book contains a selection of refereed and revised papers of the Intelligent Distributed Computing Track originally presented at the third International Symposium on Intelligent Informatics (ISI-2014), September 24-27, 2014, Delhi, India.  The papers selected for this Track cover several Distributed Computing and related topics including Peer-to-Peer Networks, Cloud Computing, Mobile Clouds, Wireless Sensor Networks, and their applications.

  1. The intelligent data recorder

    International Nuclear Information System (INIS)

    Kojima, Mamoru; Hidekuma, Sigeru.

    1985-01-01

    The intelligent data recorder has been developed to data acquisition for a microwave interferometer. The 'RS-232C' which is the standard interface is used for data transmission to the host computer. Then, it's easy to connect with any computer which has general purpose serial port. In this report, the charcteristics of the intelligent data recorder and the way of developing the software are described. (author)

  2. Intelligent Lighting Control System

    OpenAIRE

    García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

    2014-01-01

    This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

  3. Professionalizing Intelligence Analysis

    Directory of Open Access Journals (Sweden)

    James B. Bruce

    2015-09-01

    Full Text Available This article examines the current state of professionalism in national security intelligence analysis in the U.S. Government. Since the introduction of major intelligence reforms directed by the Intelligence Reform and Terrorism Prevention Act (IRTPA in December, 2004, we have seen notable strides in many aspects of intelligence professionalization, including in analysis. But progress is halting, uneven, and by no means permanent. To consolidate its gains, and if it is to continue improving, the U.S. intelligence community (IC should commit itself to accomplishing a new program of further professionalization of analysis to ensure that it will develop an analytic cadre that is fully prepared to deal with the complexities of an emerging multipolar and highly dynamic world that the IC itself is forecasting. Some recent reforms in intelligence analysis can be assessed against established standards of more fully developed professions; these may well fall short of moving the IC closer to the more fully professionalized analytical capability required for producing the kind of analysis needed now by the United States.

  4. GABA predicts visual intelligence.

    Science.gov (United States)

    Cook, Emily; Hammett, Stephen T; Larsson, Jonas

    2016-10-06

    Early psychological researchers proposed a link between intelligence and low-level perceptual performance. It was recently suggested that this link is driven by individual variations in the ability to suppress irrelevant information, evidenced by the observation of strong correlations between perceptual surround suppression and cognitive performance. However, the neural mechanisms underlying such a link remain unclear. A candidate mechanism is neural inhibition by gamma-aminobutyric acid (GABA), but direct experimental support for GABA-mediated inhibition underlying suppression is inconsistent. Here we report evidence consistent with a global suppressive mechanism involving GABA underlying the link between sensory performance and intelligence. We measured visual cortical GABA concentration, visuo-spatial intelligence and visual surround suppression in a group of healthy adults. Levels of GABA were strongly predictive of both intelligence and surround suppression, with higher levels of intelligence associated with higher levels of GABA and stronger surround suppression. These results indicate that GABA-mediated neural inhibition may be a key factor determining cognitive performance and suggests a physiological mechanism linking surround suppression and intelligence. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  5. Alzheimer's disease and intelligence.

    Science.gov (United States)

    Yeo, R A; Arden, R; Jung, R E

    2011-06-01

    A significant body of evidence has accumulated suggesting that individual variation in intellectual ability, whether assessed directly by intelligence tests or indirectly through proxy measures, is related to risk of developing Alzheimer's disease (AD) in later life. Important questions remain unanswered, however, such as the specificity of risk for AD vs. other forms of dementia, and the specific links between premorbid intelligence and development of the neuropathology characteristic of AD. Lower premorbid intelligence has also emerged as a risk factor for greater mortality across myriad health and mental health diagnoses. Genetic covariance contributes importantly to these associations, and pleiotropic genetic effects may impact diverse organ systems through similar processes, including inefficient design and oxidative stress. Through such processes, the genetic underpinnings of intelligence, specifically, mutation load, may also increase the risk of developing AD. We discuss how specific neurobiologic features of relatively lower premorbid intelligence, including reduced metabolic efficiency, may facilitate the development of AD neuropathology. The cognitive reserve hypothesis, the most widely accepted account of the intelligence-AD association, is reviewed in the context of this larger literature.

  6. Organization Effectiveness and Business Intelligence Systems. Literature Review

    Directory of Open Access Journals (Sweden)

    Remigiusz Tunowski

    2015-12-01

    Full Text Available Purpose: To better understand the impact of Business Intelligence systems on organizations’ effectiveness. Methodology: Critical and descriptive literature review. Findings: On the basis of numerous case studies described in literature and pertaining to various types of enterprises, different industries and countries, the paper confirms the positive impact of the implementation of Business Intelligence systems on organizations’ effectiveness. Research implications: The paper provides insights that can fuel future in-depth research aimed at the development of objective methods for measuring the impact of the implementation of Business Intelligence systems on organizational effectiveness, as well as further quantitative research. Practical implications: Results of the majority of studies indicate that the implementation of Business Intelligence systems brings tangible benefits to organizations. The implementation should, however, be appropriate and adequate, adjusted to each organization’s resources. Originality: The paper organizes and systematizes knowledge about the impact of BI implementation on organisation’s efficiency.

  7. Competitive intelligence as an enabler for firm competitiveness: An overview

    Directory of Open Access Journals (Sweden)

    Alexander Maune

    2014-06-01

    Full Text Available The purpose of this article is to provide an overview, from literature, about how competitive intelligence can be an enabler towards a firm’s competitiveness. This overview is done under the background of intense global competition that firms are currently experiencing. This paper used a qualitative content analysis as a data collection methodology on all identified journal articles on competitive intelligence and firm competitiveness. To identify relevant literature, academic databases and search engines were used. Moreover, a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. To ensure reliability and trustworthiness, peer-reviewed journal articles and triangulation were used. The paper found that competitive intelligence is an important enabler of firm competitiveness. The findings from this paper will assist business managers to understand and improve their outlook of competitive intelligence as an enabler of firm competitiveness and will be of great academic value.

  8. Theoretical concepts about "Intelligence" - practices and standards in democratic societies

    Directory of Open Access Journals (Sweden)

    Mr.Sc. Bahri Gashi

    2013-06-01

    Full Text Available My thesis consists of theoretical analysis on the need for recognition of academic concepts to shape and design research field intelligence community activity, careful analysis of the terms and concepts that are strongly linked to intelligence work methodology, theoretical aspects description given practice best to regulate this specific area in our academic studies, has made the study to take proper shape with bold shades of comparative empirical analysis. My study aims to summarize, to analyze existing approaches and break the "taboo theories," floats mysteriously present new knowledge, summed up in this multidisciplinary field study, now theories only considering the nature of scientific thought for recognition theoretical concepts and legal regulation best practice intelligence services in democratic societies. emocratic societies. Treatment of this complex matter such as "intelligent services submission principle" of democracy is very difficult. Is between the concept of democracy is to be open and transparent, and intelligent service logic in the concept is to be closed and secret. Generally in "strategic studies and Peace” security for the creation of "security system" argued by the authors Buzan and Herring. Concept Intelligent based on the theory: "The essence of intelligence is the adequate response to a stimulus." Is the essence of this analysis?

  9. Life system modeling and intelligent computing. Pt. I. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Li, Kang; Irwin, George W. (eds.) [Belfast Queen' s Univ. (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Fei, Minrui; Jia, Li [Shanghai Univ. (China). School of Mechatronical Engineering and Automation

    2010-07-01

    This book is part I of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 55 papers in this volume are organized in topical sections on intelligent modeling, monitoring, and control of complex nonlinear systems; autonomy-oriented computing and intelligent agents; advanced theory and methodology in fuzzy systems and soft computing; computational intelligence in utilization of clean and renewable energy resources; intelligent modeling, control and supervision for energy saving and pollution reduction; intelligent methods in developing vehicles, engines and equipments; computational methods and intelligence in modeling genetic and biochemical networks and regulation. (orig.)

  10. 78 FR 90 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

    Science.gov (United States)

    2013-01-02

    ... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: National Intelligence University, Defense Intelligence... hereby given that a closed meeting of the National Intelligence University Board of Visitors has been...

  11. Testing methodologies

    Energy Technology Data Exchange (ETDEWEB)

    Bender, M.A.

    1990-01-01

    Several methodologies are available for screening human populations for exposure to ionizing radiation. Of these, aberration frequency determined in peripheral blood lymphocytes is the best developed. Individual exposures to large doses can easily be quantitated, and population exposures to occupational levels can be detected. However, determination of exposures to the very low doses anticipated from a low-level radioactive waste disposal site is more problematical. Aberrations occur spontaneously, without known cause. Exposure to radiation induces no new or novel types, but only increases their frequency. The limitations of chromosomal aberration dosimetry for detecting low level radiation exposures lie mainly in the statistical signal to noise'' problem, the distribution of aberrations among cells and among individuals, and the possible induction of aberrations by other environmental occupational or medical exposures. However, certain features of the human peripheral lymphocyte-chromosomal aberration system make it useful in screening for certain types of exposures. Future technical developments may make chromosomal aberration dosimetry more useful for low-level radiation exposures. Other methods, measuring gene mutations or even minute changes on the DNA level, while presently less will developed techniques, may eventually become even more practical and sensitive assays for human radiation exposure. 15 refs.

  12. Testing methodologies

    International Nuclear Information System (INIS)

    Bender, M.A.

    1990-01-01

    Several methodologies are available for screening human populations for exposure to ionizing radiation. Of these, aberration frequency determined in peripheral blood lymphocytes is the best developed. Individual exposures to large doses can easily be quantitated, and population exposures to occupational levels can be detected. However, determination of exposures to the very low doses anticipated from a low-level radioactive waste disposal site is more problematical. Aberrations occur spontaneously, without known cause. Exposure to radiation induces no new or novel types, but only increases their frequency. The limitations of chromosomal aberration dosimetry for detecting low level radiation exposures lie mainly in the statistical ''signal to noise'' problem, the distribution of aberrations among cells and among individuals, and the possible induction of aberrations by other environmental occupational or medical exposures. However, certain features of the human peripheral lymphocyte-chromosomal aberration system make it useful in screening for certain types of exposures. Future technical developments may make chromosomal aberration dosimetry more useful for low-level radiation exposures. Other methods, measuring gene mutations or even minute changes on the DNA level, while presently less will developed techniques, may eventually become even more practical and sensitive assays for human radiation exposure. 15 refs

  13. Dynamic vulnerability assessment and intelligent control for sustainable power systems

    CERN Document Server

    Gonzalez-Longatt, Francisco

    2018-01-01

    Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability as essment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protect...

  14. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.

    1993-01-01

    This project was initiated in September 1989 as a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. There were two primary goals of this research project. The first goal was to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz. The second goal was to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-2 steam plant. Described in this Final (Third Annual) Technical Progress Report is the accomplishment of the project's final milestone, an in-plant intelligent control experiment conducted on April 1, 1993. The development of the experiment included: simulation validation, experiment formulation and final programming, procedure development and approval, and experimental results. Other third year developments summarized in this report are: (1) a theoretical foundation for Reconfigurable Hybrid Supervisory Control, (2) a steam plant diagnostic system, (3) control console design tools and (4) other advanced and intelligent control

  15. Emotional Intelligence Research within Human Resource Development Scholarship

    Science.gov (United States)

    Farnia, Forouzan; Nafukho, Fredrick Muyia

    2016-01-01

    Purpose: The purpose of this study is to review and synthesize pertinent emotional intelligence (EI) research within the human resource development (HRD) scholarship. Design/methodology/approach: An integrative review of literature was conducted and multiple electronic databases were searched to find the relevant resources. Using the content…

  16. Application of artificial intelligence in load frequency control of ...

    African Journals Online (AJOL)

    This paper presents the use of artificial intelligence to study the load frequency control of interconnected power system. In the proposed scheme, a control methodology is developed using Artificial Neural Network (ANN) and Fuzzy Logic controller (FLC) for interconnected hydro-thermal power system. The control strategies ...

  17. Structural Identification and Comparison of Intelligent Mobile Learning Environment

    Science.gov (United States)

    Upadhyay, Nitin; Agarwal, Vishnu Prakash

    2007-01-01

    This paper proposes a methodology using graph theory, matrix algebra and permanent function to compare different architecture (structure) design of intelligent mobile learning environment. The current work deals with the development/selection of optimum architecture (structural) model of iMLE. This can be done using the criterion as discussed in…

  18. Using Appreciative Intelligence for Ice-Breaking: A New Design

    Science.gov (United States)

    Verma, Neena; Pathak, Anil Anand

    2011-01-01

    Purpose: The purpose of this paper is to highlight the importance of applying appreciative intelligence and appreciative inquiry concepts to design a possibly new model of ice-breaking, which is strengths-based and very often used in any training in general and team building training in particular. Design/methodology/approach: The design has…

  19. Competing intelligent search agents in global optimization

    Energy Technology Data Exchange (ETDEWEB)

    Streltsov, S.; Vakili, P. [Boston Univ., MA (United States); Muchnik, I. [Rutgers Univ., Piscataway, NJ (United States)

    1996-12-31

    In this paper we present a new search methodology that we view as a development of intelligent agent approach to the analysis of complex system. The main idea is to consider search process as a competition mechanism between concurrent adaptive intelligent agents. Agents cooperate in achieving a common search goal and at the same time compete with each other for computational resources. We propose a statistical selection approach to resource allocation between agents that leads to simple and efficient on average index allocation policies. We use global optimization as the most general setting that encompasses many types of search problems, and show how proposed selection policies can be used to improve and combine various global optimization methods.

  20. Intelligent decision technology support in practice

    CERN Document Server

    Neves-Silva, Rui; Jain, Lakhmi; Phillips-Wren, Gloria; Watada, Junzo; Howlett, Robert

    2016-01-01

    This book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications.  Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative techniq...