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Sample records for hybrid intelligent methodology

  1. A Hybrid Intelligent Multisensor Positioning Methodology for Reliable Vehicle Navigation

    Directory of Open Access Journals (Sweden)

    Xu Li

    2015-01-01

    Full Text Available With the rapid development of intelligent transportation systems worldwide, it becomes more important to realize accurate and reliable vehicle positioning in various environments whether GPS is available or not. This paper proposes a hybrid intelligent multisensor positioning methodology fusing the information from low-cost sensors including GPS, MEMS-based strapdown inertial navigation system (SINS and electronic compass, and velocity constraint, which can achieve a significant performance improvement over the integration scheme only including GPS and MEMS-based SINS. First, the filter model of SINS aided by multiple sensors is presented in detail and then an improved Kalman filter with sequential measurement-update processing is developed to realize the filtering fusion. Further, a least square support vector machine- (LS SVM- based intelligent module is designed and augmented with the improved KF to constitute the hybrid positioning system. In case of GPS outages, the LS SVM-based intelligent module trained recently is used to predict the position error to achieve more accurate positioning performance. Finally, the proposed hybrid positioning method is evaluated and compared with traditional methods through real field test data. The experimental results validate the feasibility and effectiveness of the proposed method.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. Air quality estimation by computational intelligence methodologies

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    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

  7. 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

  8. 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...

  9. 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…

  10. 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.  

  11. 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.

  12. Hybrid Intelligent Control for Submarine Stabilization

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    Minghui Wang

    2013-05-01

    Full Text Available 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.

  13. Hybrid Intelligent Control for Submarine Stabilization

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    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.

  14. A Hybrid Intelligent Algorithm for Optimal Birandom Portfolio Selection Problems

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    Qi Li

    2014-01-01

    Full Text Available Birandom portfolio selection problems have been well developed and widely applied in recent years. To solve these problems better, this paper designs a new hybrid intelligent algorithm which combines the improved LGMS-FOA algorithm with birandom simulation. Since all the existing algorithms solving these problems are based on genetic algorithm and birandom simulation, some comparisons between the new hybrid intelligent algorithm and the existing algorithms are given in terms of numerical experiments, which demonstrate that the new hybrid intelligent algorithm is more effective and precise when the numbers of the objective function computations are the same.

  15. Intelligent Control Scheme of Engineering Machinery of Cluster Hybrid System

    Institute of Scientific and Technical Information of China (English)

    GAO Qiang; WANG Hongli

    2005-01-01

    In a hybrid system, the subsystems with discrete dynamics play a central role in a hybrid system. In the course of engineering machinery of cluster construction, the discrete control law is hard to obtain because the construction environment is complex and there exist many affecting factors. In this paper, hierarchically intelligent control, expert control and fuzzy control are introduced into the discrete subsystems of engineering machinery of cluster hybrid system, so as to rebuild the hybrid system and make the discrete control law easily and effectively obtained. The structures, reasoning mechanism and arithmetic of intelligent control are replanted to discrete dynamic, conti-nuous process and the interface of the hybrid system. The structures of three types of intelligent hybrid system are presented and the human experiences summarized from engineering machinery of cluster are taken into account.

  16. 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.  .

  17. DESIGNING A HYBRID INTELLIGENT MINING SYSTEM FOR CREDIT RISK EVALUATION

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In this study,a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis.In the proposed hybrid intelligent system,support vector machines are used as a tool to extract typical features and filter its noise,which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines.Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets.Therefore,the proposed hybrid intelligent system overcomes the diffi-culty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches.In addition,the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.

  18. Intelligent CAD Methodology Research of Adaptive Modeling

    Institute of Scientific and Technical Information of China (English)

    ZHANG Weibo; LI Jun; YAN Jianrong

    2006-01-01

    The key to carry out ICAD technology is to establish the knowledge-based and wide rang of domains-covered product model. This paper put out a knowledge-based methodology of adaptive modeling. It is under the Ontology mind, using the Object-Oriented technology and being a knowledge-based model framework. It involves the diverse domains in product design and realizes the multi-domain modeling, embedding the relative information including standards, regulars and expert experience. To test the feasibility of the methodology, the research bonds of the automotive diaphragm spring clutch design and an adaptive clutch design model is established, using the knowledge-based modeling language-AML.

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

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    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.

  20. Recent advances on hybrid approaches for designing intelligent systems

    CERN Document Server

    Melin, Patricia; Pedrycz, Witold; Kacprzyk, Janusz

    2014-01-01

    This book describes recent advances on hybrid intelligent systems using soft computing techniques for diverse areas of application, such as intelligent control and robotics, pattern recognition, time series prediction and optimization 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 a group of papers around a similar subject. The first part consists of papers with the main theme of type-2 fuzzy logic, which basically consists of papers that propose new models and applications for type-2 fuzzy systems. The second part contains papers with the main theme of bio-inspired optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application. The third part contains pape...

  1. Credit Scoring Model Hybridizing Artificial Intelligence with Logistic Regression

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    Han Lu

    2013-01-01

    Full Text Available Today the most commonly used techniques for credit scoring are artificial intelligence and statistics. In this paper, we started a new way to use these two kinds of models. Through logistic regression filters the variables with a high degree of correlation, artificial intelligence models reduce complexity and accelerate convergence, while these models hybridizing logistic regression have better explanations in statistically significance, thus improve the effect of artificial intelligence models. With experiments on German data set, we find an interesting phenomenon defined as ‘Dimensional interference’ with support vector machine and from cross validation it can be seen that the new method gives a lot of help with credit scoring.

  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. Engineering Design Optimization Based on Intelligent Response Surface Methodology

    Institute of Scientific and Technical Information of China (English)

    SONG Guo-hui; WU Yu; LI Cong-xin

    2008-01-01

    An intelligent response surface methodology (IRSM) was proposed to achieve the most competitivemetal forming products, in which artificial intelligence technologies are introduced into the optimization process.It is used as simple and inexpensive replacement for computationally expensive simulation model. In IRSM,the optimal design space can be reduced greatly without any prior information about function distribution.Also, by identifying the approximation error region, new design points can be supplemented correspondingly toimprove the response surface model effectively. The procedure is iterated until the accuracy reaches the desiredthreshold value. Thus, the global optimization can be performed based on this substitute model. Finally, wepresent an optimization design example about roll forming of a "U" channel product.

  4. 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.

  5. A NEW HYBRID ALGORITHM FOR BUSINESS INTELLIGENCE RECOMMENDER SYSTEM

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    P.Prabhu

    2014-03-01

    Full Text Available Business Intelligence is a set of methods, process and technologies that transform raw data into meaningful and useful information. Recommender system is one of business intelligence system that is used to obtain knowledge to the active user for better decision making. Recommender systems apply data mining techniques to the problem of making personalized recommendations for information. Due to the growth in the number of information and the users in recent years offers challenges in recommender systems. Collaborative, content, demographic and knowledge-based are four different types of recommendations systems. In this paper, a new hybrid algorithm is proposed for recommender system which combines knowledge based, profile of the users and most frequent item mining technique to obtain intelligence.

  6. Hybrid Systems for Knowledge Representation in Artificial Intelligence

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    Rajeswari P.V N

    2012-11-01

    Full Text Available There are few knowledge representation (KR techniques available for efficiently representing knowledge. However, with the increase in complexity, better methods are needed. Some researchers came up with hybrid mechanisms by combining two or more methods. In an effort to construct an intelligent computer system, a primary consideration is to represent large amounts of knowledge in a way that allows effective use and efficiently organizing information to facilitate making the recommended inferences. There are merits and demerits of combinations, and standardized method of KR is needed. In this paper, various hybrid schemes of KR were explored at length and details presented.

  7. A New Hybrid Methodology for Nonlinear Time Series Forecasting

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    Mehdi Khashei

    2011-01-01

    Full Text Available Artificial neural networks (ANNs are flexible computing frameworks and universal approximators that can be applied to a wide range of forecasting problems with a high degree of accuracy. However, using ANNs to model linear problems have yielded mixed results, and hence; it is not wise to apply them blindly to any type of data. This is the reason that hybrid methodologies combining linear models such as ARIMA and nonlinear models such as ANNs have been proposed in the literature of time series forecasting. Despite of all advantages of the traditional methodologies for combining ARIMA and ANNs, they have some assumptions that will degenerate their performance if the opposite situation occurs. In this paper, a new methodology is proposed in order to combine the ANNs with ARIMA in order to overcome the limitations of traditional hybrid methodologies and yield more general and more accurate hybrid models. Empirical results with Canadian Lynx data set indicate that the proposed methodology can be a more effective way in order to combine linear and nonlinear models together than traditional hybrid methodologies. Therefore, it can be applied as an appropriate alternative methodology for hybridization in time series forecasting field, especially when higher forecasting accuracy is needed.

  8. Artificial Intelligence Methodologies and Their Application to Diabetes.

    Science.gov (United States)

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

    2017-05-01

    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.

  9. Electric and plug-in hybrid vehicles advanced simulation methodologies

    CERN Document Server

    Varga, Bogdan Ovidiu; Moldovanu, Dan; Iclodean, Calin

    2015-01-01

    This book is designed as an interdisciplinary platform for specialists working in electric and plug-in hybrid electric vehicles powertrain design and development, and for scientists who want to get access to information related to electric and hybrid vehicle energy management, efficiency and control. The book presents the methodology of simulation that allows the specialist to evaluate electric and hybrid vehicle powertrain energy flow, efficiency, range and consumption. The mathematics behind each electric and hybrid vehicle component is explained and for each specific vehicle the powertrain

  10. DIAGNOSIS WINDOWS PROBLEMS BASED ON HYBRID INTELLIGENCE SYSTEMS

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    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.

  11. MAKHA—A New Hybrid Swarm Intelligence Global Optimization Algorithm

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    Ahmed M.E. Khalil

    2015-06-01

    Full Text Available The search for efficient and reliable bio-inspired optimization methods continues to be an active topic of research due to the wide application of the developed methods. In this study, we developed a reliable and efficient optimization method via the hybridization of two bio-inspired swarm intelligence optimization algorithms, namely, the Monkey Algorithm (MA and the Krill Herd Algorithm (KHA. The hybridization made use of the efficient steps in each of the two original algorithms and provided a better balance between the exploration/diversification steps and the exploitation/intensification steps. The new hybrid algorithm, MAKHA, was rigorously tested with 27 benchmark problems and its results were compared with the results of the two original algorithms. MAKHA proved to be considerably more reliable and more efficient in tested problems.

  12. 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...

  13. Armentum: a hybrid direct search optimization methodology

    Science.gov (United States)

    Briones, Francisco Zorrilla

    2016-07-01

    Design of experiments (DOE) offers a great deal of benefits to any manufacturing organization, such as characterization of variables and sets the path for the optimization of the levels of these variables (settings) trough the Response surface methodology, leading to process capability improvement, efficiency increase, cost reduction. Unfortunately, the use of these methodologies is very limited due to various situations. Some of these situations involve the investment on production time, materials, personnel, equipment; most of organizations are not willing to invest in these resources or are not capable because of production demands, besides the fact that they will produce non-conformant product (scrap) during the process of experimentation. Other methodologies, in the form of algorithms, may be used to optimize a process. Known as direct search methods, these algorithms search for an optimum on an unknown function, trough the search of the best combination of the levels on the variables considered in the analysis. These methods have a very different application strategy, they search on the best combination of parameters, during the normal production run, calculating the change in the input variables and evaluating the results in small steps until an optimum is reached. These algorithms are very sensible to internal noise (variation of the input variables), among other disadvantages. In this paper it is made a comparison between the classical experimental design and one of these direct search methods, developed by Nelder and Mead (1965), known as the Nelder Mead simplex (NMS), trying to overcome the disadvantages and maximize the advantages of both approaches, trough a proposed combination of the two methodologies.

  14. 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.

  15. A Hybrid Intelligent Method of Predicting Stock Returns

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    Akhter Mohiuddin Rather

    2014-01-01

    Full Text Available This paper proposes a novel method for predicting stock returns by means of a hybrid intelligent model. Initially predictions are obtained by a linear model, and thereby prediction errors are collected and fed into a recurrent neural network which is actually an autoregressive moving reference neural network. Recurrent neural network results in minimized prediction errors because of nonlinear processing and also because of its configuration. These prediction errors are used to obtain final predictions by summation method as well as by multiplication method. The proposed model is thus hybrid of both a linear and a nonlinear model. The model has been tested on stock data obtained from National Stock Exchange of India. The results indicate that the proposed model can be a promising approach in predicting future stock movements.

  16. Hybrid Risk Management Methodology: A Case Study

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    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.

  17. 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.

  18. 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.

  19. 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

  20. 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...

  1. Ground Motion Data Profile of Western Turkey with Intelligent Hybrid Processing

    Science.gov (United States)

    Korkmaz, Kasim A.; Demir, Fuat

    2016-09-01

    The recent earthquakes caused severe damages on the existing buildings. By this motivation, an important amount of research work has been conducted to determine the seismic risk of seismically active regions. For an accurate seismic risk assessment, processing of ground motions would provide an advantage. Using the current technology, it is not possible to precisely predict the future earthquakes. Therefore, most of the current seismic risk assessment methodologies are based on statistical evaluation by using recurrence and magnitude of the earthquakes hit the specified region. Because of the limited number of records on earthquakes, the quality of definitions is questionable. Fuzzy logic algorithm can be used to improve the quality of the definition. In the present study, ground motion data profile of western Turkey is defined using an intelligent hybrid processing. The approach is given in a practical way for an easier and faster calculation. Earthquake data between 1970 and 1999 from western part of Turkey have been used for training. The results are tested and validated with the earthquake data between 2000 and 2015 of the same region. Enough approximation was validated between calculated values and the earthquake data by using the intelligent hybrid processing.

  2. Ground Motion Data Profile of Western Turkey with Intelligent Hybrid Processing

    Science.gov (United States)

    Korkmaz, Kasim A.; Demir, Fuat

    2017-01-01

    The recent earthquakes caused severe damages on the existing buildings. By this motivation, an important amount of research work has been conducted to determine the seismic risk of seismically active regions. For an accurate seismic risk assessment, processing of ground motions would provide an advantage. Using the current technology, it is not possible to precisely predict the future earthquakes. Therefore, most of the current seismic risk assessment methodologies are based on statistical evaluation by using recurrence and magnitude of the earthquakes hit the specified region. Because of the limited number of records on earthquakes, the quality of definitions is questionable. Fuzzy logic algorithm can be used to improve the quality of the definition. In the present study, ground motion data profile of western Turkey is defined using an intelligent hybrid processing. The approach is given in a practical way for an easier and faster calculation. Earthquake data between 1970 and 1999 from western part of Turkey have been used for training. The results are tested and validated with the earthquake data between 2000 and 2015 of the same region. Enough approximation was validated between calculated values and the earthquake data by using the intelligent hybrid processing.

  3. 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.

  4. 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..

  5. 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

  6. 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 methodolo

  7. 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.

  8. 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.

  9. A SAA-based Novel Hybrid Intelligent Evolutionary Algorithm for Job Shop Scheduling Problem

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Through systematic analysis and comparison of the common features of SAA, ES and traditional LS (local search) algorithm, a new hybrid strategy of mixing SA, ES with LS, namely HIEA (Hybrid Intelligent Evolutionary Algorithm), is proposed in this paper. Viewed as a whole, the hybrid strategy is also an intelligent heuristic searching procedure. But it has some characteristics such as generality, robustness, etc., because it synthesizes advantages of SA, ES and LS, while the shortages of the three methods are overcome. This paper applies Markov chain theory to describe the hybrid strategy mathematically, and proves that the algorithm possesses the global asymptotical convergence and analyzes the performance of HIEA.

  10. 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 for p...

  11. APPLICATION OF INTEGRATED INTELLIGENT METHODOLOGY TO PREDICT STABILITY AND SUPPORTING DECISION IN UNDERGROUND DRIFT

    Institute of Scientific and Technical Information of China (English)

    Lai Xingping; Wu Yongping; Zhang Bingchuan; Cai Meifeng

    2000-01-01

    The present study shows that naturally the enormous engineering structure interaction with medium material, geometry or non-linearity hazardous simulation experiment, response analysis and computing theory have been regarded as a high-level question in the architecture, bridge, tunnel, hydraulic, etc engineering fields.Approaches an integrated intelligent methodology to predict stability and supporting decision in underground drift based on neural network modelling on coal-rock mechanical problem is proposed.By the terms of the non-linearity numerical simulation, this paper develops integrated intelligent methodology to research on the structure hazardous response strata soft-rock drifts.

  12. Hybrid intelligent PID control design for PEMFC anode system

    Institute of Scientific and Technical Information of China (English)

    Rui-min WANG; Ying-ying ZHANG; Guang-yi CAO

    2008-01-01

    Control design is important for proton exchange membrane fuel cell (PEMFC) generator. This work researched the anode system of a 60-kW PEMFC generator. Both anode pressure and humidity must he maintained at ideal levels during steady operation. In view of characteristics and requirements of the system, a hybrid intelligent PID controller is designed specifically based on dynamic simulation. A single neuron PI controller is used for anode humidity by adjusting the water injection to the hydrogen cell. Another incremental PID controller, based on the diagonal recurrent neural network (DRNN) dynamic identification, is used to control anode pressure to be more stable and exact by adjusting the hydrogen flow rate. This control strategy can avoid the coupling problem of the PEMFC and achieve a more adaptive ability. Simulation results showed that the control strategy can maintain both anode humidity and pressure at ideal levels regardless of variable load, nonlinear dynamic and coupling characteristics of the system. This work will give some guides for further control design and applications of the total PEMFC generator.

  13. Design Intelligent Model base Online Tuning Methodology for Nonlinear System

    Directory of Open Access Journals (Sweden)

    Ali Roshanzamir

    2014-04-01

    Full Text Available In various dynamic parameters systems that need to be training on-line adaptive control methodology is used. In this paper fuzzy model-base adaptive methodology is used to tune the linear Proportional Integral Derivative (PID controller. The main objectives in any systems are; stability, robust and reliability. However PID controller is used in many applications but it has many challenges to control of continuum robot. To solve these problems nonlinear adaptive methodology based on model base fuzzy logic is used. This research is used to reduce or eliminate the PID controller problems based on model reference fuzzy logic theory to control of flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.

  14. 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…

  15. Joint intelligence operations centers (JIOC) business process model & capabilities evaluation methodology

    OpenAIRE

    Schacher, Gordon; Irvine, Nelson; Hoyt, Roger

    2012-01-01

    A JIOC Business Process Model has been developed for use in evaluating JIOC capabilities. The model is described and depicted through OV5 and organization swim-lane diagrams. Individual intelligence activities diagrams are included. A JIOC evaluation methodology is described.

  16. 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.

  17. 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.

  18. 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.

  19. Organic/inorganic hybrid materials: challenges for ab initio methodology.

    Science.gov (United States)

    Draxl, Claudia; Nabok, Dmitrii; Hannewald, Karsten

    2014-11-18

    CONSPECTUS: Organic/inorganic hybrid structures are most exciting since one can expect new properties that are absent in either of their building blocks. They open new perspectives toward the design and tailoring of materials with desired features and functions. Prerequisite for real progress is, however, the in-depth understanding of what happens on the atomic and electronic scale. In this respect, hybrid materials pose a challenge for electronic-structure theory. Methods that proved useful for describing one side may not be applicable for the other one, and they are likely to fail for the interfaces. In this Account, we address the question to what extent we can quantitatively describe hybrid materials and where we even miss a qualitative description. We note that we are dealing with extended systems and thus adopt a solid-state approach. Therefore, density-functional theory (DFT) and many-body perturbation theory (MBPT), the GW approach for charged and the Bethe-Salpeter equation for neutral excitations, are our methods of choice. We give a brief summary of the used methodology, focusing on those aspects where problems can be expected when materials of different character meet at an interface. These issues are then taken up when discussing hybrid materials. We argue when and why, for example, standard DFT may fall short when it comes to the electronic structure of organic/metal interfaces or where the framework of MBPT can or must take over. Selected examples of organic/inorganic interfaces, structural properties, electronic bands, optical excitation spectra, and charge-transport properties as obtained from DFT and MBPT highlight which properties can be reliably computed for such materials. The crucial role of van der Waals forces is shown for sexiphenyl films, where the subtle interplay between intermolecular and molecule-substrate interactions is decisive for growth and morphologies. With a PTCDA monolayer on metal surfaces we discuss the performance of DFT in

  20. 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…

  1. An Intelligent Response Surface Methodology for Modeling of Domain Level Constraints

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    An effective modeling method of domain level constraints in the constraint network for concurrent engineering (CE) was developed. The domain level constraints were analyzed and the framework of modeling of domain level constraints based on simulation and approximate technology was given. An intelligent response surface methodology (IRSM) was proposed, in which artificial intelligence technologies are introduced into the optimization process. The design of crank and connecting rod in the V6 engine as example was given to show the validity of the modeling method.

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    A. Hajizadeh

    2013-12-01

    Full Text Available 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 power system is simulated in MATLAB/ SIMIULINK environment and different operating conditions have been considered to evaluate the response of power management strategy.

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

    Directory of Open Access Journals (Sweden)

    Salvador Lopez

    Full Text Available According to Howard Garner, 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 a different type of intelligence from students registered in traditional face-to-face courses. At the beginning of the fall semester of 2011, a group of 128 students from four different courses in Business Statistics completed a survey to determine their types of intelligence. Our findings reveal surprising results with important consequences in terms of teaching styles that better fit our students.

  5. 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.

  6. 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.

  7. 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.

  8. High Precision Motion Control of Hybrid Five-Bar Mechanism with an Intelligent Control

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ke; WANG Sheng-ze

    2009-01-01

    Hybrid mechanism is a new type of planar controllable mechanism. Position control accuracy of system determines the output acctracy of the mechanism In order to achieve the desired high accuracy, nonlinear factors as friction must be accurately compensated in the real-time servo control algarithm. In this paper, the model of a hybrid flve-bar mechanism is introduced In terms of the characteristics of the hybrid mechanism, a hybrid intelligent control algorithm based on proportional-integral-derivative(PID) control and cerebellar model articulation control techniques was presented and used to perform control of hybrid five-bar mechanism for the first time. The simulation results show that the hybrid control method can improve the control effect remarkably, compared with the traditional PID control strategy.

  9. ?HY-CHANGE?: AN HYBRID METHODOLOGY FOR CONTINUOUS PERFORMANCE IMPROVEMENT OF MANUFACTURING PROCESSES

    OpenAIRE

    Dassisti, Michele

    2010-01-01

    Abstract An hybrid methodology based on the joint recourse of Business Process An hybrid methodology for Continuous Performance Improvement (CPI) is presented, basically funded on the joint recourse of Business Process Reengineering (BPR) and Continuous Quality Improvement (CQI) principles and tools. The methodology (called HY-CHANGE) is conceived as a logical and technical support to the decision maker. It results in a number of recursive phases, where the rational and synchronous...

  10. Order to Disorder Transitions in Hybrid Intelligent Systems: a Hatch to the Interactions of Nations -Governments

    CERN Document Server

    Owladeghaffari, Hamed

    2008-01-01

    In this study, under general frame of MAny Connected Intelligent Particles Systems (MACIPS), we reproduce two new simple subsets of such intelligent complex network, namely hybrid intelligent systems, involved a few prominent intelligent computing and approximate reasoning methods: self organizing feature map (SOM), Neuro-Fuzzy Inference System and Rough Set Theory (RST). Over this, we show how our algorithms can be construed as a linkage of government-society interaction, where government catches various fashions of behavior: solid (absolute) or flexible. So, transition of such society, by changing of connectivity parameters (noise) from order to disorder is inferred. Add to this, one may find an indirect mapping among finical systems and eventual market fluctuations with MACIPS.

  11. 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.

  12. Development of Intelligent Suits for Disuse Atrophy of Musculoskeletal System Using Hybrid Exercise Method

    Science.gov (United States)

    Shiba, Naoto; Yoshimitsu, Kazuhiro; Matsugaki, Tohru; Narita, Arata; Maeda, Takashi; Inada, Tomohisa; Tagawa, Yoshihiko; Numada, Kiyoshi; Nishi, Tetsuya

    We developed ‘Hybrid exercise’ method that was designed to maintain the musculoskeletal system by using electrically stimulated antagonist muscles to resist volitional contraction of agonist muscles. This approach also produces a minimum of inertial reaction forces and has the advantage that it may minimize the need for external stabilization that is currently necessary during exercise in a weightlessness environment. The purpose of this study was to develop the intelligent suits with virtual reality (VR) system that had function of preventing disuse atrophy of musculoskeletal system using hybrid exercise system. Installing of the hybrid exercise system to the subject became easy by the intelligent suits. VR system realized the sense of sight by computer graphics animation synchronized with subjects' motion, and sense of force induced by electrical stimulation. By using VR system, the management of the exercise accomplishment degree was enabled easily because the device could record the exercise history. Intelligent suits with VR hybrid exercise system might become one of the useful countermeasures for the disuse musculoskeletal system in the space.

  13. 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.

  14. Development of Hydrophobic Coatings for Water-Repellent Surfaces Using Hybrid Methodology

    Science.gov (United States)

    2014-04-01

    windows, optical components, protective eyewear, and clothing, this type of surface is desired for the material to be soil repellent and water ...Development of Hydrophobic Coatings for Water - Repellent Surfaces Using Hybrid Methodology by Amanda S. Weerasooriya, Jacqueline Yim, Andres A...Proving Ground, MD 21005-5069 ARL-TR-6898 April 2014 Development of Hydrophobic Coatings for Water - Repellent Surfaces Using Hybrid

  15. A new hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer

    Science.gov (United States)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    This paper describes new and recent advances in the development of a hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer problems. The transfinite element methodology, while retaining the modeling versatility of contemporary finite element formulations, is based on application of transform techniques in conjunction with classical Galerkin schemes and is a hybrid approach. The purpose of this paper is to provide a viable hybrid computational methodology for applicability to general transient thermal analysis. Highlights and features of the methodology are described and developed via generalized formulations and applications to several test problems. The proposed transfinite element methodology successfully provides a viable computational approach and numerical test problems validate the proposed developments for conduction/convection/radiation thermal analysis.

  16. A new hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer

    Science.gov (United States)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    This paper describes new and recent advances in the development of a hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer problems. The transfinite element methodology, while retaining the modeling versatility of contemporary finite element formulations, is based on application of transform techniques in conjunction with classical Galerkin schemes and is a hybrid approach. The purpose of this paper is to provide a viable hybrid computational methodology for applicability to general transient thermal analysis. Highlights and features of the methodology are described and developed via generalized formulations and applications to several test problems. The proposed transfinite element methodology successfully provides a viable computational approach and numerical test problems validate the proposed developments for conduction/convection/radiation thermal analysis.

  17. Intelligent Scheduling of Public Traffic Vehicles Based on a Hybrid Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHANG Feizhou; CAO Xuejun; YANG Dongkai

    2008-01-01

    A genetic algorithm (GA) and a hybrid genetic algorithm (HGA) were used for optimal scheduling of public vehicles based on their actual operational environments.The performance for three kinds of vehicular levels were compared using one-point and two-point crossover operations.The vehicle scheduling times are improved by the intelligent characteristics of the GA.The HGA,which integrates the genetic algorithm with a tabu search,further improves the convergence performance and the optimization by avoiding the premature convergence of the GA.The results show that intelligent scheduling of public vehicles based on the HGA overcomes the shortcomings of traditional scheduling methods.The vehicle operation management efficiency is improved by this essential technology for intelligent scheduling of public vehicles.

  18. Intelligent Hybrid Cluster Based Classification Algorithm for Social Network Analysis

    Directory of Open Access Journals (Sweden)

    S. Muthurajkumar

    2014-05-01

    Full Text Available In this paper, we propose an hybrid clustering based classification algorithm based on mean approach to effectively classify to mine the ordered sequences (paths from weblog data in order to perform social network analysis. In the system proposed in this work for social pattern analysis, the sequences of human activities are typically analyzed by switching behaviors, which are likely to produce overlapping clusters. In this proposed system, a robust Modified Boosting algorithm is proposed to hybrid clustering based classification for clustering the data. This work is useful to provide connection between the aggregated features from the network data and traditional indices used in social network analysis. Experimental results show that the proposed algorithm improves the decision results from data clustering when combined with the proposed classification algorithm and hence it is proved that of provides better classification accuracy when tested with Weblog dataset. In addition, this algorithm improves the predictive performance especially for multiclass datasets which can increases the accuracy.

  19. Application of Computational Intelligence in Order to Develop Hybrid Orbit Propagation Methods

    Directory of Open Access Journals (Sweden)

    Iván Pérez

    2013-01-01

    Full Text Available We present a new approach in astrodynamics and celestial mechanics fields, called hybrid perturbation theory. A hybrid perturbation theory combines an integrating technique, general perturbation theory or special perturbation theory or semianalytical method, with a forecasting technique, statistical time series model or computational intelligence method. This combination permits an increase in the accuracy of the integrating technique, through the modeling of higher-order terms and other external forces not considered in the integrating technique. In this paper, neural networks have been used as time series forecasters in order to help two economic general perturbation theories describe the motion of an orbiter only perturbed by the Earth’s oblateness.

  20. An intelligent hybrid behavior coordination system for an autonomous mobile robot

    Science.gov (United States)

    Luo, Chaomin; Krishnan, Mohan; Paulik, Mark; Fallouh, Samer

    2013-12-01

    In this paper, development of a low-cost PID controller with an intelligent behavior coordination system for an autonomous mobile robot is described that is equipped with IR sensors, ultrasonic sensors, regulator, and RC filters on the robot platform based on HCS12 microcontroller and embedded systems. A novel hybrid PID controller and behavior coordination system is developed for wall-following navigation and obstacle avoidance of an autonomous mobile robot. Adaptive control used in this robot is a hybrid PID algorithm associated with template and behavior coordination models. Software development contains motor control, behavior coordination intelligent system and sensor fusion. In addition, the module-based programming technique is adopted to improve the efficiency of integrating the hybrid PID and template as well as behavior coordination model algorithms. The hybrid model is developed to synthesize PID control algorithms, template and behavior coordination technique for wall-following navigation with obstacle avoidance systems. The motor control, obstacle avoidance, and wall-following navigation algorithms are developed to propel and steer the autonomous mobile robot. Experiments validate how this PID controller and behavior coordination system directs an autonomous mobile robot to perform wall-following navigation with obstacle avoidance. Hardware configuration and module-based technique are described in this paper. Experimental results demonstrate that the robot is successfully capable of being guided by the hybrid PID controller and behavior coordination system for wall-following navigation with obstacle avoidance.

  1. A New Hybrid Fuzzy Intelligent Filter for Medical Image Noise Reduction

    OpenAIRE

    Somaye Aliakbari Dehkordi; Mohammad Ghasemzadeh; Vali Derhami

    2014-01-01

    Medical imaging comprises different imaging modalities and processes to image human body for diagnostic and treatment purposes and, therefore has an important role in the improvement of public health in all population groups. In this paper, we present an intelligent hybrid noise reduction filter which is based on Neuro-Fuzzy systems. It is especially beneficial in medical image noise reduction. First stage we feed the input image into four general noise reduction filters in parallel. These ge...

  2. Hybrid Computation Model for Intelligent System Design by Synergism of Modified EFC with Neural Network

    OpenAIRE

    2015-01-01

    In recent past, it has been seen in many applications that synergism of computational intelligence techniques outperforms over an individual technique. This paper proposes a new hybrid computation model which is a novel synergism of modified evolutionary fuzzy clustering with associated neural networks. It consists of two modules: fuzzy distribution and neural classifier. In first module, mean patterns are distributed into the number of clusters based on the modified evolutionary fuzzy cluste...

  3. 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.

  4. 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…

  5. 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…

  6. 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.

  7. Intelligent uninterruptible power supply system with back-up fuel cell/battery hybrid power source

    Science.gov (United States)

    Zhan, Yuedong; Guo, Youguang; Zhu, Jianguo; Wang, Hua

    2008-05-01

    This paper presents the development of an intelligent uninterruptible power supply (UPS) system with a hybrid power source that comprises a proton-exchange membrane fuel cell (PEMFC) and a battery. Attention is focused on the architecture of the UPS hybrid system and the data acquisition and control of the PEMFC. Specifically, the hybrid UPS system consists of a low-cost 60-cell 300 W PEMFC stack, a 3-cell lead-acid battery, an active power factor correction ac-dc rectifier, a half-bridge dc-ac inverter, a dc-dc converter, an ac-dc charger and their control units based on a digital signal processor TMS320F240, other integrated circuit chips, and a simple network management protocol adapter. Experimental tests and theoretical studies are conducted. First, the major parameters of the PEMFC are experimentally obtained and evaluated. Then an intelligent control strategy for the PEMFC stack is proposed and implemented. Finally, the performance of the hybrid UPS system is measured and analyzed.

  8. 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.

  9. Online Intelligent Controllers for an Enzyme Recovery Plant: Design Methodology and Performance

    Directory of Open Access Journals (Sweden)

    M. S. Leite

    2010-01-01

    Full Text Available This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4 is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS, based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE, lower power consumption, and better recovery of enzyme activity.

  10. Fractional snow cover mapping from MODIS data using wavelet-artificial intelligence hybrid models

    Science.gov (United States)

    Moosavi, Vahid; Malekinezhad, Hossein; Shirmohammadi, Bagher

    2014-04-01

    This study was carried out to evaluate the wavelet-artificial intelligence hybrid models to produce fractional snow cover maps. At first, cloud cover was removed from MODIS data and cloud free images were produced. SVM-based binary classified ETM+ imagery were then used as reference maps in order to obtain train and test data for sub-pixel classification models. ANN and ANFIS-based modeling were performed using raw data (without wavelet-based preprocessing). In the next step, several mother wavelets and levels were used in order to decompose the original data to obtain wavelet coefficients. Then, the decomposed data were used for further modeling processes. ANN, ANFIS, wavelet-ANN and wavelet-ANFIS models were compared to evaluate the effect of wavelet transformation on the ability of artificial intelligence models. It was demonstrated that wavelet transformation as a preprocessing approach can significantly enhance the performance of ANN and ANFIS models. This study indicated an overall accuracy of 92.45% for wavelet-ANFIS model, 86.13% for wavelet-ANN, 72.23% for ANFIS model and 66.78% for ANN model. In fact, hybrid wavelet-artificial intelligence models can extract the characteristics of the original signals (i.e. model inputs) accurately through decomposing the non-stationary and complex signals into several stationary and simpler signals. The positive effect of fuzzification as well as wavelet transformation in the wavelet-ANFIS model was also confirmed.

  11. 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.

  12. 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

  13. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    Science.gov (United States)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.

  14. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    Science.gov (United States)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model. PMID:28120889

  15. 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...... diagnoses. The final result is a short but robust rule based classification scheme, achieving high degree of classification accuracy (exceeding 90% of accuracy for most classes) in a meaningful and user-friendly representation form for the medical expert. The domain of application analyzed through the paper...... is the well-known Pap-Test problem, corresponding to a numerical database, which consists of 450 medical records, 25 diagnostic attributes and 5 different diagnostic classes. Experimental data are divided in two equal parts for the training and testing phase, and 8 mutually dependent rules for diagnosis...

  16. Hybrid intelligent control of combustion process for ore-roasting furnace

    Institute of Scientific and Technical Information of China (English)

    Aijun YAN; Tianyou CHAI; Fenghua WU; Pu WANG

    2008-01-01

    Because of its synthetic and complex characteristics, the combustion process of the shaft ore-roasting furnace is very difficult to control stably. A hybrid intelligent control approach is developed which consists of two systems: one is a cascade fuzzy control system with a temperature soft-sensor, and the other is a ratio control system for air flow with a compensation model for heating gas flow and air-fuel ratio. This approach combined intelligent control, soft-sensing and fault diagnosis with conventional control. It can adjust both the heating gas flow and the air-fuel ratio in real time. By this way, the difficulty of online measurement of the furnace temperature is solved, the fault ratios during combustion process is decreased, the steady control of the furnace temperature is achieved, and the gas consumption is reduced. The successful application in shaft furnaces of a mineral processing plant in China indicates its effectiveness.

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

    Science.gov (United States)

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

    2016-03-01

    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.

  18. Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System

    Directory of Open Access Journals (Sweden)

    Tarık Çakar

    2012-12-01

    Full Text Available This paper considers the problem of scheduling a given number of jobs on a specified number of identical parallel robots with unequal release dates and precedence constraints in order to minimize mean tardiness. This problem is strongly NP-hard. The author proposes a hybrid intelligent solution system, which uses Genetic Algorithms and Simulated Annealing (GA+SA. A genetic algorithm, as is well known, is an efficient tool for the solution of combinatorial optimization problems. Solutions for problems of different scales are found using genetic algorithms, simulated annealing and a Hybrid Intelligent Solution System (HISS. Computational results of empirical experiments show that the Hybrid Intelligent Solution System (HISS is successful with regards to solution quality and computational time.

  19. Hybrid methodology for hourly global radiation forecasting in Mediterranean area

    CERN Document Server

    Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure

    2012-01-01

    The renewable energies prediction and particularly global radiation forecasting is a challenge studied by a growing number of research teams. This paper proposes an original technique to model the insolation time series based on combining Artificial Neural Network (ANN) and Auto-Regressive and Moving Average (ARMA) model. While ANN by its non-linear nature is effective to predict cloudy days, ARMA techniques are more dedicated to sunny days without cloud occurrences. Thus, three hybrids models are suggested: the first proposes simply to use ARMA for 6 months in spring and summer and to use an optimized ANN for the other part of the year; the second model is equivalent to the first but with a seasonal learning; the last model depends on the error occurred the previous hour. These models were used to forecast the hourly global radiation for five places in Mediterranean area. The forecasting performance was compared among several models: the 3 above mentioned models, the best ANN and ARMA for each location. In t...

  20. 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.

  1. 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,…

  2. 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,…

  3. 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)

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Ranganathan Mohanasundaram

    2015-01-01

    Full Text Available 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.

  6. 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

  7. 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.

  8. Ergodynamics in the Reliability of Power Plant Operators and Prospective Hybrid Intelligence Systems.

    Science.gov (United States)

    Venda; Chachko

    1996-01-01

    Based on ergodynamics and the hybrid intelligence theory, an analysis of the nuclear power plant operator's performance is given at the levels of strategies, tactics, and actions. Special attention is paid to the strategies used in the course of severe accidents at nuclear power plants. Data from Ukrainian and Russian power plants and training centres, and from accidents around the world were collected and processed. It is shown that in an emergency it is essential for the human operator to be flexible. This flexibility includes two main training and personal factors: a large set of strategies and tactics the operator manages to use, and quick transformations between the strategies (tactics). It was also found that some emergency tasks are too complicated: They require simultaneous use of different strategies, with time strictly limited by nuclear power plant dynamics. Those tasks cannot be successfully solved by any individual operator. Hybrid intelligence systems involving different specialists should be used in those cases in order to avoid failures in emergency problem solving and macroergonomic organizational design.

  9. Intelligent Energy Management Strategy for a Separated-Axle Parallel Hybrid Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Naser Fallahi

    2014-03-01

    Full Text Available Hybrid electric vehicles (HEV in addition to provide the benefits of electric vehicles could satisfy consumers for some performances of conventional internal combustion engine (ICE vehicles such as acceleration and long range. On this way, suitable energy optimization strategies should be employed to get desired efficiency, less fuel consumption and pollution. One of the favorite and simple configurations of HEVs is parallel type. A student team at University of Kashan, IRAN have designed and manufactured Shaheb 2 hybrid electric vehicle. It is a separated-axle (or Through-to-Road (TTR parallel HEV type based on Pride platform. Employed energy management in Shaheb 2 is on/off strategy and three modes; motor, engine and hybrid have been implemented. This paper investigates the modeling of separated-axle (or TTR parallel type of HEV in ADVISOR software and then evaluates two control strategies for Shaheb 2; on/off strategy and an intelligent control based on fuzzy logic. On this way, maximizing the engine is considered as objective function. The simulation results indicate that the fuzzy strategy leads to less fuel consumption and lower pollution for given UDDS driving cycle rather than on/off strategy for Shaheb 2.

  10. 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.

  11. 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.

  12. Hybrid intelligent system for Sale Forecasting using Delphi and adaptive Fuzzy Back-Propagation Neural Networks

    Directory of Open Access Journals (Sweden)

    Attariuas Hicham

    2012-12-01

    Full Text Available ales forecasting is one of the most crucial issues addressed in business. Control and evaluation of future sales still seem concerned both researchers and policy makers and managers of companies. this research propose an intelligent hybrid sales forecasting system Delphi-FCBPN sales forecast based on Delphi Method, fuzzy clustering and Back-propagation (BP Neural Networks with adaptive learning rate. The proposed model is constructed to integrate expert judgments, using Delphi method, in enhancing the model of FCBPN. Winter’s Exponential Smoothing method will be utilized to take the trend effect into consideration. The data for this search come from an industrial company that manufactures packaging. Analyze of results show that the proposed model outperforms other three different forecasting models in MAPE and RMSE measures.

  13. 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.

  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. Monitoring Technology Proliferation: An Open Source Methodology For Generating Proliferation Intelligence

    Science.gov (United States)

    1993-12-01

    disciplines including robotics , biotechnology, artificial intelligence, directed energy weapons, and super-miniaturization. The development of defense...Air Breathing Propulsion - Aeronautics 10. Machine Intel/ Robotics - Intelligent Processing Equipment - Flexible Couter Integrated Manufacturing 11...ROYAL ORDHAXCZ PLC (UK) SA NARXNE A/B (83R) SNORT BROTHERS (UK) SIMA (PERU) SOCXUTA INDUSTRIALE CARDAUR SIC (SPA) SPERRY GYROSCOPES (USA) TECHICAL

  16. Performance Evaluation of OLSR Using Swarm Intelligence and Hybrid Particle Swarm Optimization Using Gravitational Search Algorithm

    Directory of Open Access Journals (Sweden)

    S. Meenakshi Sundaram

    2014-04-01

    Full Text Available The aim of this research is to evaluate the performance of OLSR using swarm intelligence and HPSO with Gravitational search algorithm to lower the jitter time, data drop and end to end delay and improve the network throughput. Simulation was carried out for multimedia traffic and video streamed network traffic using OPNET Simulator. Routing is exchanging of information from one host to another in a network. Routing forwards packets to destination using an efficient path. Path efficiency is measured through metrics like hop number, traffic and security. Each host node acts as a specialized router in Ad-hoc networks. A table driven proactive routing protocol Optimized Link State Protocol (OLSR has available topology information and routes. OLSR’s efficiency depends on Multipoint relay selection. Various studies were conducted to decrease control traffic overheads through modification of existing OLSR routing protocol and traffic shaping based on packet priority. This study proposes a modification of OLSR using swarm intelligence, Hybrid Particle Swarm Optimization (HPSO using Gravitational Search Algorithm (GSA and evaluation of performance of jitter, end to end delay, data drop and throughput. Simulation was carried out to investigate the proposed method for the network’s multimedia traffic.

  17. 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.

  18. 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.

  19. An Adaptive Hybrid Multi-level Intelligent Intrusion Detection System for Network Security

    Directory of Open Access Journals (Sweden)

    P. Ananthi

    2014-04-01

    Full Text Available Intrusion Detection System (IDS plays a vital factor in providing security to the networks through detecting malicious activities. Due to the extensive advancements in the computer networking, IDS has become an active area of research to determine various types of attacks in the networks. A large number of intrusion detection approaches are available in the literature using several traditional statistical and data mining approaches. Data mining techniques in IDS observed to provide significant results. Data mining approaches for misuse and anomaly-based intrusion detection generally include supervised, unsupervised and outlier approaches. It is important that the efficiency and potential of IDS be updated based on the criteria of new attacks. This study proposes a novel Adaptive Hybrid Multi-level Intelligent IDS (AHMIIDS system which is the combined version of anomaly and misuse detection techniques. The anomaly detection is based on Bayesian Networks and then the misuse detection is performed using Adaptive Neuro Fuzzy Inference System (ANFIS. The outputs of both anomaly detection and misuse detection modules are applied to Decision Table Majority (DTM to perform the final decision making. A rule-base approach is used in this system. It is observed from the results that the proposed AHMIIDS performs better than other conventional hybrid IDS.

  20. Quality of Service Routing in Manet Using a Hybrid Intelligent Algorithm Inspired by Cuckoo Search

    Directory of Open Access Journals (Sweden)

    S. Rajalakshmi

    2015-01-01

    Full Text Available A hybrid computational intelligent algorithm is proposed by integrating the salient features of two different heuristic techniques to solve a multiconstrained Quality of Service Routing (QoSR problem in Mobile Ad Hoc Networks (MANETs is presented. The QoSR is always a tricky problem to determine an optimum route that satisfies variety of necessary constraints in a MANET. The problem is also declared as NP-hard due to the nature of constant topology variation of the MANETs. Thus a solution technique that embarks upon the challenges of the QoSR problem is needed to be underpinned. This paper proposes a hybrid algorithm by modifying the Cuckoo Search Algorithm (CSA with the new position updating mechanism. This updating mechanism is derived from the differential evolution (DE algorithm, where the candidates learn from diversified search regions. Thus the CSA will act as the main search procedure guided by the updating mechanism derived from DE, called tuned CSA (TCSA. Numerical simulations on MANETs are performed to demonstrate the effectiveness of the proposed TCSA method by determining an optimum route that satisfies various Quality of Service (QoS constraints. The results are compared with some of the existing techniques in the literature; therefore the superiority of the proposed method is established.

  1. Quality of Service Routing in Manet Using a Hybrid Intelligent Algorithm Inspired by Cuckoo Search.

    Science.gov (United States)

    Rajalakshmi, S; Maguteeswaran, R

    2015-01-01

    A hybrid computational intelligent algorithm is proposed by integrating the salient features of two different heuristic techniques to solve a multiconstrained Quality of Service Routing (QoSR) problem in Mobile Ad Hoc Networks (MANETs) is presented. The QoSR is always a tricky problem to determine an optimum route that satisfies variety of necessary constraints in a MANET. The problem is also declared as NP-hard due to the nature of constant topology variation of the MANETs. Thus a solution technique that embarks upon the challenges of the QoSR problem is needed to be underpinned. This paper proposes a hybrid algorithm by modifying the Cuckoo Search Algorithm (CSA) with the new position updating mechanism. This updating mechanism is derived from the differential evolution (DE) algorithm, where the candidates learn from diversified search regions. Thus the CSA will act as the main search procedure guided by the updating mechanism derived from DE, called tuned CSA (TCSA). Numerical simulations on MANETs are performed to demonstrate the effectiveness of the proposed TCSA method by determining an optimum route that satisfies various Quality of Service (QoS) constraints. The results are compared with some of the existing techniques in the literature; therefore the superiority of the proposed method is established.

  2. 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.

  3. 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.

  4. 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...

  5. Design Intelligent Model-free Hybrid Guidance Controller for Three Dimension Motor

    Directory of Open Access Journals (Sweden)

    Abdol Majid Mirshekaran

    2014-10-01

    Full Text Available The minimum rule base Proportional Integral Derivative (PID Fuzzy hybrid guidance Controller for three dimensions spherical motor is presented in this research. A three dimensions spherical motor is well equipped with conventional control techniques and, in particular, various PID controllers which demonstrate a good performance and successfully solve different guidance problems. Guidance control in a three dimensions spherical motor is performed by the PID controllers producing the control signals which are applied to systems torque. The necessary reference inputs for a PID controller are usually supplied by the system's sensors based on different data. The popularity of PID Fuzzy hybrid guidance Controller can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. PID methodology has three inputs and if any input is described with seven linguistic values, and any rule has three conditions we will need 343 rules. It is too much work to write 343 rules. In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PD-like fuzzy controller and a conventional PI controller to have the minimum rule base. Linear type PID controller is used to modify PID fuzzy logic theory to design hybrid guidance methodology. This research is used to reduce or eliminate the fuzzy and conventional PID controller problem based on minimum rule base fuzzy logic theory and modified it by PID method to control of spherical motor system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.

  6. HYBRIDIZATION OF MODIFIED ANT COLONY OPTIMIZATION AND INTELLIGENT WATER DROPS ALGORITHM FOR JOB SCHEDULING IN COMPUTATIONAL GRID

    Directory of Open Access Journals (Sweden)

    P. Mathiyalagan

    2013-10-01

    Full Text Available As grid is a heterogeneous environment, finding an optimal schedule for the job is always a complex task. In this paper, a hybridization technique using intelligent water drops and Ant colony optimization which are nature-inspired swarm intelligence approaches are used to find the best resource for the job. Intelligent water drops involves in finding out all matching resources for the job requirements and the routing information (optimal path to reach those resources. Ant Colony optimization chooses the best resource among all matching resources for the job. The objective of this approach is to converge to the optimal schedule faster, minimize the make span of the job, improve load balancing of resources and efficient utilization of available resources.

  7. Identification of sorghum hybrids with high phenotypic stability using GGE biplot methodology.

    Science.gov (United States)

    Teodoro, P E; Almeida Filho, J E; Daher, R F; Menezes, C B; Cardoso, M J; Godinho, V P C; Torres, F E; Tardin, F D

    2016-06-10

    The aim of this study was to identify sorghum hybrids that have both high yield and phenotypic stability in Brazilian environments. Seven trials were conducted between February and March 2011. The experimental design was a randomized complete block with 25 treatments and three replicates. The treatments consisted of 20 simple pre-commercial hybrids and five witnesses of grain sorghum. Sorghum genotypes were analyzed by the genotype main effects + genotype environment interaction (GGE) biplot method if significant genotype x environment interaction, adaptability, and phenotypic stability were detected. GGE biplot methodology identified two groups of environments, the first composed of Água Comprida-MG, Montividiu-GO, and Vilhena- RO and the second of Guaíra-SP and Sete Lagoas-MG. The BRS 308 and 1G282 genotypes were found to have high grain yield, adaptability, and phenotypic stability and are thus indicated for cultivation in the first and second groups of environments, respectively.

  8. Robust Intelligence (RI) under uncertainty: Mathematical foundations of autonomous hybrid (human-machine-robot) teams, organizations and systems

    OpenAIRE

    Lawless, William F.

    2013-01-01

    To develop a theory of Robust Intelligence (RI), we continue to advance our theory of interdependence on the efficient and effective control of systems of autonomous hybrid teams composed of robots, machines and humans working interchangeably. As is the case with humans, we believe that RI is less likely to be achieved by individual computational agents; instead, we propose that a better path to RI is with interdependent agents. However, unlike conventional computational models where agents a...

  9. Ultrafast laser based hybrid methodology of silicon microstructure fabrication for optoelectronic applications

    Science.gov (United States)

    Kanaujia, Pawan K.; Bulbul, Angika; Parmar, Vinod; Prakash, G. Vijaya

    2017-10-01

    As an alternative approach to conventional lithography based fabrication, simple methodology of ultrafast laser writing followed by chemical processing for fabrication of silicon microstructures is studied and presented. Laser fluence and number of pulses dependent laser-matter interaction study reveals several concurrent extreme nonlinearities that influence the structural morphology in both longitudinal and transverse directions. High intensity femtosecond pulse propagation produces inevitable structural features, such as quasi aperiodic surface textures, V-shaped craters, re-casted melt and debris. To minimize such undesired effects, isotropic and anisotropic chemical etching processes have been systematically optimized. Such hybrid protocols resulted into definite microstructures, with surface quality comparable to those obtained from other lithographic fabrication methods. The proposed methodology is expected to provide control over desired feature sizes, for large-scale and cost-effective fabrication of microstructures for many optoelectronics applications.

  10. Topology optimization of double- and triple-layer grids using a hybrid methodology

    Science.gov (United States)

    Dehghani, M.; Mashayekhi, M.; Salajegheh, E.

    2016-08-01

    In this article, a hybrid methodology combining evolutionary structural optimization (ESO) and gravitational particle swarm (GPS) methods is proposed for topology optimization of double- and triple-layer grids. In the present methodology, which is called the ESO-GPS method, the size optimization of double- and triple-layer grids is first performed by ESO. Then, the outcomes of the ESO are used to improve the GPS through four modifications. Structural weight is minimized against constraints on the displacements of nodes, internal stresses and element slenderness ratio. The GPS is used to investigate the optimum topology of large-scale skeletal structures with discrete variables whose agents update their respective positions by the particle swarm optimization velocity and the acceleration of the gravitational search algorithm. The numerical results show that the proposed algorithm, the ESO-GPS, performs better than the GPS and the other methods presented in the literature.

  11. 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

  12. [Development of New Mathematical Methodology in Air Traffic Control for the Analysis of Hybrid Systems

    Science.gov (United States)

    Hermann, Robert

    1997-01-01

    The aim of this research is to develop new mathematical methodology for the analysis of hybrid systems of the type involved in Air Traffic Control (ATC) problems. Two directions of investigation were initiated. The first used the methodology of nonlinear generalized functions, whose mathematical foundations were initiated by Colombeau and developed further by Oberguggenberger; it has been extended to apply to ordinary differential. Systems of the type encountered in control in joint work with the PI and M. Oberguggenberger. This involved a 'mixture' of 'continuous' and 'discrete' methodology. ATC clearly involves mixtures of two sorts of mathematical problems: (1) The 'continuous' dynamics of a standard control type described by ordinary differential equations (ODE) of the form: {dx/dt = f(x, u)} and (2) the discrete lattice dynamics involved of cellular automata. Most of the CA literature involves a discretization of a partial differential equation system of the type encountered in physics problems (e.g. fluid and gas problems). Both of these directions requires much thinking and new development of mathematical fundamentals before they may be utilized in the ATC work. Rather than consider CA as 'discretization' of PDE systems, I believe that the ATC applications will require a completely different and new mathematical methodology, a sort of discrete analogue of jet bundles and/or the sheaf-theoretic techniques to topologists. Here too, I have begun work on virtually 'virgin' mathematical ground (at least from an 'applied' point of view) which will require considerable preliminary work.

  13. A New Hybrid Fuzzy Intelligent Filter for Medical Image Noise Reduction

    Directory of Open Access Journals (Sweden)

    Somaye Aliakbari Dehkordi

    2014-10-01

    Full Text Available Medical imaging comprises different imaging modalities and processes to image human body for diagnostic and treatment purposes and, therefore has an important role in the improvement of public health in all population groups. In this paper, we present an intelligent hybrid noise reduction filter which is based on Neuro-Fuzzy systems. It is especially beneficial in medical image noise reduction. First stage we feed the input image into four general noise reduction filters in parallel. These general filters are: mean filter, median filter, weighted median filter and the adaptive median filter. At the second stage we give the output of the above filters as input into a Neuro-Fuzzy system. As expected, the ability of Neuro-Fuzzy systems in encoding human knowledge and using non-deterministic knowledge, allow us to achieve much more noise reduction from the input images. We implement the proposed method and use it for reduction of noise from a set of medical images affected with high noise density. Experimental results show that the idea is considerably effective.

  14. Hybrid Intelligent System to Perform Fault Detection on BIS Sensor During Surgeries

    Science.gov (United States)

    Casteleiro-Roca, José-Luis; Calvo-Rolle, José Luis; Méndez Pérez, Juan Albino; Roqueñí Gutiérrez, Nieves; de Cos Juez, Francisco Javier

    2017-01-01

    This paper presents a new fault detection system in hypnotic sensors used for general anesthesia during surgery. Drug infusion during surgery is based on information received from patient monitoring devices; accordingly, faults in sensor devices can put patient safety at risk. Our research offers a solution to cope with these undesirable scenarios. We focus on the anesthesia process using intravenous propofol as the hypnotic drug and employing a Bispectral Index (BISTM) monitor to estimate the patient’s unconsciousness level. The method developed identifies BIS episodes affected by disturbances during surgery with null clinical value. Thus, the clinician—or the automatic controller—will not take those measures into account to calculate the drug dose. Our method compares the measured BIS signal with expected behavior predicted by the propofol dose provider and the electromyogram (EMG) signal. For the prediction of the BIS signal, a model based on a hybrid intelligent system architecture has been created. The model uses clustering combined with regression techniques. To validate its accuracy, a dataset taken during surgeries with general anesthesia was used. The proposed fault detection method for BIS sensor measures has also been verified using data from real cases. The obtained results prove the method’s effectiveness. PMID:28106793

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. A new hybrid intelligent system for accurate detection of Parkinson's disease.

    Science.gov (United States)

    Hariharan, M; Polat, Kemal; Sindhu, R

    2014-03-01

    Elderly people are commonly affected by Parkinson's disease (PD) which is one of the most common neurodegenerative disorders due to the loss of dopamine-producing brain cells. People with PD's (PWP) may have difficulty in walking, talking or completing other simple tasks. Variety of medications is available to treat PD. Recently, researchers have found that voice signals recorded from the PWP is becoming a useful tool to differentiate them from healthy controls. Several dysphonia features, feature reduction/selection techniques and classification algorithms were proposed by researchers in the literature to detect PD. In this paper, hybrid intelligent system is proposed which includes feature pre-processing using Model-based clustering (Gaussian mixture model), feature reduction/selection using principal component analysis (PCA), linear discriminant analysis (LDA), sequential forward selection (SFS) and sequential backward selection (SBS), and classification using three supervised classifiers such as least-square support vector machine (LS-SVM), probabilistic neural network (PNN) and general regression neural network (GRNN). PD dataset was used from University of California-Irvine (UCI) machine learning database. The strength of the proposed method has been evaluated through several performance measures. The experimental results show that the combination of feature pre-processing, feature reduction/selection methods and classification gives a maximum classification accuracy of 100% for the Parkinson's dataset. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  20. Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    M. Sudha

    2015-12-01

    Full Text Available Uncertain atmosphere is a prevalent factor affecting the existing prediction approaches. Rough set and fuzzy set theories as proposed by Pawlak and Zadeh have become an effective tool for handling vagueness and fuzziness in the real world scenarios. This research work describes the impact of Hybrid Intelligent System (HIS for strategic decision support in meteorology. In this research a novel exhaustive search based Rough set reduct Selection using Genetic Algorithm (RSGA is introduced to identify the significant input feature subset. The proposed model could identify the most effective weather parameters efficiently than other existing input techniques. In the model evaluation phase two adaptive techniques were constructed and investigated. The proposed Artificial Neural Network based on Back Propagation learning (ANN-BP and Adaptive Neuro Fuzzy Inference System (ANFIS was compared with existing Fuzzy Unordered Rule Induction Algorithm (FURIA, Structural Learning Algorithm on Vague Environment (SLAVE and Particle Swarm OPtimization (PSO. The proposed rainfall prediction models outperformed when trained with the input generated using RSGA. A meticulous comparison of the performance indicates ANN-BP model as a suitable HIS for effective rainfall prediction. The ANN-BP achieved 97.46% accuracy with a nominal misclassification rate of 0.0254 %.

  1. 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.

  2. Application of hybrid methodology to rotors in steady and maneuvering flight

    Science.gov (United States)

    Rajmohan, Nischint

    Helicopters are versatile flying machines that have capabilities that are unparalleled by fixed wing aircraft, such as operating in hover, performing vertical takeoff and landing on unprepared sites. This makes their use especially desirable in military and search-and-rescue operations. However, modern helicopters still suffer from high levels of noise and vibration caused by the physical phenomena occurring in the vicinity of the rotor blades. Therefore, improvement in rotorcraft design to reduce the noise and vibration levels requires understanding of the underlying physical phenomena, and accurate prediction capabilities of the resulting rotorcraft aeromechanics. The goal of this research is to study the aeromechanics of rotors in steady and maneuvering flight using hybrid Computational Fluid Dynamics (CFD) methodology. The hybrid CFD methodology uses the Navier-Stokes equations to solve the flow near the blade surface but the effect of the far wake is computed through the wake model. The hybrid CFD methodology is computationally efficient and its wake modeling approach is nondissipative making it an attractive tool to study rotorcraft aeromechanics. Several enhancements were made to the CFD methodology and it was coupled to a Computational Structural Dynamics (CSD) methodology to perform a trimmed aeroelastic analysis of a rotor in forward flight. The coupling analyses, both loose and tight were used to identify the key physical phenomena that affect rotors in different steady flight regimes. The modeling enhancements improved the airloads predictions for a variety of flight conditions. It was found that the tightly coupled method did not impact the loads significantly for steady flight conditions compared to the loosely coupled method. The coupling methodology was extended to maneuvering flight analysis by enhancing the computational and structural models to handle non-periodic flight conditions and vehicle motions in time accurate mode. The flight test

  3. 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

  4. A hybrid CS-SA intelligent approach to solve uncertain dynamic facility layout problems considering dependency of demands

    Science.gov (United States)

    Moslemipour, Ghorbanali

    2017-07-01

    This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algorithm is proposed by combining the simulated annealing and clonal selection algorithms. The proposed model and the hybrid algorithm are verified and validated using design of experiment and benchmark methods. The results show that the hybrid algorithm has an outstanding performance from both solution quality and computational time points of view. Besides, the proposed model can be used in both of the stochastic and deterministic situations.

  5. 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.

  6. 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.

  7. 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.

  8. The assessment of emotional intelligence: a comparison of performance-based and self-report methodologies.

    Science.gov (United States)

    Goldenberg, Irina; Matheson, Kimberly; Mantler, Janet

    2006-02-01

    We assessed the patterns of convergent validity for the Mayer-Salovey-Caruso Emotional Intelligence Test (Mayer, Salovey, & Caruso, 2002), a performance-based measure of emotional intelligence (EI) that entails presenting problems thought to have correct responses, and a self-report measure of EI (Schutte et al., 1998). The relations between EI and demographic characteristics of a diverse community sample (N = 223) concurred with previous research. However, the performance-based and self-report scales were not related to one another. Only self-reported EI scores showed a consistent pattern of relations with self-reported coping styles and depressive affect, whereas the performance-based measure demonstrated stronger relations with age, education, and receiving psychotherapy. We discuss implications for the validity of these measures and their utility.

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

    OpenAIRE

    Heather M Szeles

    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...

  10. 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.

  11. A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

    Science.gov (United States)

    Dragos, Kosmas; Smarsly, Kay

    2016-04-01

    System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

  12. When the lowest energy does not induce native structures: parallel minimization of multi-energy values by hybridizing searching intelligences.

    Directory of Open Access Journals (Sweden)

    Qiang Lü

    Full Text Available BACKGROUND: Protein structure prediction (PSP, which is usually modeled as a computational optimization problem, remains one of the biggest challenges in computational biology. PSP encounters two difficult obstacles: the inaccurate energy function problem and the searching problem. Even if the lowest energy has been luckily found by the searching procedure, the correct protein structures are not guaranteed to obtain. RESULTS: A general parallel metaheuristic approach is presented to tackle the above two problems. Multi-energy functions are employed to simultaneously guide the parallel searching threads. Searching trajectories are in fact controlled by the parameters of heuristic algorithms. The parallel approach allows the parameters to be perturbed during the searching threads are running in parallel, while each thread is searching the lowest energy value determined by an individual energy function. By hybridizing the intelligences of parallel ant colonies and Monte Carlo Metropolis search, this paper demonstrates an implementation of our parallel approach for PSP. 16 classical instances were tested to show that the parallel approach is competitive for solving PSP problem. CONCLUSIONS: This parallel approach combines various sources of both searching intelligences and energy functions, and thus predicts protein conformations with good quality jointly determined by all the parallel searching threads and energy functions. It provides a framework to combine different searching intelligence embedded in heuristic algorithms. It also constructs a container to hybridize different not-so-accurate objective functions which are usually derived from the domain expertise.

  13. Spatiotemporal groundwater level modeling using hybrid artificial intelligence-meshless method

    Science.gov (United States)

    Nourani, Vahid; Mousavi, Shahram

    2016-05-01

    Uncertainties of the field parameters, noise of the observed data and unknown boundary conditions are the main factors involved in the groundwater level (GL) time series which limit the modeling and simulation of GL. This paper presents a hybrid artificial intelligence-meshless model for spatiotemporal GL modeling. In this way firstly time series of GL observed in different piezometers were de-noised using threshold-based wavelet method and the impact of de-noised and noisy data was compared in temporal GL modeling by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). In the second step, both ANN and ANFIS models were calibrated and verified using GL data of each piezometer, rainfall and runoff considering various input scenarios to predict the GL at one month ahead. In the final step, the simulated GLs in the second step of modeling were considered as interior conditions for the multiquadric radial basis function (RBF) based solve of governing partial differential equation of groundwater flow to estimate GL at any desired point within the plain where there is not any observation. In order to evaluate and compare the GL pattern at different time scales, the cross-wavelet coherence was also applied to GL time series of piezometers. The results showed that the threshold-based wavelet de-noising approach can enhance the performance of the modeling up to 13.4%. Also it was found that the accuracy of ANFIS-RBF model is more reliable than ANN-RBF model in both calibration and validation steps.

  14. 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.

  15. Systematization of a hybrid costing method for medical procedures: a concomitant apllication of the ABC and UEP methodologies

    OpenAIRE

    Márcia Zanievicz da Silva; Altair Borgert; Charles Albino Schultz

    2009-01-01

    The purpose of this study consists in systematization Hybrid Costing Methodology supported by the concepts of Activity Based Costing (ABC) and the Production Effort Unit (UEP) to quantify the cost of medical procedures in hospitals. By means of theory-concept research, the hybrid method application stages were organized and then tested at the University Hospital of the University of the State of Santa Catarina with the purpose of determining the cost of medical procedures, more...

  16. Multi-objective Optimization of Continuous Drive Friction Welding Process Parameters Using Response Surface Methodology with Intelligent Optimization Algorithm

    Institute of Scientific and Technical Information of China (English)

    P M AJITH; T MAFSAL HUSAIN; P SATHIYA; S ARAVINDAN

    2015-01-01

    The optimum friction welding (FW) parameters of duplex stainless steel (DSS) UNS S32205 joint was determined. The experiment was carried out as the central composite array of 30 experiments. The selected input parameters were friction pressure (F), upset pressure (U), speed (S) and burn-off length (B), and responses were hardness and ultimate tensile strength. To achieve the quality of the welded joint, the ultimate tensile strength and hardness were maximized, and response surface methodology (RSM) was applied to create separate regression equations of tensile strength and hardness. Intelligent optimization technique such as genetic algorithm was used to predict the Pareto optimal solutions. Depending upon the application, preferred suitable welding parameters were selected. It was inferred that the changing hardness and tensile strength of the friction welded joint inlfuenced the upset pressure, friction pressure and speed of rotation.

  17. 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.

  18. PWR Containment Shielding Calculations with SCALE6.1 Using Hybrid Deterministic-Stochastic Methodology

    Directory of Open Access Journals (Sweden)

    Mario Matijević

    2016-01-01

    Full Text Available The capabilities of the SCALE6.1/MAVRIC hybrid shielding methodology (CADIS and FW-CADIS were demonstrated when applied to a realistic deep penetration Monte Carlo (MC shielding problem of a full-scale PWR containment model. Automatic preparation of variance reduction (VR parameters is based on deterministic transport theory (SN method providing the space-energy importance function. The aim of this paper was to determine the neutron-gamma dose rate distributions over large portions of PWR containment with uniformly small MC uncertainties. The sources of ionizing radiation included fission neutrons and photons from the reactor and photons from the activated primary coolant. We investigated benefits and differences of FW-CADIS over CADIS methodology for the objective of the uniform MC particle density in the desired tally regions. Memory intense deterministic module was used with broad group library “v7_27n19g” opposed to the fine group library “v7_200n47g” used for final MC simulation. Compared with CADIS and with the analog MC, FW-CADIS drastically improved MC dose rate distributions. Modern shielding problems with large spatial domains require not only extensive computational resources but also understanding of the underlying physics and numerical interdependence between SN-MC modules. The results of the dose rates throughout the containment are presented and discussed for different volumetric adjoint sources.

  19. Hybrid Genetic Crossover Based Swarm Intelligence Optimization for Efficient Resource Allocation in MIMO OFDM Systems

    Directory of Open Access Journals (Sweden)

    B. Sathish Kumar

    2015-07-01

    Full Text Available Rapid development of wireless services, leads to ubiquitous personal connectivity in the world. The demand for multimedia interactivity is higher in the world which leads to the requirement of high data transmission rate. Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM is a future wireless service which is used to overcome the existing service problems such as development of subscriber pool and higher throughput per user. Although it overcomes the problems in existing services, resource allocation becomes one of the major issues in the MIMO-OFDM systems. Resource allocation in MIMO-OFDM is the optimization of subcarrier and power allocation for the user. The overall performance of the system can be improved only with the efficient resource allocation approach. The user data rate is increased by efficient allocation of the subcarrier and power allocation for each user at the base station, which is subject to constraints on total power and bit error rate. In this study, the problem of resource allocation in MIMO-OFDM system is tackled using hybrid artificial bee colony optimization algorithm based on a crossover operation along with Poisson-Jensen in equation. The experimental results show that the proposed methodology is better than the existing techniques.

  20. An intelligent control framework for robot-aided resistance training using hybrid system modeling and impedance estimation.

    Science.gov (United States)

    Xu, Guozheng; Guo, Xiaobo; Zhai, Yan; Li, Huijun

    2015-08-01

    This study presents a novel therapy control method for robot-assisted resistance training using the hybrid system modeling technology and the estimated patient's bio-impedance changes. A new intelligent control framework based on hybrid system theory is developed, to automatically generate the desired resistive force and to make accommodating emergency behavior, when monitoring the changes of the impaired limb's muscle strength or the unpredictable safety-related occurrences during the execution of the training task. The impaired limb's muscle strength progress is online evaluated using its bio-damping and bio-stiffness estimation results. The proposed method is verified with a custom constructed therapeutic robot system featuring a Barrett WAM™ compliant manipulator. A typical inpatient stroke subject was recruited and enrolled in a ten-week resistance training program. Preliminary results show that the proposed therapeutic strategy can enhance the impaired limb's muscle strength and has practicability for robot-aided rehabilitation training.

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

    Science.gov (United States)

    Szeles, Heather M

    2015-01-01

    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. 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. 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. This study contributes to the body of EI literature and research on nursing education and leadership development.

  2. 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.

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

    Science.gov (United States)

    Chandrasekaran, Muthumari; Tamang, Santosh

    2016-06-01

    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.

  4. 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.

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

    Science.gov (United States)

    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. PMID:27403153

  6. 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.

  7. 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.

  8. Modeling of the ORNL PCA Benchmark Using SCALE6.0 Hybrid Deterministic-Stochastic Methodology

    Directory of Open Access Journals (Sweden)

    Mario Matijević

    2013-01-01

    Full Text Available Revised guidelines with the support of computational benchmarks are needed for the regulation of the allowed neutron irradiation to reactor structures during power plant lifetime. Currently, US NRC Regulatory Guide 1.190 is the effective guideline for reactor dosimetry calculations. A well known international shielding database SINBAD contains large selection of models for benchmarking neutron transport methods. In this paper a PCA benchmark has been chosen from SINBAD for qualification of our methodology for pressure vessel neutron fluence calculations, as required by the Regulatory Guide 1.190. The SCALE6.0 code package, developed at Oak Ridge National Laboratory, was used for modeling of the PCA benchmark. The CSAS6 criticality sequence of the SCALE6.0 code package, which includes KENO-VI Monte Carlo code, as well as MAVRIC/Monaco hybrid shielding sequence, was utilized for calculation of equivalent fission fluxes. The shielding analysis was performed using multigroup shielding library v7_200n47g derived from general purpose ENDF/B-VII.0 library. As a source of response functions for reaction rate calculations with MAVRIC we used international reactor dosimetry libraries (IRDF-2002 and IRDF-90.v2 and appropriate cross-sections from transport library v7_200n47g. The comparison of calculational results and benchmark data showed a good agreement of the calculated and measured equivalent fission fluxes.

  9. 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.

  10. Multistep Wind Speed Forecasting Using a Novel Model Hybridizing Singular Spectrum Analysis, Modified Intelligent Optimization, and Rolling Elman Neural Network

    Directory of Open Access Journals (Sweden)

    Zhongshan Yang

    2016-01-01

    Full Text Available Wind speed high-accuracy forecasting, an important part of the electrical system monitoring and control, is of the essence to protect the safety of wind power utilization. However, the wind speed signals are always intermittent and intrinsic complexity; therefore, it is difficult to forecast them accurately. Many traditional wind speed forecasting studies have focused on single models, which leads to poor prediction accuracy. In this paper, a new hybrid model is proposed to overcome the shortcoming of single models by combining singular spectrum analysis, modified intelligent optimization, and the rolling Elman neural network. In this model, except for the multiple seasonal patterns used to reduce interferences from the original data, the rolling model is utilized to forecast the multistep wind speed. To verify the forecasting ability of the proposed hybrid model, 10 min and 60 min wind speed data from the province of Shandong, China, were proposed in this paper as the case study. Compared to the other models, the proposed hybrid model forecasts the wind speed with higher accuracy.

  11. Solar PV power generation forecasting using hybrid intelligent algorithms and uncertainty quantification based on bootstrap confidence intervals

    Science.gov (United States)

    AlHakeem, Donna Ibrahim

    This thesis focuses on short-term photovoltaic forecasting (STPVF) for the power generation of a solar PV system using probabilistic forecasts and deterministic forecasts. Uncertainty estimation, in the form of a probabilistic forecast, is emphasized in this thesis to quantify the uncertainties of the deterministic forecasts. Two hybrid intelligent models are proposed in two separate chapters to perform the STPVF. In Chapter 4, the framework of the deterministic proposed hybrid intelligent model is presented, which is a combination of wavelet transform (WT) that is a data filtering technique and a soft computing model (SCM) that is generalized regression neural network (GRNN). Additionally, this chapter proposes a model that is combined as WT+GRNN and is utilized to conduct the forecast of two random days in each season for 1-hour-ahead to find the power generation. The forecasts are analyzed utilizing accuracy measures equations to determine the model performance and compared with another SCM. In Chapter 5, the framework of the proposed model is presented, which is a combination of WT, a SCM based on radial basis function neural network (RBFNN), and a population-based stochastic particle swarm optimization (PSO). Chapter 5 proposes a model combined as a deterministic approach that is represented as WT+RBFNN+PSO, and then a probabilistic forecast is conducted utilizing bootstrap confidence intervals to quantify uncertainty from the output of WT+RBFNN+PSO. In Chapter 5, the forecasts are conducted by furthering the tests done in Chapter 4. Chapter 5 forecasts the power generation of two random days in each season for 1-hour-ahead, 3-hour-ahead, and 6-hour-ahead. Additionally, different types of days were also forecasted in each season such as a sunny day (SD), cloudy day (CD), and a rainy day (RD). These forecasts were further analyzed using accuracy measures equations, variance and uncertainty estimation. The literature that is provided supports that the proposed

  12. 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.

  13. 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.

  14. 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.

  15. Development of Hybrid Intelligent Systems and their Applications from Engineering Systems to Complex Systems

    CERN Document Server

    Owladeghaffari, Hamed

    2008-01-01

    In this study, we introduce general frame of MAny Connected Intelligent Particles Systems (MACIPS). Connections and interconnections between particles get a complex behavior of such merely simple system (system in system).Contribution of natural computing, under information granulation theory, are the main topic of this spacious skeleton. Upon this clue, we organize different algorithms involved a few prominent intelligent computing and approximate reasoning methods such as self organizing feature map (SOM)[9], Neuro- Fuzzy Inference System[10], Rough Set Theory (RST)[11], collaborative clustering, Genetic Algorithm and Ant Colony System. Upon this, we have employed our algorithms on the several engineering systems, especially emerged systems in Civil and Mineral processing. In other process, we investigated how our algorithms can be taken as a linkage of government-society interaction, where government catches various fashions of behavior: solid (absolute) or flexible. So, transition of such society, by chan...

  16. Hybrid methodologies for modeling the dynamics in selected classes of materials

    Science.gov (United States)

    Miljacic, Ljubomir

    The advent of computers brought a profound change in the way the practical problems in the physics of materials are addressed. Within the last decade, a rapidly evolving area of research is oriented towards interfacing the existing numerical tools in an optimized way, by explicitly taking advantage of the specifics of the problem, the so called "hybrid" approach. The Classical Molecular Dynamics (CMD) method holds a central position among computational methods for modeling on different levels of physical behavior; its two main limitations are the accuracy of the force-fields used, and accessible time scale. In this work, a new methodology was constructed to improve a force-field quality by matching it to a quantum model via mapping a complex many-body situation to a much reduced description of important local geometries. It was tested on a system of a water molecule interacting with hematite surface and a 66% reduction in the force mismatch was achieved. Also, a strategy of efficiently improving radial data fitting is found, where fit-functions are defined on a set of overlapping radial zones and where a specific post-processing numerical demand on the fitting data is required. It was incorporated, tested and applied to the DVM density-functional code and showed that the fitting error of the radial degrees of freedom can be efficiently removed for all practical purposes. Two different systems with concurrent Poisson and Newtonian evolution were analyzed in attempt go to beyond the CMD accessible time. Polymerization and self-assembly of thin molecular films on a quartz surface was modeled where local hydrogen bonding was used as an indicator of local configurational relaxation, and as a guide to a polymerization process. The results present a consistent picture which contradicts previous interpretation of experimental data. Also, a study of glass-forming glycerol liquid diffusion was conducted on a temperature range inaccessible to CMD. Atoms were artificially

  17. 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.

  18. 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.

  19. HYBRID OPTIMIZING GRIFFON-VULTURE ALGORITHM BASED ON SWARM INTELLIGENCE MECHANISMS

    Directory of Open Access Journals (Sweden)

    Chastikova V. A.

    2014-06-01

    Full Text Available Griffon-vultures with input parameters minimal value for compound functions optimization that change during the time searching hybrid algorithm offered in this article. Researches of its efficiency and comparing analysis with some other systems have been performed

  20. Applying Computational Intelligence

    CERN Document Server

    Kordon, Arthur

    2010-01-01

    Offers guidelines on creating value from the application of computational intelligence methods. This work introduces a methodology for effective real-world application of computational intelligence while minimizing development cost, and outlines the critical, underestimated technology marketing efforts required

  1. 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.

  2. 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.

  3. Systematization of a hybrid costing method for medical procedures: a concomitant apllication of the ABC and UEP methodologies

    Directory of Open Access Journals (Sweden)

    Márcia Zanievicz da Silva

    2009-01-01

    Full Text Available The purpose of this study consists in systematization Hybrid Costing Methodology supported by the concepts of Activity Based Costing (ABC and the Production Effort Unit (UEP to quantify the cost of medical procedures in hospitals. By means of theory-concept research, the hybrid method application stages were organized and then tested at the University Hospital of the University of the State of Santa Catarina with the purpose of determining the cost of medical procedures, more specifically childbirth. The execution process flow of childbirth is divided into seven distinct procedures because of its variations. Besides presenting the cost calculations of this process, the research establishes a numerical value called Activity Effort Measure which is based on the execution cost for all the activities necessary to achieve it. The results demonstrate that the proposed method can be applied to quantify the costs, as well as support the management of the several hospital activities.

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

    OpenAIRE

    Lukas Falat; Dusan Marcek; Maria Durisova

    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 sug...

  5. Mathematical Model and Its Hybrid Dynamic Mechanism in Intelligent Control of Ironmaking

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang-guan; ZENG Jiu-sun; ZHAO Min

    2007-01-01

    A hybrid dynamic model was proposed, which considered both the hydrokinetic and the chaotic properties of the blast furnace ironmaking process; and great emphasis was put on its mechanism. The new model took the high complexity of the blast furnace as well as the effects of main parameters of the model into account, and the predicted results were in very good agreement with actual data.

  6. 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.

  7. Hybrid Intelligent Diagnosis Technology Based on Granular Computing%应用粒计算的混合智能故障诊断技术研究

    Institute of Scientific and Technical Information of China (English)

    张周锁; 侯照文; 孙闯; 何正嘉

    2011-01-01

    Aiming at lacking hybrid modes and common algorithms in existing hybrid intelligent diagnosis, a new model of hybrid intelligent fault diagnosis based on granular computing is proposed. In the model, the core features sets (CFS) are extracted in different granular levels by the reduction algorithm based on neighborhood rough set, then, CFS are chosen to train artificial neural network and support vector machines as sub-classifiers in corresponding levels. And the results of sub-classifiers in different granular levels are combined by criterion matrix algorithm as output of hybrid intelligent diagnosis. The model is applied to fault diagnosis of roller bearings in high-speed locomotive. The application results demonstrate that the classification accuracy is raised with the increasing granular levels, and the accuracy of hybrid results is higher than the one of any sub-classifier. The proposed model exhibits the effect of granulation and the advantages complementation among different intelligent methods to provide a new way for hybrid intelligent diagnosis.%针对现有的混合智能故障诊断模型缺乏通用方法和混合框架,未能实现不同智能诊断方法的实质性融合和优势互补的问题,提出并构建了一种基于粒计算的混合智能故障诊断模型.该模型的核心是在邻域粗糙集中求取不同的邻域值,对故障特征集进行分层粒化,在不同粒度下获得核属性集.利用核属性集在相应粒度下构建人工神经网络和支持向量机子分类器,通过评估矩阵算法对所有粒度下全部子分类器的诊断结果进行融合集成.模型应用结果表明,分类精度随着粒度层的增加而不断提高,集成后的分类精度高于不同粒度下的所有子分类器,从而体现了粒化分层的优势和不同智能诊断方法的优势互补,为混合智能诊断提供了一种新途径.

  8. Hybrid Educational Methodology for the Cognitive Domain of Built Heritage Protection Interconnecting Secondary with Tertiary Level Education

    Directory of Open Access Journals (Sweden)

    Agoritsa Konstanti

    2013-10-01

    Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 In the present work, a hybrid educational methodology has been developed for approaching the cognitive domain of Built Heritage Protection in an interdisciplinary and integrated way. This domain was selected as a pilot one, presenting various remarkable characteristics, such as bringing together STEM subjects with social and human sciences, proving concrete concepts, being attractive for youth, and demanding combination of technical solutions with social aspects. The methodology had the scope to interconnect secondary with tertiary level education for the achievement of the best possible results, as the latter possesses the needed specialised knowledge, expertise and infrastructure. The methodology incorporates problem - based learning, aiming at the effective solution of real and extremely complex problems encountered in monument scale, which is combined with traditional teaching methods, such as lectures, as well as contemporary elements, such as class exercise laboratory experiments, in situ field work, promoting hands - on experience of students. The pilot application and evaluation of the hybrid methodology proved to be a valuable experience for students of secondary level education, which needs to be further exploited and optimised in order to meet the expectations of the interested parties.   /* Style Definitions */ table.MsoNormalTable {mso-style-name:"????????? ???????"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;}

  9. Special purpose hybrid transfinite elements and unified computational methodology for accurately predicting thermoelastic stress waves

    Science.gov (United States)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    This paper represents an attempt to apply extensions of a hybrid transfinite element computational approach for accurately predicting thermoelastic stress waves. The applicability of the present formulations for capturing the thermal stress waves induced by boundary heating for the well known Danilovskaya problems is demonstrated. A unique feature of the proposed formulations for applicability to the Danilovskaya problem of thermal stress waves in elastic solids lies in the hybrid nature of the unified formulations and the development of special purpose transfinite elements in conjunction with the classical Galerkin techniques and transformation concepts. Numerical test cases validate the applicability and superior capability to capture the thermal stress waves induced due to boundary heating.

  10. Intelligent design of investment casting mold based on a hybrid reasoning method

    Institute of Scientific and Technical Information of China (English)

    Jiang Ruisong; Zhang Dinghua; Wang Wenhu; Bu Kun

    2009-01-01

    A hybrid reasoning model was proposed in which CBR (case-based reasoning) was applied to the conceptual design and RBR (rule-based reasoning) was applied to the detailed design after research of the design process and domain knowledge of the acre-engine turbine blade investment casting mold design field. In the conceptual design stage, the representation and retrieval technologies were researched which improve the retrieval efficiency. Meanwhile, RBR was used to modify the retrieval result. The experimentation shows that the approach in this study can be used to obtain a more satisfactory design result.

  11. 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.

  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 Hybrid Intelligent Diagnosis Approach for Quick Screening of Alzheimer’s Disease Based on Multiple Neuropsychological Rating Scales

    Directory of Open Access Journals (Sweden)

    Ziming Yin

    2015-01-01

    Full Text Available Neuropsychological testing is an effective means for the screening of Alzheimer’s disease. Multiple neuropsychological rating scales should be used together to get subjects’ comprehensive cognitive state due to the limitation of a single scale, but it is difficult to operate in primary clinical settings because of the inadequacy of time and qualified clinicians. Aiming at identifying AD’s stages more accurately and conveniently in screening, we proposed a computer-aided diagnosis approach based on critical items extracted from multiple neuropsychological scales. The proposed hybrid intelligent approach combines the strengths of rough sets, genetic algorithm, and Bayesian network. There are two stages: one is attributes reduction technique based on rough sets and genetic algorithm, which can find out the most discriminative items for AD diagnosis in scales; the other is uncertain reasoning technique based on Bayesian network, which can forecast the probability of suffering from AD. The experimental data set consists of 500 cases collected by a top hospital in China and each case is determined by the expert panel. The results showed that the proposed approach could not only reduce items drastically with the same classification precision, but also perform better on identifying different stages of AD comparing with other existing scales.

  15. 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.

  16. 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.

  17. Dissolved oxygen content prediction in crab culture using a hybrid intelligent method

    Science.gov (United States)

    Yu, Huihui; Chen, Yingyi; Hassan, Shahbazgul; Li, Daoliang

    2016-06-01

    A precise predictive model is needed to obtain a clear understanding of the changing dissolved oxygen content in outdoor crab ponds, to assess how to reduce risk and to optimize water quality management. The uncertainties in the data from multiple sensors are a significant factor when building a dissolved oxygen content prediction model. To increase prediction accuracy, a new hybrid dissolved oxygen content forecasting model based on the radial basis function neural networks (RBFNN) data fusion method and a least squares support vector machine (LSSVM) with an optimal improved particle swarm optimization(IPSO) is developed. In the modelling process, the RBFNN data fusion method is used to improve information accuracy and provide more trustworthy training samples for the IPSO-LSSVM prediction model. The LSSVM is a powerful tool for achieving nonlinear dissolved oxygen content forecasting. In addition, an improved particle swarm optimization algorithm is developed to determine the optimal parameters for the LSSVM with high accuracy and generalizability. In this study, the comparison of the prediction results of different traditional models validates the effectiveness and accuracy of the proposed hybrid RBFNN-IPSO-LSSVM model for dissolved oxygen content prediction in outdoor crab ponds.

  18. 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.

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

    NARCIS (Netherlands)

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

    2011-01-01

    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 fo

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

    NARCIS (Netherlands)

    Dimitrova, D.C.; Heijenk, Gerhard J.; 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

  1. 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.

  2. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E. [Argonne National Lab., IL (United States); Applequist, C. A. [Commonwealth Research Corp., Chicago, IL (United States); Chasensky, T.M. [Commonwealth Edison Co., Chicago, IL (United States)

    1996-03-01

    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.

  4. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

    Ko, Soon Heum [Linkoeping University, Linkoeping (Sweden); Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel [Louisiana State University, Baton Rouge (United States); Jha, Shantenu [Rutgers University, Piscataway (United States)

    2014-01-15

    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.

  6. 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.

  7. 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

  8. 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

  9. Computational intelligence in optimization

    CERN Document Server

    Tenne, Yoel

    2010-01-01

    This volume presents a collection of recent studies covering the spectrum of computational intelligence applications with emphasis on their application to challenging real-world problems. Topics covered include: Intelligent agent-based algorithms, Hybrid intelligent systems, Cognitive and evolutionary robotics, Knowledge-Based Engineering, fuzzy sets and systems, Bioinformatics and Bioengineering, Computational finance and Computational economics, Data mining, Machine learning, and Expert systems. ""Computational Intelligence in Optimization"" is a comprehensive reference for researchers, prac

  10. GA_MLP NN: A Hybrid Intelligent System for Diabetes Disease Diagnosis

    Directory of Open Access Journals (Sweden)

    Dilip Kumar Choubey

    2016-01-01

    Full Text Available Diabetes is a condition in which the amount of sugar in the blood is higher than normal. Classification systems have been widely used in medical domain to explore patient’s data and extract a predictive model or set of rules. The prime objective of this research work is to facilitate a better diagnosis (classification of diabetes disease. There are already several methodology which have been implemented on classification for the diabetes disease. The proposed methodology implemented work in 2 stages: (a In the first stage Genetic Algorithm (GA has been used as a feature selection on Pima Indian Diabetes Dataset. (b In the second stage, Multilayer Perceptron Neural Network (MLP NN has been used for the classification on the selected feature. GA is noted to reduce not only the cost and computation time of the diagnostic process, but the proposed approach also improved the accuracy of classification. The experimental results obtained classification accuracy (79.1304% and ROC (0.842 show that GA and MLP NN can be successfully used for the diagnosing of diabetes disease.

  11. 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

  12. 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...

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

    Science.gov (United States)

    Garduno-Ramirez, Raul

    2000-10-01

    In response to the multiple and tighter operation requirements already placed on power plants, and anticipating everyday variations on their quantity and relevance due to competition on deregulated energy markets, this dissertation contributes the Intelligent Coordinated Control System (ICCS) paradigm that establishes a reference framework for the design of overall control systems for fossil-fuel power units, and develops a minimum prototype (ICCS-MP) to show its feasibility. The ICCS consists of a multiagent system organization structured as an open set of functionally grouped agent clusters in a two-level hierarchy. The upper level performs the supervisory functions needed to produce self-governing system behavior, while the lower level performs the fast reactive functions necessary for real-time control and protection. The ICCS-MP greatly extends the concept of current coordinated control schemes and embraces a minimum set of ICCS functions for the power unit to participate in load-frequency control in deregulated power systems; provides the means to achieve optimal wide-range load-tracking in multiobjective operating scenarios. The ICCS-MP preserves the ICCS structure. Supervisory functions include optimization and command generation, learning and control tuning, and performance and state monitoring. Direct level control functions realize a nonlinear multivariable feedforward-feedback scheme. These functions are implemented in three modules: reference governor, feedforward control processor (FFCP), and feedback control processor (FBCP). The reference governor provides set-point trajectories for the control loops by solving a multiobjective optimization problem that accommodates the operating scenario at hand. The FFCP facilitates achievement of wide-range operation; it is implemented as a fuzzy system that emulates the inverse static behavior of the power unit, and it is designed using neural networks. The FBCP provides disturbance and uncertainty compensation

  14. 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.

  15. A Hybrid Flight Control for a Simulated Raptor-30 V2 Helicopter

    Directory of Open Access Journals (Sweden)

    Arbab Nighat Khizer

    2015-04-01

    Full Text Available 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?s 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.

  16. 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. 

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. A constructive hybrid structure optimization methodology for radial basis probabilistic neural networks.

    Science.gov (United States)

    Huang, De-Shuang; Du, Ji-Xiang

    2008-12-01

    In this paper, a novel heuristic structure optimization methodology for radial basis probabilistic neural networks (RBPNNs) is proposed. First, a minimum volume covering hyperspheres (MVCH) algorithm is proposed to select the initial hidden-layer centers of the RBPNN, and then the recursive orthogonal least square algorithm (ROLSA) combined with the particle swarm optimization (PSO) algorithm is adopted to further optimize the initial structure of the RBPNN. The proposed algorithms are evaluated through eight benchmark classification problems and two real-world application problems, a plant species identification task involving 50 plant species and a palmprint recognition task. Experimental results show that our proposed algorithm is feasible and efficient for the structure optimization of the RBPNN. The RBPNN achieves higher recognition rates and better classification efficiency than multilayer perceptron networks (MLPNs) and radial basis function neural networks (RBFNNs) in both tasks. Moreover, the experimental results illustrated that the generalization performance of the optimized RBPNN in the plant species identification task was markedly better than that of the optimized RBFNN.

  2. A hybrid Land Cover Dataset for Russia: a new methodology for merging statistics, remote sensing and in-situ information

    Science.gov (United States)

    Schepaschenko, D.; McCallum, I.; Shvidenko, A.; Kraxner, F.; Fritz, S.

    2009-04-01

    There is a critical need for accurate land cover information for resource assessment, biophysical modeling, greenhouse gas studies, and for estimating possible terrestrial responses and feedbacks to climate change. However, practically all existing land cover datasets have quite a high level of uncertainty and suffer from a lack of important details that does not allow for relevant parameterization, e.g., data derived from different forest inventories. The objective of this study is to develop a methodology in order to create a hybrid land cover dataset at the level which would satisfy requirements of the verified terrestrial biota full greenhouse gas account (Shvidenko et al., 2008) for large regions i.e. Russia. Such requirements necessitate a detailed quantification of land classes (e.g., for forests - dominant species, age, growing stock, net primary production, etc.) with additional information on uncertainties of the major biometric and ecological parameters in the range of 10-20% and a confidence interval of around 0.9. The approach taken here allows the integration of different datasets to explore synergies and in particular the merging and harmonization of land and forest inventories, ecological monitoring, remote sensing data and in-situ information. The following datasets have been integrated: Remote sensing: Global Land Cover 2000 (Fritz et al., 2003), Vegetation Continuous Fields (Hansen et al., 2002), Vegetation Fire (Sukhinin, 2007), Regional land cover (Schmullius et al., 2005); GIS: Soil 1:2.5 Mio (Dokuchaev Soil Science Institute, 1996), Administrative Regions 1:2.5 Mio, Vegetation 1:4 Mio, Bioclimatic Zones 1:4 Mio (Stolbovoi & McCallum, 2002), Forest Enterprises 1:2.5 Mio, Rivers/Lakes and Roads/Railways 1:1 Mio (IIASA's data base); Inventories and statistics: State Land Account (FARSC RF, 2006), State Forest Account - SFA (FFS RF, 2003), Disturbances in forests (FFS RF, 2006). The resulting hybrid land cover dataset at 1-km resolution comprises

  3. A new displacement back analysis to identify mechanical geo-material parameters based on hybrid intelligent methodology

    Science.gov (United States)

    Feng, Xia-Ting; Zhao, Hongbo; Li, Shaojun

    2004-09-01

    Displacement back analysis is a common method to identify mechanical geo-material parameters using the monitored displacement. How to obtain a global optimum solution in large space search of highly non-linear multimodal is a key point of optimum back analysis. The paper presents a new back analysis that is an integration of evolutionary support vector machines (SVMs), numerical analysis and genetic algorithm. The non-linear relationship between the mechanical geo-material parameters to be identified and the corresponding displacement values of key points is learned and represented by evolutionary SVMs in global optimum. Numerical analysis is used to create training and testing samples for recognition of SVMs. Then, performing a global optimum search on the obtained SVMs using genetic algorithm can identify the mechanical geo-material parameters. The proposed algorithm is tested by back analysis of an elastic plate and an elastic-plastic plate and used to recognize mechanical parameters of subclay, strongly weathered tuff and weakly weathered tuff of Bachimen slope, Funing expressway, Fujian, China. The results indicate that applicability of the proposed algorithm with enough accuracy. Copyright

  4. Cocaine profiling for strategic intelligence, a cross-border project between France and Switzerland: part II. Validation of the statistical methodology for the profiling of cocaine.

    Science.gov (United States)

    Lociciro, S; Esseiva, P; Hayoz, P; Dujourdy, L; Besacier, F; Margot, P

    2008-05-20

    Harmonisation and optimization of analytical and statistical methodologies were carried out between two forensic laboratories (Lausanne, Switzerland and Lyon, France) in order to provide drug intelligence for cross-border cocaine seizures. Part I dealt with the optimization of the analytical method and its robustness. This second part investigates statistical methodologies that will provide reliable comparison of cocaine seizures analysed on two different gas chromatographs interfaced with a flame ionisation detectors (GC-FIDs) in two distinct laboratories. Sixty-six statistical combinations (ten data pre-treatments followed by six different distance measurements and correlation coefficients) were applied. One pre-treatment (N+S: area of each peak is divided by its standard deviation calculated from the whole data set) followed by the Cosine or Pearson correlation coefficients were found to be the best statistical compromise for optimal discrimination of linked and non-linked samples. The centralisation of the analyses in one single laboratory is not a required condition anymore to compare samples seized in different countries. This allows collaboration, but also, jurisdictional control over data.

  5. A sizing-design methodology for hybrid fuel cell power systems and its application to an unmanned underwater vehicle

    Science.gov (United States)

    Cai, Q.; Brett, D. J. L.; Browning, D.; Brandon, N. P.

    Hybridizing a fuel cell with an energy storage unit (battery or supercapacitor) combines the advantages of each device to deliver a system with high efficiency, low emissions, and extended operation compared to a purely fuel cell or battery/supercapacitor system. However, the benefits of such a system can only be realised if the system is properly designed and sized, based on the technologies available and the application involved. In this work we present a sizing-design methodology for hybridisation of a fuel cell with a battery or supercapacitor for applications with a cyclic load profile with two discrete power levels. As an example of the method's application, the design process for selecting the energy storage technology, sizing it for the application, and determining the fuel load/range limitations, is given for an unmanned underwater vehicle (UUV). A system level mass and energy balance shows that hydrogen and oxygen storage systems dominate the mass and volume of the energy system and consequently dictate the size and maximum mission duration of a UUV.

  6. 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.

  7. 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.

  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. An intelligent approach to the discovery of luminescent materials using a combinatorial approach combined with Taguchi methodology.

    Science.gov (United States)

    Chen, Lei; Chu, Cheng-I; Chen, Kuo-Ju; Chen, Po-Yuan; Hu, Shu-Fen; Liu, Ru-Shi

    2011-01-01

    A significant advance made in combinatorial approach research was that the emphasis shifted from simple mixing to intelligent screening, so as to improve the efficiency and accuracy of discovering new materials from a larger number of diverse compositions. In this study, the long-lasting luminescence of SrAl(2)O(4), which is co-doped with Eu(2+), Ce(3+), Dy(3+), Li(+) and H(3)BO(3), was investigated based on a combinatorial approach in conjunction with the Taguchi method. The minimal number of 16 samples to be tested (five dopants and four levels of concentration) were designed using the Taguchi method. The samples to be screened were synthesized using a parallel combinatorial strategy based on ink-jetting of precursors into an array of micro-reactor wells. The relative brightness of luminescence of the different phosphors over a particular period was assessed. Ce(3+) was identified as the constituent that detrimentally affected long-lasting luminescence. Its concentration was optimized to zero. Li(+) had a minor effect on long-lasting luminescence but the main factors that contributed to the objective property (long-lasting luminescence) were Eu(2+), Dy(3+) and H(3)BO(3), and the concentrations of these dopants were optimized to 0.020, 0.030 and 0.300, respectively, for co-doping into SrAl(2)O(4). This study demonstrates that the utility of the combinatorial approach for evaluating the effect of components on an objective property (e.g. phosphorescence) and estimating the expected performance under the optimal conditions can be improved by the Taguchi method.

  10. The development of a performance assessment methodology for activity based intelligence: A study of spatial, temporal, and multimodal considerations

    Science.gov (United States)

    Lewis, Christian M.

    Activity Based Intelligence (ABI) is the derivation of information from a series of in- dividual actions, interactions, and transactions being recorded over a period of time. This usually occurs in Motion imagery and/or Full Motion Video. Due to the growth of unmanned aerial systems technology and the preponderance of mobile video devices, more interest has developed in analyzing people's actions and interactions in these video streams. Currently only visually subjective quality metrics exist for determining the utility of these data in detecting specific activities. One common misconception is that ABI boils down to a simple resolution problem; more pixels and higher frame rates are better. Increasing resolution simply provides more data, not necessary more informa- tion. As part of this research, an experiment was designed and performed to address this assumption. Nine sensors consisting of four modalities were place on top of the Chester F. Carlson Center for Imaging Science in order to record a group of participants executing a scripted set of activities. The multimodal characteristics include data from the visible, long-wave infrared, multispectral, and polarimetric regimes. The activities the participants were scripted to cover a wide range of spatial and temporal interactions (i.e. walking, jogging, and a group sporting event). As with any large data acquisition, only a subset of this data was analyzed for this research. Specifically, a walking object exchange scenario and simulated RPG. In order to analyze this data, several steps of preparation occurred. The data were spatially and temporally registered; the individual modalities were fused; a tracking algorithm was implemented, and an activity detection algorithm was applied. To develop a performance assessment for these activities a series of spatial and temporal degradations were performed. Upon completion of this work, the ground truth ABI dataset will be released to the community for further analysis.

  11. Springer handbook of computational intelligence

    CERN Document Server

    Pedrycz, Witold

    2015-01-01

    This is the first book covering the basics and the state of the art and important applications of the complete growing discipline of computational intelligence. This comprehensive handbook presents a unique synergy of various approaches and new qualities to be gained by using hybrid approaches, incl. inspirations from biology and living organisms and animate systems. The text is organized in 7 main parts foundations, fuzzy sets, rough sets, evolutionary computation, neural networks, swarm intelligence and hybrid computational intelligence systems.

  12. Hybridizing Conversational and Clear Speech to Investigate the Source of Increased Intelligibility in Speakers with Parkinson's Disease

    Science.gov (United States)

    Tjaden, Kris; Kain, Alexander; Lam, Jennifer

    2014-01-01

    Purpose: A speech analysis-resynthesis paradigm was used to investigate segmental and suprasegmental acoustic variables explaining intelligibility variation for 2 speakers with Parkinson's disease (PD). Method: Sentences were read in conversational and clear styles. Acoustic characteristics from clear sentences were extracted and applied to…

  13. 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....

  14. 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.

  15. 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.

  16. Intelligent Mobile Olfaction of Swarm Robots

    National Research Council Canada - National Science Library

    Siti Nurmaini; Bambang Tutuko; Aulia Rahman Thoharsin

    2013-01-01

      This work presents intelligent mobile olfaction design and experimental results of intelligent swarm robots to detection a gas/odour source in an indoor environment by using multi agent based on hybrid algorithm...

  17. 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, A1 alternative; and Audio/Visual Alerting Pillbox, A2 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

  18. 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.

  19. A robust hybrid fuzzy-simulated annealing-intelligent water drops approach for tuning a distribution static compensator nonlinear controller in a distribution system

    Science.gov (United States)

    Bagheri Tolabi, Hajar; Hosseini, Rahil; Shakarami, Mahmoud Reza

    2016-06-01

    This article presents a novel hybrid optimization approach for a nonlinear controller of a distribution static compensator (DSTATCOM). The DSTATCOM is connected to a distribution system with the distributed generation units. The nonlinear control is based on partial feedback linearization. Two proportional-integral-derivative (PID) controllers regulate the voltage and track the output in this control system. In the conventional scheme, the trial-and-error method is used to determine the PID controller coefficients. This article uses a combination of a fuzzy system, simulated annealing (SA) and intelligent water drops (IWD) algorithms to optimize the parameters of the controllers. The obtained results reveal that the response of the optimized controlled system is effectively improved by finding a high-quality solution. The results confirm that using the tuning method based on the fuzzy-SA-IWD can significantly decrease the settling and rising times, the maximum overshoot and the steady-state error of the voltage step response of the DSTATCOM. The proposed hybrid tuning method for the partial feedback linearizing (PFL) controller achieved better regulation of the direct current voltage for the capacitor within the DSTATCOM. Furthermore, in the event of a fault the proposed controller tuned by the fuzzy-SA-IWD method showed better performance than the conventional controller or the PFL controller without optimization by the fuzzy-SA-IWD method with regard to both fault duration and clearing times.

  20. 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.

  1. A methodology for risk analysis based on hybrid Bayesian networks: application to the regasification system of liquefied natural gas onboard a floating storage and regasification unit.

    Science.gov (United States)

    Martins, Marcelo Ramos; Schleder, Adriana Miralles; Droguett, Enrique López

    2014-12-01

    This article presents an iterative six-step risk analysis methodology based on hybrid Bayesian networks (BNs). In typical risk analysis, systems are usually modeled as discrete and Boolean variables with constant failure rates via fault trees. Nevertheless, in many cases, it is not possible to perform an efficient analysis using only discrete and Boolean variables. The approach put forward by the proposed methodology makes use of BNs and incorporates recent developments that facilitate the use of continuous variables whose values may have any probability distributions. Thus, this approach makes the methodology particularly useful in cases where the available data for quantification of hazardous events probabilities are scarce or nonexistent, there is dependence among events, or when nonbinary events are involved. The methodology is applied to the risk analysis of a regasification system of liquefied natural gas (LNG) on board an FSRU (floating, storage, and regasification unit). LNG is becoming an important energy source option and the world's capacity to produce LNG is surging. Large reserves of natural gas exist worldwide, particularly in areas where the resources exceed the demand. Thus, this natural gas is liquefied for shipping and the storage and regasification process usually occurs at onshore plants. However, a new option for LNG storage and regasification has been proposed: the FSRU. As very few FSRUs have been put into operation, relevant failure data on FSRU systems are scarce. The results show the usefulness of the proposed methodology for cases where the risk analysis must be performed under considerable uncertainty.

  2. Intelligent Systems for Engineers and Scientists

    CERN Document Server

    Hopgood, Adrian A

    2011-01-01

    The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and

  3. 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) ...

  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. Intelligent hybrid genetic algorithm for container ship loading%集装箱船装载问题的混合遗传智能优化算法

    Institute of Scientific and Technical Information of China (English)

    朱莹; 向先波; 杨运桃; 王英伟

    2015-01-01

    For the purpose of optimizing the efficiency of the container,a mathematical model of con-tainer ship loading problem was established with the goal of maximizing the utilization of space.An intelligent hybrid genetic algorithm combined with a new encoding method consisting of the sequence and the placement of the cargo was presented.The genetic operators including partial mapped cross-over operator,two-point crossover operator,sequence reversed mutation operator and basic bit muta-tion operator were applied to the loading problem.Simulations were performed to validate the pro-posed algorithm.By taking two sets of test data in the classic Loh′s algorithm test,the space utiliza-tion respectively reached 94.31% and 91.41% which had an obvious improvement compared with the other algorithms.The results show the effectiveness of the intelligent hybrid genetic algorithm for ad-dressing the container ship loading problem.%为了提高集装箱的利用率,以空间利用率最大化为优化目标,建立集装箱船装载问题的数学模型,提出了一种新型混合遗传智能算法.算法中设计了一种包含货物装填顺序和放置状态的两段编码方式,构造适应集装箱船装载问题的部分映射交叉算子、两点交叉算子、顺序逆转变异算子和基本位变异算子,并对此算法进行了仿真验证.以 Loh 和 Nee 的两组经典测试数据为实例进行算法测试,空间利用率分别达到94.3%和91.4%,与相同类型装箱算法进行对比,空间利用率有明显提升,验证了混合遗传智能优化算法的有效性.

  7. 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.

  8. 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.

  9. 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.

  10. 新型智能混合式交流接触器%A New Type of Hybrid Semiconductor Intelligent AC Contactor

    Institute of Scientific and Technical Information of China (English)

    张培铭; 陈从华; 郑昕

    2001-01-01

    介绍了一种新型的混合式智能交流接触器,其仅用2个单向晶闸管就实现了接触器的少弧或无弧运行,且大大降低成本,减少体积。该接触器实现了全过程的动态优化控制,达到了节能、节材、无噪声、高操作频率、高电寿命,且可与主控计算机进行双向通信。%A new-type hybrid semiconductor intelligent AC contactor was developed. In the contacts of this kind of contactor with two SCRs only will there be no arcing or just small arcing when they are broken. The cost and volume are reduced greatly. This contactor realizes the optimal control in dynamic process and brings the benefits of energy and materials saving, no noise, high operating frequency and high electrical endurance. And it can also be communicated with the central master computer.

  11. 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.

  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. 'A new methodology for the development of hybrid powertrains'; 'Neue Methodik zur realitaetsnahen Auslegung hybrider Antriebskonzepte'

    Energy Technology Data Exchange (ETDEWEB)

    Cornelsen, K.; Form, T. [Technische Univ. Braunschweig (Germany). Inst. fuer Regelungstechnik; Jaensch, D.; Nietschke, W.; Wolter, T.M. [IAV GmbH, Berlin (Germany)]|[IAV GmbH, Gifhorn (Germany)

    2008-07-01

    Hybrid powertrains are highly complex systems. Their efficacy largely depends on the right design of components and their accurate coordination. In selecting the operating strategy, consideration must be given to the intended type of application and the overall system, consisting of environment, traffic, driver, vehicle and powertrain. Today, powertrain systems are developed off-line in a full-vehicle simulation process that predicts the quantitative values of a hybrid concept's handling characteristics with relative accuracy as early as the design phase. Qualitative values and actual driving feel, in contrast, are described inadequately. To date, it has only been possible to convey them in a later phase of the development process by constructing drivable prototypes. This paper presents a project that closes the gap between design and prototype test driving. The project has the aim of developing a simulator that can be driven in actual road traffic. This would provide developers and consumer acceptance investigations with a tool that makes it possible to test, check, compare, assess and present new powertrain system types in the early design and development phase. This would then produce a more accurate statement on the anticipated efficacy of the concept in relation to the particular situation in which it is used. (orig.)

  14. Acoustic Prediction Methodology and Test Validation for an Efficient Low-Noise Hybrid Wing Body Subsonic Transport

    Science.gov (United States)

    Kawai, Ronald T. (Compiler)

    2011-01-01

    This investigation was conducted to: (1) Develop a hybrid wing body subsonic transport configuration with noise prediction methods to meet the circa 2007 NASA Subsonic Fixed Wing (SFW) N+2 noise goal of -52 dB cum relative to FAR 36 Stage 3 (-42 dB cum re: Stage 4) while achieving a -25% fuel burned compared to current transports (re :B737/B767); (2) Develop improved noise prediction methods for ANOPP2 for use in predicting FAR 36 noise; (3) Design and fabricate a wind tunnel model for testing in the LaRC 14 x 22 ft low speed wind tunnel to validate noise predictions and determine low speed aero characteristics for an efficient low noise Hybrid Wing Body configuration. A medium wide body cargo freighter was selected to represent a logical need for an initial operational capability in the 2020 time frame. The Efficient Low Noise Hybrid Wing Body (ELNHWB) configuration N2A-EXTE was evolved meeting the circa 2007 NRA N+2 fuel burn and noise goals. The noise estimates were made using improvements in jet noise shielding and noise shielding prediction methods developed by UC Irvine and MIT. From this the Quiet Ultra Integrated Efficient Test Research Aircraft #1 (QUIET-R1) 5.8% wind tunnel model was designed and fabricated.

  15. Genetic based sensorless hybrid intelligent controller for strip loop formation control between inter-stands in hot steel rolling mills.

    Science.gov (United States)

    Thangavel, S; Palanisamy, V; Duraiswamy, K

    2008-04-01

    Safe operating environment is essential for all complex industrial processes. The safety issues in steel rolling mill when the hot strip passes through consecutive mill stands have been considered in this paper. Formation of sag in strip is a common problem in the rolling process. The excessive sag can lead to scrap runs and damage to machinery. Conventional controllers for mill actuation system are based on a rolling model. The factors like rise in temperature, aging, wear and tear are not taken into account while designing a conventional controller. Therefore, the conventional controller cannot yield a requisite controlled output. In this paper, a new Genetic-neuro-fuzzy hybrid controller without tension sensor has been proposed to optimize the quantum of excessive sag and reduce it. The performance of the proposed controller has been compared with the performance of fuzzy logic controller, Neuro-fuzzy controller and conventional controller with the help of data collected from the plant. The simulation results depict that the proposed controller has superior performance than the other controllers.

  16. Design and Simulation of a Hybrid Intelligent Shock Absorption System%混合式智能减震系统的设计与仿真

    Institute of Scientific and Technical Information of China (English)

    马驰; 李光林; 宋杰; 李小云

    2016-01-01

    为提高摩托车在较差路况下的减震效率,增加行驶的平稳性和乘坐人员的舒适性,设计研究了一种混合式智能减震系统.该系统以弹簧、电磁铁为基础,空气阻尼为耗损振动能介质,利用压力传感器实时检测振动力的变换,自动调节电磁作用力,使系统具有自适应调整减震的能力.通过ANSYS对系统电磁部分进行性能仿真,分析该系统的力学性能和电磁性能,并阐述了系统设计方案.仿真分析表明,在相同载荷和冲击力条件下,混合式智能减震系统与一般筒式液压减震系统相比,不仅减震性能好,同时具备自动化柔性减震功能,能够满足较差路况的减震需求,使摩托车行驶更加平稳.能耗分析表明,在连续振动冲击下,使用7Ah蓄电池给系统供电,系统能够有效工作5.4h,完全能够满足实际使用需要.%A hybrid intelligent shock absorption system that uses spring and electromagnet as the basis and air damping as the vibration loss medium is designed to improve the shock absorption efficiency under poor road conditions and to increase smooth driving and riding comfort .A pressure sensor is used to realize a re‐al‐time test of vibration change and automatically regulate the electromagnetic force to get a self‐adapting shock absorbing system .The electromagnetics performance of the system is simulated through ANSYS to analyze its mechanical property and electromagnetic performance and to expound the system design scheme .The simulation analysis indicates that with the same load and impact ,the hybrid intelligent shock absorption system shows better performance and excellences than the commonly used cylindrical hydraulic shock absorbers ,and it has automatic flexible shock absorption to meet the need of smooth driving under poor road conditions .The energy consumption analysis indicates that this system can work effectively for 11 h under a

  17. Stably superhydrophobic (IL/TiO{sub 2}){sub n} hybrid films: Intelligent self-cleaning materials

    Energy Technology Data Exchange (ETDEWEB)

    Xin, Bingwei, E-mail: bingweixin2@163.com; Wang, Limei; Jia, Chunxiao

    2015-12-01

    Graphical abstract: - Highlights: • Stably superhydrophobic hybrid nanocomposite films. • Ionic liquids mediated thin film with controlled wetting property. • Layer-by-layer self-assembled nanostructures. • Synergistic effect between ionic liquids and titanium dioxide nanoparticles. • Self-cleaning surfaces. - Abstract: Stably self-cleaning (IL/TiO{sub 2}){sub n} nanocomposites were prepared via electrostatic layer-by-layer (LbL) self-assembly technique. Positively charged [C{sub 12}mim]Br and negatively charged TiO{sub 2} nanoparticles were alternatively adsorbed on the negative glass substrates to form (IL/TiO{sub 2}){sub n} layers. They were characterized by scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS) and UV–vis absorption spectroscopy. Under the synergistic action of ionic liquids and TiO{sub 2} P25, in which TiO{sub 2} nanoparticles provided surface roughness while [C{sub 12}mim]Br acted as lower surface tension material, glass coated with 13 bilayers of [C{sub 12}mim]Br/TiO{sub 2} film arrived to superhydrophobicity with 151.7 ± 2°. Owing to the photoresponsive and photocatalytic properties of TiO{sub 2}, (IL/TiO{sub 2}){sub n} nanocomposites achieved the reversible superhydrophobic and superhydrophilic transition upon alternating UV irradiation and storage in the dark, and presented good performance for photocatalytic degradation of methyl orange with ultraviolet (UV) illumination. Significantly, they could be recycled for several times without obvious fatigue.

  18. 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.

  19. An improved hybrid intelligent extreme learning machine%一种新的混合智能极限学习机

    Institute of Scientific and Technical Information of China (English)

    林梅金; 罗飞; 苏彩红; 许玉格

    2015-01-01

    An improved hybrid intelligent algorithm based on differential evolution(DE) and particle swarm optimization (PSO) is proposed. The performance of DEPSO algorithm is verified by simulations on 10 benchmark functions. Then, an improved learning algorithm named DEPSO extreme learning machine(DEPSO-ELM) algorithm for single hidden layer feedforward networks(SLFNs) is proposed. In DEPSO-ELM, DEPSO is used to optimize the network hidden node parameters, and ELM is used to analytically determine the output weights. Simulation results of 6 real world datasets regression problems show that the DEPSO-ELM algorithm performs better than DE-ELM and SaE-ELM. Finally, the effectiveness of the DEPSO-ELM algorithm is verified in the prediction of NC machine tool thermal errors.%提出一种基于差分进化(DE)和粒子群优化(PSO)的混合智能方法—–DEPSO算法,并通过对10个典型函数进行测试,表明DEPSO算法具有良好的寻优性能。针对单隐层前向神经网络(SLFNs)提出一种改进的学习算法—–DEPSO-ELM算法,即应用DEPSO算法优化SLFNs的隐层节点参数,采用极限学习算法(ELM)求取SLFNs的输出权值。将DEPSO-ELM算法应用于6个典型真实数据集的回归计算,并与DE-ELM、SaE-ELM算法相比,获得了更精确的计算结果。最后,将DEPSO-ELM算法应用于数控机床热误差的建模预测,获得了良好的预测效果。

  20. 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 %.

  1. Artificial intelligence in medicine.

    Science.gov (United States)

    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 different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

  2. 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.

  3. Optimization of fractional PID controller based on hybrid computation intelligent learning algorithm%基于混合计算智能的分数阶PID控制器参数优化

    Institute of Scientific and Technical Information of China (English)

    毛书军; 盛贤君

    2014-01-01

    In order to solve the challenging problem of optimization of five-dimensional parameters in fractional PID controller, based on the introduction of swarm intelligence algorithm and evolutionary computing, a hybrid computation intelligent learning algorithm was proposed, which combined Glowworm Swarm Optimization ( GSO) with Genetic Algorithm ( GA) . The hybrid algorithm was based on the swarm intelligence and individual evolution of creatures, which can greatly increase the accuracy of optimization and ensure that algorithm evolves to optimum. A series of experiments verify that the proposed hybrid algorithm can shorten the time of computing and increase the accuracy of simulation.%为解决分数阶PID控制器五维参数优化的难题,设计了一种把萤火虫算法和遗传算法相结合的混合计算智能算法,阐述了计算智能中的群智能算法和进化计算的基本原理和数学算法。该方法基于生物的群体智能和个体进化相结合的思想,能够有效地提高寻优精度,并使算法向最优方向不断进化。经过仿真验证,混合算法在分数阶PID参数整定方面具有运算时间短、仿真精度高等优点。

  4. 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

  5. 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

  6. A Hybrid Intelligent Early Warning System for Predicting Economic Crises: a Case of China%我国宏观经济智能预警系统的构建

    Institute of Scientific and Technical Information of China (English)

    贺星星

    2011-01-01

    将神经网络理论、模糊系统理论和时间序列分析相结合,构建我国宏观经济综合动态智能预警系统;通过1999年至2009年季度数据的输入,对2010年我国宏观经济进行尝试性预测,并对模型进行稳健性检验.%This paper combines artificial neural networks (ANN), fuzzy optimization and time-series econometric models in one unified framework to form a hybrid intelligent early warning system (EWS) for predicting economic crises. Using quarterly data on 12 macroeconomic and financial variables for the Chinese economy from 1999 to 2008, the paper finds that the hybrid model pessesses strong predictive power and the likelihood of economic crises in China during 2009 and 2010 remains high.

  7. 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.

  8. Some issues for discipline of intelligence science

    Institute of Scientific and Technical Information of China (English)

    CAI Zi-xing

    2006-01-01

    The general frame for the system of intelligence science was proposed, the common features of the researching objects of the intelligence science were summarized. The intelligence science consists of three portions:scientific foundation, technical methodology and application fields. The common features of intelligence science include complexity, intersection, nonlinearity, anthropomorphic property, uncertainty, incompleteness and distribution etc. The new proposed scientific branch would reflect the new height, new thought and new way for developing the control science and intelligent systems from one angle, and present a strong wish for establishing a new branch of intelligence science.

  9. Hybridization of Response Surface Methodology and Genetic Algorithm optimization for CO2 laser cutting parameter on AA6061 material

    Directory of Open Access Journals (Sweden)

    A.Parthiban

    2014-03-01

    Full Text Available Investigation of laser cutting parameters on aluminium alloy (AA6061 is important due to its high reflectivity and thermal conductivity. Generally Aluminium alloy is a widely used material in aeronautical and automation industries for its inherent properties. Although the main problem during laser cutting is occurrence of recasting layer and laser beam incidence that affecting the cutting quality is known as kerf dimensions. In a sense the relationship between the laser cutting parameters such as laser power, cutting speed, gas pressure and focal position with kerf dimensions are having important role in laser cutting operation. So this work considers the response surface methodology (RSM, for making empirical relationship between dependent and independent variables. Simultaneously, this work reveals that laser power, cutting speed, gas pressure and focal position have significant effects on kerf dimension. Thus the development of empirical model and the selection of best parameters are important for manufacturing industries. Hence this work develops the statistical model with RSM and optimizes the cutting parameters with genetic algorithm (GA.

  10. 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

  11. Attention and Intelligence.

    Science.gov (United States)

    Lewis, Michael; Brooks-Gunn, Jeanne

    1981-01-01

    The authors discuss methodological and theoretical issues in psychological investigations of infant attention, fixation times, habituation, and intelligence. A consensus on how to measure individual differences in habituation has not been reached. The relation between IQ and attention is discussed. (RD)

  12. 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

  13. Business intelligence

    Directory of Open Access Journals (Sweden)

    Cebotarean Elena

    2011-02-01

    Full Text Available Business intelligence (BI refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes. BI technologies provide historical, current, and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, business performance management, benchmarking, text mining, and predictive analytics. Business intelligence aims to support better business decision-making. Thus a BI system can be called a decision support system (DSS. Though the term business intelligence is sometimes used as a synonym for competitive intelligence, because they both support decision making, BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors. Business intelligence understood broadly can include the subset of competitive intelligence.

  14. Artificial Intelligence.

    Science.gov (United States)

    Waltz, David L.

    1982-01-01

    Describes kinds of results achieved by computer programs in artificial intelligence. Topics discussed include heuristic searches, artificial intelligence/psychology, planning program, backward chaining, learning (focusing on Winograd's blocks to explore learning strategies), concept learning, constraint propagation, language understanding…

  15. 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.

  16. 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.

  17. 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…

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  2. 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)

  3. Time estimation predicts mathematical intelligence.

    Directory of Open Access Journals (Sweden)

    Peter Kramer

    Full Text Available BACKGROUND: Performing mental subtractions affects time (duration estimates, and making time estimates disrupts mental subtractions. This interaction has been attributed to the concurrent involvement of time estimation and arithmetic with general intelligence and working memory. Given the extant evidence of a relationship between time and number, here we test the stronger hypothesis that time estimation correlates specifically with mathematical intelligence, and not with general intelligence or working-memory capacity. METHODOLOGY/PRINCIPAL FINDINGS: Participants performed a (prospective time estimation experiment, completed several subtests of the WAIS intelligence test, and self-rated their mathematical skill. For five different durations, we found that time estimation correlated with both arithmetic ability and self-rated mathematical skill. Controlling for non-mathematical intelligence (including working memory capacity did not change the results. Conversely, correlations between time estimation and non-mathematical intelligence either were nonsignificant, or disappeared after controlling for mathematical intelligence. CONCLUSIONS/SIGNIFICANCE: We conclude that time estimation specifically predicts mathematical intelligence. On the basis of the relevant literature, we furthermore conclude that the relationship between time estimation and mathematical intelligence is likely due to a common reliance on spatial ability.

  4. 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

  5. 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...

  6. 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...

  7. Swarm Intelligence

    OpenAIRE

    Thampi, Sabu M.

    2009-01-01

    Biologically inspired computing is an area of computer science which uses the advantageous properties of biological systems. It is the amalgamation of computational intelligence and collective intelligence. Biologically inspired mechanisms have already proved successful in achieving major advances in a wide range of problems in computing and communication systems. The consortium of bio-inspired computing are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial i...

  8. 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

  9. 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.

  10. THE ROLE OF WORKER'S MULTIPLE INTELLIGENCES ON THEIR PRODUCTIVITY IN CULTURAL INSTITUTIONS OF MOGHAN

    Directory of Open Access Journals (Sweden)

    Mir Hossein Seyyedi

    2011-10-01

    Full Text Available The main focus of this study is Cultural Institutions of Moghan region in Iran. The theory of multiple intelligences was developed in 1983 by Howard Gardner. He suggests that the traditional notion of intelligence, based on I.Q. testing, is far too limited. Instead, Dr. Gardner proposes eight different intelligences to account for a broader range of human potential in children and adults. These intelligences are linguistic intelligence, logical intelligence, spatial intelligence, bodily intelligence, musical intelligence, interpersonal intelligence, intrapersonal intelligence and Naturalist intelligence. The purpose of this research is surveying of relationship between multiple intelligences and productivity of Cultural Institutions workers in Moghan. The methodology of study is descriptive and analytical study. Data collection instrument was a questionnaire that its reliability was confirmed by Crohn Bach’s alpha and library studies. The results show that, there is a relationship between multiple intelligences and productivity of Cultural Institutions workers in Moghan.

  11. 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....

  12. 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…

  13. 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…

  14. 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....

  15. 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...

  16. 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

  17. 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

  18. 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.

  19. 风电—抽蓄—海水淡化综合系统及其智能控制%Intelligent control of hybrid wind-pumped storage-desalination system

    Institute of Scientific and Technical Information of China (English)

    任岩; 郑源; 陈德新; 李冲

    2012-01-01

    我国很多海岛地处偏远,电网很难达到,为解决海岛的用电用水问题,提出了风力发电—抽水蓄能—海水淡化综合系统。建立了系统的数学模型,并对系统进行智能控制,搭建了控制系统硬件平台,提出了智能控制策略,利用VC#2008软件建立了可视化的主控平台,将系统的数据采集、数据检测、控制、数据后处理、数据报表打印等集成在一个交互平台。利用该控制系统可以对风力发电—抽水蓄能—海水淡化综合系统进行实时监测,并通过对实时数据的处理判断系统的运行状态,对综合系统进行智能调度,确保了综合系统运行的高效性和可靠性。将该系统用于海岛,能充分利用当地丰富的风能资源解决海岛用电用水的问题,通过对其进行智能控制,可以实现整个系统的无人值班。%Many islands in our country are far away where power supply by the grid is too difficult.To solve the problems of electricity and freshwater uses in these areas,a hybrid wind-pumped storage-desalination system was brought forward recent years.In the present work,a mathematical model of such hybrid systems was developed and a hardware platform of control system was built.The focus was to study intelligent control of the system and formulate a practical control strategy.By using VC 2008,a visual interactive platform was established as a central control for data collection,data examination,control,data post-processing,data report-forms,data mimeograph and so on,and it was applied to real-time monitoring of the hybrid system.Through analysis of the real-time data and estimation of the system′s operating state,intelligent dispatching schemes have been formulated to assure efficiency and reliability of system operation.The system,if built on an island,can make use of the local abundant wind energy and the adoption of intelligent control system provides the island with self-service of electricity and

  20. Business intelligence

    National Research Council Canada - National Science Library

    Cebotarean Elena

    2011-01-01

    Business intelligence (BI) refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes...

  1. 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...

  2. 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…

  3. Hybrid centralized pre-computing/local distributed optimization of shared disjoint-backup path approach to GMPLS optical mesh network intelligent restoration

    Science.gov (United States)

    Gong, Qian; Xu, Rong; Lin, Jintong

    2004-04-01

    Wavelength Division Multiplexed (WDM) networks that route optical connections using intelligent optical cross-connects (OXCs) is firmly established as the core constituent of next generation networks. Rapid failure recovery is fundamental to building reliable transport networks. Mesh restoration promises cost effective failure recovery compared with legacy ring networks, and is now seeing large-scale deployment. Many carriers are migrating away from SONET ring restoration for their core transport networks and replacing it with mesh restoration through "intelligent" O-E-O cross-connects (XC). The mesh restoration is typically provided via two fiber-disjoint paths: a service path and a restoration path. this scheme can restore any single link failure or node failure. And by used shared mesh restoration, although every service route is assigned a restoration route, no dedicated capacity needs to be reserved for the restoration route, resulting in capacity savings. The restoration approach we propose is Centralized Pre-computing, Local Distributed Optimization, and Shared Disjoint-backup Path. This approach combines the merits of centralized and distributed solutions. It avoids the scalability issues of centralized solutions by using a distributed control plane for disjoint service path computation and restoration path provisioning. Moreover, if the service routes of two demands are disjoint, no single failure will affect both demands simultaneously. This means that the restoration routes of these two demands can share link capacities, because these two routes will not be activated at the same time. So we can say, this restoration capacity sharing approach achieves low restoration capacity and fast restoration speed, while requiring few control plane changes.

  4. Intelligent Sensors Security

    Directory of Open Access Journals (Sweden)

    Andrzej Bialas

    2010-01-01

    Full Text Available The paper is focused on the security issues of sensors provided with processors and software and used for high-risk applications. Common IT related threats may cause serious consequences for sensor system users. To improve their robustness, sensor systems should be developed in a restricted way that would provide them with assurance. One assurance creation methodology is Common Criteria (ISO/IEC 15408 used for IT products and systems. The paper begins with a primer on the Common Criteria, and then a general security model of the intelligent sensor as an IT product is discussed. The paper presents how the security problem of the intelligent sensor is defined and solved. The contribution of the paper is to provide Common Criteria (CC related security design patterns and to improve the effectiveness of the sensor development process.

  5. Intelligent Sensors Security

    Science.gov (United States)

    Bialas, Andrzej

    2010-01-01

    The paper is focused on the security issues of sensors provided with processors and software and used for high-risk applications. Common IT related threats may cause serious consequences for sensor system users. To improve their robustness, sensor systems should be developed in a restricted way that would provide them with assurance. One assurance creation methodology is Common Criteria (ISO/IEC 15408) used for IT products and systems. The paper begins with a primer on the Common Criteria, and then a general security model of the intelligent sensor as an IT product is discussed. The paper presents how the security problem of the intelligent sensor is defined and solved. The contribution of the paper is to provide Common Criteria (CC) related security design patterns and to improve the effectiveness of the sensor development process. PMID:22315571

  6. 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.

  7. Competitive Intelligence: methodology applied in Brazilian companies

    OpenAIRE

    2012-01-01

    Introdução: Apresenta um panorama acerca da Inteligência Competitiva no contexto das organizações brasileiras. Objetivo: Investiga a existência de metodologias de Inteligência Competitiva aplicadas a organizações nacionais e multinacionais de diferentes segmentos de mercado. Metodologia: Revisão de literatura nacional e internacional – envolvendo o status quo da atividade de Inteligência Competitiva no mundo – e cujo conteúdo foi confrontado com os resultados obtidos em entrevistas realizadas...

  8. 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.  .

  9. The Random Fuzzy Multi-objective Assignment Problem Based on A Hybrid Intelligent Algorithm%基于混合智能算法的随机模糊多目标指派问题

    Institute of Scientific and Technical Information of China (English)

    肖继先; 寇春蕾

    2015-01-01

    文中从不确定理论出发,将随机模糊约束规划理论引入对随机模糊多目标指派问题的研究。构建了多目标指派问题的随机模糊规划机会约束模型,并设计了将随机模糊模拟、神经网络和遗传算法结合在一起的混合智能算法对模型进行求解。%This paper based on the uncertainty theory,put the theory of random fuzzy constraint programming introduce into the study of random fuzzy multi-objective assignment problem.Build random fuzzy planning opportunities constraint model of the Multi -objective Assignment problem.And design a hybrid intelligent algorithm, which combined the random fuzzy simulation,neural network and genetic algorithm,to solve the model.

  10. 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...

  11. Návrh agilní metodiky pro Business Intelligence projekty

    OpenAIRE

    Huňáček, Tomáš

    2015-01-01

    This master's thesis deals with the topic of designing an agile methodology for Business Intelligence projects. The thesis presents the topic of Business Intelligence, methodologies for managing projects and methodologies for data warehouse development. It presents Scrum, BEAM* and Data Vault methodologies as well as approaches like pomodoro, Action Centered Leadership and a 40-hour work week. Based on synthesis of presented methodologies and approaches this thesis defines the methodology for...

  12. 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

  13. 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

  14. Type-2 Fuzzy Logic in Intelligent Control Applications

    CERN Document Server

    Castillo, Oscar

    2012-01-01

    We describe in this book, hybrid intelligent systems based mainly on type-2 fuzzy logic for intelligent control. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. The book is organized in three main parts, which contain a group of chapters around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which can be the basis for achieving intelligent control with interval type-2 fuzzy logic. The second part of the book is comprised of chapters with the main theme of evolutionary optimization of type-2 fuzzy systems in intelligent control with the aim of designing optimal type-2 fuzzy controllers for complex control problems in diverse areas of application, including mobile robotics, aircraft dynamics systems and hardware implementations. Th...

  15. 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.

  16. Civic Intelligence.

    Science.gov (United States)

    Mathews, David

    1985-01-01

    Social studies must educate students to be socially responsible, civically competent persons. In addition to encouraging civic literacy, civic values, and civic skill, teachers need to help students develop civic-mindedness. The objective of the NCSS' National Issues Forum in the Classroom Project is to develop students' civic intelligence. (RM)

  17. 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.

  18. Ambient intelligence

    OpenAIRE

    Sanders, David; Gegov, Alexander

    2006-01-01

    This paper considers some history and the state of the art of Ambient Intelligence and from that seeks to identify new topics and future work. Ubiquitous computing, communications, human-centric computer interaction, embedded systems, context awareness, adaptive systems and distributed device networks are considered.

  19. Physical Intelligence and Thermodynamic Computing

    Directory of Open Access Journals (Sweden)

    Robert L. Fry

    2017-03-01

    Full Text Available This paper proposes that intelligent processes can be completely explained by thermodynamic principles. They can equally be described by information-theoretic principles that, from the standpoint of the required optimizations, are functionally equivalent. The underlying theory arises from two axioms regarding distinguishability and causality. Their consequence is a theory of computation that applies to the only two kinds of physical processes possible—those that reconstruct the past and those that control the future. Dissipative physical processes fall into the first class, whereas intelligent ones comprise the second. The first kind of process is exothermic and the latter is endothermic. Similarly, the first process dumps entropy and energy to its environment, whereas the second reduces entropy while requiring energy to operate. It is shown that high intelligence efficiency and high energy efficiency are synonymous. The theory suggests the usefulness of developing a new computing paradigm called Thermodynamic Computing to engineer intelligent processes. The described engineering formalism for the design of thermodynamic computers is a hybrid combination of information theory and thermodynamics. Elements of the engineering formalism are introduced in the reverse-engineer of a cortical neuron. The cortical neuron provides perhaps the simplest and most insightful example of a thermodynamic computer possible. It can be seen as a basic building block for constructing more intelligent thermodynamic circuits.

  20. Design of Wind and Solar Energy Hybrid Micro Grid Intelligent Terminal%风光互补微电网智能测控终端的设计

    Institute of Scientific and Technical Information of China (English)

    吕继伟; 向驰; 付永长; 周振华; 宋春亮

    2012-01-01

    为了集中采集微网系统实时运行数据,并且对微网系统进行协调控制以及对蓄电池充放电进行有效管理,设计了微网智能测控终端。测控终端结构简单、运行可靠,硬件上采用高性能的ADSP—BF518数字信号处理芯片和高精度同步采样模数转换芯片AD7606,从而实现数据集中采集功能,并采用基于短期负荷预测的储能控制策略实现蓄电池管理。测控终端通过通信网络可以及时向监控中心上传数据,并能够接受中心下发遥控指令对微网系统进行控制。工程实践表明,该设计在微网实时监测与集中控制方面效果明显。%This paper proposes the intelligent terminal design just for measuring and sampling the real-time voltage and current data of micro grid, realization for coordinated control of micro grid and battery management. The terminal possesses the simple structure and reliable operation. The paper gives the use of high performance about ADSP - BFS18 and the measurement chip AD7606 on hardware design. The control strategy based on short-term load forecasting has been adopted in the energy storage and battery management system. The terminal can upload the sampled data and accept remote commands through the GPRS communication network. Engineering results show that the design is accurate and reliable in terms of micro grid measurement and control.

  1. Sustainable Energy Solutions Task 4.1 Intelligent Manufacturing of Hybrid Carbon-Glass Fiber-Reinforced Composite Wind Turbine Blades

    Energy Technology Data Exchange (ETDEWEB)

    Twomey, Janet M. [Wichita State Univ., KS (United States)

    2010-04-30

    In this subtask, the manufacturability of hybrid carbon-glass fiber-reinforced composite wind turbine blades using Vacuum-Assisted Resin Transfer Molding (VARTM) was investigated. The objective of this investigation was to study the VARTM process and its parameters to manufacture cost-effective wind turbine blades with no defects (mainly eliminate dry spots and reduce manufacturing time). A 2.5-dimensional model and a 3-dimensional model were developed to simulate mold filling and part curing under different conditions. These conditions included isothermal and non-isothermal filling, curing of the part during and after filling, and placement of injection gates at different locations. Results from this investigation reveal that the process can be simulated and also that manufacturing parameters can be optimized to eliminate dry spot formation and reduce the manufacturing time. Using computer-based models is a cost-effective way to simulate manufacturing of wind turbine blades. The approach taken herein allows the design of the wind blade manufacturing processes without physically running trial-and-error experiments that are expensive and time-consuming; especially for larger blades needed for more demanding environmental conditions. This will benefit the wind energy industry by reducing initial design and manufacturing costs which can later be passed down to consumers and consequently make the wind energy industry more competitive.

  2. 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.

  3. Intelligence Course Scheduling System Based on Hybrid Algorithm%基于混合算法的智能排课系统

    Institute of Scientific and Technical Information of China (English)

    赵耀锋

    2011-01-01

    传统采用单一排课算法设计的排课系统,编排出的课程表总是与期望结果相差太大.为了使课表编排结果能满足教学要求,在此对排课约束条件进行了详细分析,采用基于遗传算法和贪婪算法的混合算法进行排课系统设计,将排课分为时间安排和地点安排2部分进行,时间安排采用遗传算法设计,地点安排采用贪婪算法设计,时间安排和地点安排过程可以人工干预,编排的课程表基本符合教务管理需求.混合算法设计的智能排课系统编排的课程表更加科学化、合理化和人性化.%The school timetable generated by the traditional course scheduling system designed with the single course scheduling algorithm is far from the expeetation. In order to make the result of course scheduling satisfy the teaching requirements, the constraint condition of course scheduling is analyzed. The hybrid algorithm based on the genetic algorithms and greedy algorithm is adopted to design the course scheduling system. The caurse scheduling is divided into time arrangement and classroom arrangement. The former is designed with genetic algorithms and the later with greedy algorithm. The process of both arrangements can be intervened manually. The school timetable designed in this way can basically meet the requirements of teaching management, and is more scientific, rational and humanized.

  4. 基于混合智能算法的电力系统经济负荷分配%Economic Load Dispatch of Power System Based on Hybrid Intelligent Algorithm

    Institute of Scientific and Technical Information of China (English)

    周广闯; 陈璟华; 郭壮志; 潘帅; 刘春香

    2014-01-01

    为解决复杂、不连续、不可导、非线性的电力系统经济负荷分配(economic load dispatch,ELD)问题,提出粒子群算法(particle swarm optimization,PSO)结合单纯形算法(simplex method,NM)的混合智能算法(simplex method-particle swarm optimization,NMPSO)。利用NMPSO解决ELD问题时,综合考虑了发电机组的阀点效应和系统网损,使ELD更接近实际情况,充分利用 PSO 随机性的全局寻优能力和 NM快速确定性的局部寻优能力,弥补了 PSO和NM分别单独应用时的不足。仿真结果表明,NMPSO应用于 ELD 问题,具有较好的优化效果。%For solving problem of economic load dispatch of complex,discontinuous,unguided and nonlinear power system,a kind of hybrid intelligent algorithm combining particle swarm optimization and simplex method was proposed.When using NMPSO to solve ELD problem,valve point effect and system transmission losses of the generator unit were comprehensively considered which made ELD more closely approximate to physical truth.By fully using global optimization of PSO random and partial optimization of NM rapid certainty,it was able to make up shortages of independent PSO and NM.Simulation results indicated that application of NMPSO in ELD was of better optimization effect.

  5. Team B Intelligence Coups

    Science.gov (United States)

    Mitchell, Gordon R.

    2006-01-01

    The 2003 Iraq prewar intelligence failure was not simply a case of the U.S. intelligence community providing flawed data to policy-makers. It also involved subversion of the competitive intelligence analysis process, where unofficial intelligence boutiques "stovepiped" misleading intelligence assessments directly to policy-makers and…

  6. 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.

  7. 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.

  8. On the Working Definition of Intelligence

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    This paper is about the philosophical and methodological foundation of artificial intelligence (AI). After discussing what is a good "working definition", "intelligence" is defined as "the ability for an information processing system to adapt to its environment with insuffcient knowledge and resources". Applying the definition to a reasoning system, we get the major components of Non-Axiomatic Reasoning System (NARS) , which is a symbolic logic implemented in a computer system, and has many interesting ...

  9. 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.

  10. Intelligence Revisited

    Science.gov (United States)

    2005-05-01

    environment (i.e., culture , class, family, educational 2 Chapter 23 Intelligence Revisited opportunities, gender) shapes our intellect, and there are no...connectivity is going to be rather problematic, to say the least. A single nano-bot cruising this Disneyland of synaptic wonderment is certainly... cultures ). Embodiment – A sense of being anchored to our physical bodies. Agency – A sense of free will, wherein we are in charge of our own

  11. 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...

  12. Computational Intelligence and Its Encoding Mechanism

    Institute of Scientific and Technical Information of China (English)

    LIU Man-dan

    2004-01-01

    The origin and characteristics of computational intelligence, and several typical computational intelligence algorithms such as genetic algorithm and DNA computing are described, and the influence of evolution strategies and convergence properties on the encoding mechanism is discussed. A novel genetic algorithm based on degressive carry number encoding is then proposed. This algorithm uses degressive carry number encoding in the evolutionary process instead of commonly used fixed carry number. Finally a novel encoding mechanism and a new algorithm are proposed, which combine modern computational intelligence with the traditional Chinese methodology.

  13. Computational Intelligence and Its Encoding Mechanism

    Institute of Scientific and Technical Information of China (English)

    LIUMan-dan

    2004-01-01

    The origin and characteristics of computational intelligence, and several typical computational intelligence algorithms such as genetic algorithm and DNA computing are described, and the influence of evolution strategies and convergence properties on the encoding mechanism is discussed. A novel genetic algorithm based on degressive carry number encoding is then proposed. This algorithm uses degressive carry number encoding in the evolutionary process instead of commonly used fixed carry number. Finally a novel encoding mechanism and a new algorithm are proposed, which combine modem computational intelligence with the traditional Chinese methodology.

  14. The Profit Impact of Business Intelligence

    CERN Document Server

    Williams, Steve

    2006-01-01

    Business Intelligence (BI): It's not just a technology. It's not just a methodology. It's a powerful new management approach that - when done right - can deliver knowledge, efficiency, better decisions, and profit to almost any organization that uses it.When BI first came on the scene, it promised a lot but often failed to deliver. The missing element was the business-centric focus explained in The Profit Impact of Business Intelligence. Written by BI gurus Steve Williams and Nancy Williams, The Profit Impact of Business Intelligence shows step by step how you can achieve the promise of BI by

  15. Trends in Artificial Intelligence.

    Science.gov (United States)

    Hayes, Patrick

    1978-01-01

    Discusses the foundations of artificial intelligence as a science and the types of answers that may be given to the question, "What is intelligence?" The paradigms of artificial intelligence and general systems theory are compared. (Author/VT)

  16. Teaching Intelligence Analysis with TIACRITIS

    Science.gov (United States)

    2010-12-01

    by-doing approach. Recently we have developed Disciple-LTA, a unique and complex cognitive assistant for evidence- based hypothesis analysis which...interaction with experienced intelligence analysts. Indeed, instead of being programmed by a knowledge engineer (which is a very long, difficult and...An Apprenticeship Multistrategy Learning Theory, Methodology, Tool and Case Studies, Academic Press, 1998. http://lac.gmu.edu/publications/1998

  17. Intelligent Real-Time Reservoir Operation for Flood Control

    Science.gov (United States)

    Chang, L.; Hsu, H.

    2008-12-01

    Real-time flood control of a multi-purpose reservoir should consider decreasing the flood peak stage downstream and storing floodwaters for future usage during typhoon seasons. It is a continuous and instant decision-making process based on relevant operating rules, policy and water laws, in addition the immediate rainfall and the hydrology information; however, it is difficult to learn the intelligent experience from the elder operators. The main purpose of this study is to establish the automatic reservoir flood control model to achieve the goal of a reservoir operation during flood periods. In this study, we propose an intelligent reservoir operating methodology for real-time flood control. First, the genetic algorithm is used to search the optimal solutions, which can be considered as extracting the knowledge of reservoir operation strategies. Then, the adaptive network-based fuzzy inference system (ANFIS), which uses a hybrid learning procedure for extracting knowledge in the form of fuzzy if-then rules, is used to learn the input-output patterns and then to estimate the optimal flood operation. The Shihmen reservoir in Northern Taiwan was used as a case study, where its 26 typhoon events are investigated by the proposed method. The results demonstrate that the proposed control model can perform much better than the original reservoir operator in 26 flood events and effectively achieve decreasing peak flood stage downstream and storing floodwaters for future usage.

  18. The Importance of Collective Intelligence Implementing the ‘Third Mission’ of Universities

    Directory of Open Access Journals (Sweden)

    Viktorija Stokaitė

    2015-02-01

    Full Text Available Purpose – transformation of regular traditional university is a natural going process, which was affected not only by attractive theoretical or practical meaning of entrepreneurial university, but by the necessity of economic and social changes, as well. According to that, university is an important member of “Triple Helix” (University-Industry-State model importance of collective intelligence for the implementation and development of “Third Mission” of university hybrid. “Triple Helix” model’s expansion is being proven in the upshot of analysis of scientific literature.Design/Methodology/Approach – analysis of scientific literature.Findings – after literature analysis, the following findings are presented: Concept of “Third Mission”; The importance of entrepreneurial university for “Third Mission’s” implementation is investigated; The importance of collective intelligence for “Third Mission’s” implementation is highlighted.Practical usage – according to the necessity of fast changes for Lithuanian and for East European universities in common, it is being expected that proven importance of collective intelligence for the implementation of “Third Mission” of university will affect the research of unique interdisciplinary solutions.Originality/Value – the main concept of collective intelligence is not really new, but the article explains its value for entrepreneurial university and for implementation of “Third Mission”. The development of hybrid “Triple Helix” model has not been investigated properly yet. Because of this, it is expected that the article will affect the start of new discussions and research of new solutions.Research type – literature review, viewpoint.

  19. 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.

  20. Granular computing analysis and design of intelligent systems

    CERN Document Server

    Pedrycz, Witold

    2013-01-01

    Information granules, as encountered in natural language, are implicit in nature. To make them fully operational so they can be effectively used to analyze and design intelligent systems, information granules need to be made explicit. An emerging discipline, granular computing focuses on formalizing information granules and unifying them to create a coherent methodological and developmental environment for intelligent system design and analysis. Granular Computing: Analysis and Design of Intelligent Systems presents the unified principles of granular computing along with its comprehensive algo

  1. 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.

  2. 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.

  3. 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…

  4. 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…

  5. 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…

  6. Business Intelligence

    OpenAIRE

    Strejčková, Lucie

    2006-01-01

    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. Business Intelligence

    OpenAIRE

    Strejčková, Lucie

    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...

  8. 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.

  9. A Hybrid Intelligent Fault Diagnosis Method and Fault Diagnosis for Diesel Engine%一种混合智能故障诊断方法及柴油机故障诊断

    Institute of Scientific and Technical Information of China (English)

    李恒宾; 马文朋

    2012-01-01

    提出了一种模糊聚类、粗糙集理论与神经网络集成的混合智能故障诊断方法.引入聚类有效性函数和点分布密度函数.对模糊c-均值聚类算法进行改进,形成了自适应模糊聚类算法并依据该算法将连续的故障特征值离散化.应用粗糙集理论处理离散化的故障诊断数据.采用基于信息熵的方法,约简冗余的故障特征.依据约简结果构建神经网络,采用遗传算法优化网络的权值和阈值.将该方法用于柴油机气门故障诊断,并与普通神经网络进行对比.结果表明,该方法提高了故障诊断的正确率.%A hybrid intelligent fault diagnosis method integrating fuzzy clustering, rough sets theory and artificial neural network was proposed. Adaptive fuzzy clustering algorithm was formed by the introduction of cluster validity index and distribution density function of data point to improve fuzzy c-means fuzzy clustering algorithm. And continuous values of fault feature were discretized according the algorithm. Rough sets theory was employed to deal with the fault diagnosis data and redundant features were reduced by the information entropy-based method. Neural networks were established on the basis of reduction, and the weights and biases of which were optimized by genetic algorithm. Applying the method to the fault diagnosis of diesel engine valve and comparing with general neural network , the results indicate that the presented method improves the accuracy of fault diagnosis.

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

    OpenAIRE

    V. sreenivasulu

    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...

  12. Intelligent products : A survey

    NARCIS (Netherlands)

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

    2009-01-01

    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 In

  13. 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...

  14. 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.

  15. 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.

  16. Pathogen intelligence

    Science.gov (United States)

    Steinert, Michael

    2014-01-01

    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 behavior, but also collective sensing, interbacterial communication, distributed information processing, joint decision making, dissociative behavior, 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. PMID:24551600

  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. 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...

  19. Limitations on the Detection Rate of High-Risk HPV by Hybrid Capture 2 Methodology in High Grade Intraepithelial (HSIL or Atypical Squamous Cells-Cannot Exclude HSIL (ASC-H Cytological Lesions with Proved CIN2+

    Directory of Open Access Journals (Sweden)

    Jean-Christophe Noël

    2015-01-01

    Full Text Available Recent literature data suggest that the high-risk human papillomaviruses (HR-HPVs testing with several molecular techniques could be an alternative to cytology in the detection of cervical intraepithelial neoplasias of grade 2 or worse (CIN2+. However, any molecular techniques have its own limits and may give false negative results which must be clearly known before undertaking a primary HPV screening. This study aims to evaluate the performance of the high-risk HPV hybrid capture II detection kit (HCII which is considered as a “gold standard technique” in a series of 100 women having proved both cytological lesions of atypical squamous cells-cannot exclude an HSIL (ASC-H or high-grade squamous intraepithelial lesion (HSIL and histological lesions of CIN2+. The clinical sensitivity of HCII in women with a cytological diagnosis of ASC-H/HSIL and a diagnosis of CIN2+ is high but not absolute and estimated at 96% (95,6% and 100% of women with a diagnosis of CIN2/3 or invasive squamous cell carcinoma, resp.. These data although they are infrequent must be clearly referred before to start an HPV primary screening of CIN2+ especially with HCII methodology.

  20. Hybrid response surface methodology-genetic algorithm optimization of ultrasound-assisted transesterification of waste oil catalysed by immobilized lipase on mesoporous silica/iron oxide magnetic core-shell nanoparticles.

    Science.gov (United States)

    Karimi, Mahmoud; Keyhani, Alireza; Akram, Asadolah; Rahman, Masoud; Jenkins, Bryan; Stroeve, Pieter

    2013-01-01

    The production ofbiodiesel by transesterification of waste cooking oil (WCO) to partially substitute petroleum diesel is one of the measures for solving the twin problems of environment pollution and energy demand. An environmentally benign process for the enzymatic transesterification using immobilized lipase has attracted considerable attention for biodiesel production. Here, a superparamagnetic, high surface area substrate for lipase immobilization is evaluated. These immobilization substrates are composed of mesoporous silica/superparamagnetic iron oxide core-shell nanoparticles. The effects of methanol ratio to WCO, lipase concentration, water content and reaction time on the synthesis of biodiesel were analysed by utilizing the response surface methodology (RSM). A quadratic response surface equation for calculating fatty acid methyl ester (FAME) content as the objective function was established based on experimental data obtained in accordance with the central composite design. The RSM-based model was then used as the fitness function for genetic algorithm (GA) to optimize its input space. Hybrid RSM-GA predicted the maximum FAME content (91%) at the optimum level of medium variables: methanol ratio to WCO, 4.34; lipase content, 43.6%; water content, 10.22%; and reaction time, 6h. Moreover, the immobilized lipase could be used for four times without considerable loss of the activity.

  1. 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...

  2. DIFFERENCES IN SOCIAL AND MACHIAVELLIAN INTELLIGENCE BETWEEN THE MANAGEMENT STUDENTS FROM THE CZECH AND SLOVAK REPUBLIC

    Directory of Open Access Journals (Sweden)

    Miroslav Frankovský

    2013-06-01

    Full Text Available Identifying and specifying social and Machiavellian intelligence is related to the broader discussion about the existence of several kinds of intelligence. When characterizing these two particular types it is inevitable to take a broader social context defining them into account. In the report we present the results of comparisons of assessing the selected attributes of social and Machiavellian intelligence by the management students from Czech Republic and Slovakia by means of the TSIS methodology, Mach IV and EMESI - an own methodology for detecting social intelligence. The presented comparisons are based on the influence of the macrosocial and microsocial environments on perception of the studied types of intelligence. This comparative analysis is connected also to the theoretical and methodological verification of the original methodology for measuring social intelligence - EMESI.

  3. 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…

  4. 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…

  5. Emotional Intelligence Meets Traditional Standards for an Intelligence.

    Science.gov (United States)

    Mayer, John D.; Caruso, David R.; Salovey, Peter

    1999-01-01

    Results of 2 studies involving 503 adults and 229 adolescents show that emotional intelligence, as measured by the Multifactor Emotional Intelligence Scale, a new ability test of emotional intelligence, meets 3 classical criteria of a standard intelligence. (SLD)

  6. Distributed intelligent systems for substation automation - New methodology to manage the distribution networks in the presence of decentralized generation; Intelligence decentralisee appliquee a l'automatisation de sous-stations. Nouvelle methodologie pour gerer les reseaux de distribution en presence de production decentralisee

    Energy Technology Data Exchange (ETDEWEB)

    Yuen, Ch. [ABB Switzerland Ltd., Baden-Daettwil (Switzerland)

    2010-07-01

    This article describes a new concept for electric network management, developed by ABB Ltd. in co-operation with seven universities and two electric network utilities. This is a British project the aim of which is the distributed management of regional sub-networks by means of distributed control and intelligence. These network parts include intelligent devices, demand management, storage units and sub-stations and are widely autonomous. Such a new concept is required in particular due to increasing share of renewable energy sources in power generation. Moreover, most of these new generators deliver power in a stochastic way. The article explains the basic principles of the concept and describes the status of the project.

  7. 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.

  8. Tourism Methodologies

    DEFF Research Database (Denmark)

    This volume offers methodological discussions within the multidisciplinary field of tourism and shows how tourism researchers develop and apply new tourism methodologies. The book is presented as an anthology, giving voice to many diverse researchers who reflect on tourism methodology in different...... in interview and field work situations, and how do we engage with the performative aspects of tourism as a field of study? The book acknowledges that research is also performance and that it constitutes an aspect of intervention in the situations and contexts it is trying to explore. This is an issue dealt...

  9. 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…

  10. Inverting the Army Intelligence Pyramid

    Science.gov (United States)

    2011-05-19

    Counterinsurgency, Company Intelligence Support Team, COIST, HUMINT, SIGINT, MASINT, OSINT 16. SECURITY CLASSIFICATION OF: (U) 17. LIMITATION OF...intelligence ( OSINT ), signals intelligence (SIGINT), and technical intelligence (TECHINT).14 11

  11. Hybrid partial least squares and neural network approach for short-term electrical load forecasting

    Institute of Scientific and Technical Information of China (English)

    Shukang YANG; Ming LU; Huifeng XUE

    2008-01-01

    Intelligent systems and methods such as the neural network (NN) are usually used in electric power systems for short-term electrical load forecasting. However, a vast amount of electrical load data is often redundant, and linearly or nonlinearly correlated with each other. Highly correlated input data can result in erroneous prediction results given out by an NN model. Besides this, the determination of the topological structure of an NN model has always been a problem for designers. This paper presents a new artificial intelligence hybrid procedure for next day electric load forecasting based on partial least squares (PLS) and NN. PLS is used for the compression of data input space, and helps to determine the structure of the NN model. The hybrid PLS-NN model can be used to predict hourly electric load on weekdays and weekends. The advantage of this methodology is that the hybrid model can provide faster convergence and more precise prediction results in comparison with abductive networks algorithm. Extensive testing on the electrical load data of the Puget power utility in the USA confirms the validity of the proposed approach.

  12. Hybrid Perturbation methods based on Statistical Time Series models

    CERN Document Server

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

    2016-01-01

    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 a...

  13. 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.

  14. 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.

  15. Intelligence Operations Manual

    Directory of Open Access Journals (Sweden)

    Karla Andrade

    2016-02-01

    Full Text Available This Manual was an important document for the development of intelligence units in El Salvador´s police. It is a guiding document for intelligence operations where relevant aspects on overall information management are detailed.

  16. Intelligent route surveillance

    NARCIS (Netherlands)

    Schoemaker, R.M.; Sandbrink, R.D.J.; Voorthuijsen, G.P. van

    2009-01-01

    Intelligence on abnormal and suspicious behaviour along roads in operational domains is extremely valuable for countering the IED (Improvised Explosive Device) threat. Local sensor networks at strategic spots can gather data for continuous monitoring of daily vehicle activity. Unattended intelligent

  17. Intelligent Computer Graphics 2012

    CERN Document Server

    Miaoulis, Georgios

    2013-01-01

    In Computer Graphics, the use of intelligent techniques started more recently than in other research areas. However, during these last two decades, the use of intelligent Computer Graphics techniques is growing up year after year and more and more interesting techniques are presented in this area.   The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008), “Intelligent Computer Graphics 2009” (2009), “Intelligent Computer Graphics 2010” (2010) and “Intelligent Computer Graphics 2011” (2011).   Usually, this kind of volume contains, every year, selected extended papers from the corresponding 3IA Conference of the year. However, the current volume is made from directly reviewed and selected papers, submitted for publication in the volume “Intelligent Computer Gr...

  18. 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...

  19. 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.

  20. 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 ...

  1. The Frontiers of Intelligence

    OpenAIRE

    Marcus Anthony

    2007-01-01

    The generally accepted theory of intelligence is developed mainly in the framework of the pragmatic critical philosophy. The discussed issues are psychometric and system theory of intelligence. However, the subject of this article are some of the more promising theories which, while remaining within the traditional scientific concepts, describe, in particular, emotional, creative, intrapersonal intelligence and wisdom. Of course, there are other ideas about intelligence. Among them, for examp...

  2. Tests of Machine Intelligence

    CERN Document Server

    Legg, Shane

    2007-01-01

    Although the definition and measurement of intelligence is clearly of fundamental importance to the field of artificial intelligence, no general survey of definitions and tests of machine intelligence exists. Indeed few researchers are even aware of alternatives to the Turing test and its many derivatives. In this paper we fill this gap by providing a short survey of the many tests of machine intelligence that have been proposed.

  3. Construct of emotional intelligence

    OpenAIRE

    Sonja Pečjak in Andreja Avsec

    2003-01-01

    The article highlights the construct of emotional intelligence, that has appeared about then years ago. We present the popular and scientific comprehension of emotional intelligence, briefly describe the development of the concept and than in detail we propose the existing comprehension of emotional intelligence: through the models of Goleman (1995) and Bar-On (1997) we present the comprehension of emotional intelligence as a non-cognitive (personality) traits.

  4. Construct of emotional intelligence

    Directory of Open Access Journals (Sweden)

    Sonja Pečjak in Andreja Avsec

    2003-04-01

    Full Text Available The article highlights the construct of emotional intelligence, that has appeared about then years ago. We present the popular and scientific comprehension of emotional intelligence, briefly describe the development of the concept and than in detail we propose the existing comprehension of emotional intelligence: through the models of Goleman (1995 and Bar-On (1997 we present the comprehension of emotional intelligence as a non-cognitive (personality traits.

  5. 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…

  6. 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…

  7. 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…

  8. Research of IDSS Architecture Based on Hybrid Systems

    Institute of Scientific and Technical Information of China (English)

    MA Biao; YANG Bao-an

    2005-01-01

    This paper discusses the necessity of building IDSS on hybrid systems, and adopts XML technology to manage isomeric knowledge in hybrid systems. The paper proposes a new architecture of hybrid systems based IDSS whose core system is isomeric knowledge system. The architecture is composed of knowledge component, problems processing system, data component and intelligent user interface. This new architecture aims to enhance the capability of integrating hybrid systems, to improve the supporting effectiveness of decision-making and the intelligent level of IDSS, and tries a new way to elevate the system's ability of handling and learning knowledge.

  9. 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.

  10. Creativity and Autonomy in Swarm Intelligence Systems

    OpenAIRE

    al-Rifaie, Mohammad Majid; Bishop,Mark; Caines, Suzanne

    2012-01-01

    This work introduces two swarm intelligence algorithms -- one mimicking the behaviour of one species of ants (\\emph{Leptothorax acervorum}) foraging (a `Stochastic Diffusion Search', SDS) and the other algorithm mimicking the behaviour of birds flocking (a `Particle Swarm Optimiser', PSO) -- and outlines a novel integration strategy exploiting the local search properties of the PSO with global SDS behaviour. The resulting hybrid algorithm is used to sketch novel drawings of an input image, ex...

  11. Speech intelligibility metrics in small unoccupied classrooms

    Science.gov (United States)

    Cruikshank, Matthew E.; Carney, Melinda J.; Cheenne, Dominique J.

    2005-04-01

    Nine small volume classrooms in schools located in the Chicago suburbs were tested to quantify speech intelligibility at various seat locations. Several popular intelligibility metrics were investigated, including Speech Transmission Index (STI), %Alcons, Signal to Noise Ratios (SNR), and 80 ms Useful/Detrimental Ratios (U80). Incorrect STI values were experienced in high noise environments, while the U80s and the SNRs were found to be the most accurate methodologies. Test results are evaluated against the guidelines of ANSI S12.60-2002, and match the data from previous research.

  12. 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"....

  13. 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.

  14. Inverse Kinematics Using Neuro-Fuzzy Intelligent Technique for Robotic Manipulator

    Directory of Open Access Journals (Sweden)

    Shiv Manjaree

    2013-12-01

    Full Text Available Inverse Kinematics of robotic manipulators is a complex task. For higher degree of freedom robotic manipulators, the algebra related to traditional approaches become highly complex. This has led to the usage of artificial intelligence techniques. In this paper, the hybrid combination of Neural Networks and Fuzzy Logic Intelligent Technique has been applied for 3 degree of freedom robotic manipulator. The variations of joint angles obtained in the results show the effective implementation of artificial intelligence.

  15. Measuring Intelligence through Games

    CERN Document Server

    Schaul, Tom; Schmidhuber, Jürgen

    2011-01-01

    Artificial general intelligence (AGI) refers to research aimed at tackling the full problem of artificial intelligence, that is, create truly intelligent agents. This sets it apart from most AI research which aims at solving relatively narrow domains, such as character recognition, motion planning, or increasing player satisfaction in games. But how do we know when an agent is truly intelligent? A common point of reference in the AGI community is Legg and Hutter's formal definition of universal intelligence, which has the appeal of simplicity and generality but is unfortunately incomputable. Games of various kinds are commonly used as benchmarks for "narrow" AI research, as they are considered to have many important properties. We argue that many of these properties carry over to the testing of general intelligence as well. We then sketch how such testing could practically be carried out. The central part of this sketch is an extension of universal intelligence to deal with finite time, and the use of samplin...

  16. Speech intelligibility in hospitals.

    Science.gov (United States)

    Ryherd, Erica E; Moeller, Michael; Hsu, Timothy

    2013-07-01

    Effective communication between staff members is key to patient safety in hospitals. A variety of patient care activities including admittance, evaluation, and treatment rely on oral communication. Surprisingly, published information on speech intelligibility in hospitals is extremely limited. In this study, speech intelligibility measurements and occupant evaluations were conducted in 20 units of five different U.S. hospitals. A variety of unit types and locations were studied. Results show that overall, no unit had "good" intelligibility based on the speech intelligibility index (SII > 0.75) and several locations found to have "poor" intelligibility (SII speech intelligibility across a variety of hospitals and unit types, offers some evidence of the positive impact of absorption on intelligibility, and identifies areas for future research.

  17. Cluster Tree Based Hybrid Document Similarity Measure

    Directory of Open Access Journals (Sweden)

    M. Varshana Devi

    2015-10-01

    Full Text Available hybrid similarity measure is established to measure the hybrid similarity. In cluster tree, the hybrid similarity measure can be calculated for the random data even it may not be the co-occurred and generate different views. Different views of tree can be combined and choose the one which is significant in cost. A method is proposed to combine the multiple views. Multiple views are represented by different distance measures into a single cluster. Comparing the cluster tree based hybrid similarity with the traditional statistical methods it gives the better feasibility for intelligent based search. It helps in improving the dimensionality reduction and semantic analysis.

  18. 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.

  19. INTELMOD - An Intelligent Satellite Modelling Toolkit

    Science.gov (United States)

    Aynsley, M.; Hiden, H.

    This paper describes the development of an intelligent, generic spacecraft modelling toolkit, INTELMOD (INTELligent MODeller). The system has been designed to provide an environment which can efficiently capture spacecraft engineering and operational expertise, coupled with mission or phase-related knowledge. This knowledge can then be applied to support human flight controllers at ESA (European Space Agency) in performing a number of generic monitoring, analytical and diagnostic tasks. INTELMOD has been developed using a RAD (Rapid Application Development) approach, based on the Dynamic Systems Development Methodology (DSDM) and has made extensive use of Commercial Off-The-Shelf (COTS) software products. INTELMOD also incorporates UNiT (Universal Intelligent Toolkit), to provide automatic execution of recovery procedures following fault detection and isolation. Users of INTELMOD require no formal programming experience, as models can be constructed with user-friendly editors that employ a “drag and drop” approach using pre- defined palettes of key components.

  20. 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.

  1. 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 Bi-Objective Genetic Algorithm.

    Science.gov (United States)

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

    2017-03-09

    In this study, Faujasite (FAU) zeolite was coated on low cost tubular ceramic support as a separating layer via 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 by 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 was 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 RSM (Response Surface Methodology) was employed. The predicted models for permeate flux and rejection were further subjected to bi-objective Genetic Algorithm (GA). The hybrid RSM-GA approach resulted 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 in order to know the potential of the fabricated FAU zeolite ceramic-composite membrane.

  2. A Hybrid Wind/Photovoltaic Power Supply System Based on Discrete Probabilistic Methodology%基于离散概率模型的风光互补供电系统优化配置

    Institute of Scientific and Technical Information of China (English)

    叶承晋; 黄民翔; 王焱; 孙飞飞; 钟宇峰

    2013-01-01

    A probabilistic methodology based quantitative capacity optimal configuration method of hybrid wind/photovoltaic power supply system is proposed. A discrete probability distribution model is established to represent the random variables in the system, including the uncertainty of power injections and the random failure of components. A multi-objective optimization model is proposed involving three contradictory objectives: minimization of major investment, power inadequacy and voltage deviation. An innovative probabilistic load flow algorithm is introduced for the purpose of fast probability computing while maintaining a relatively high degree of accuracy, which uses moments to calculate and convert cumulants and Gram-Charlier series to obtain probabilistic distribution functions of target variable. The parallel elitist non-dominated sorting genetic algorithm (PNSGA-Ⅱ) is introduced to search the Pareto-optimal solutions. Finally, a numerical example is provided to validate the applications of the proposed method.%提出了一种基于概率模型的风光互补供电系统定量优化配置方法.该方法用离散概率分布表示系统中的随机变化因素,包括风、光、负荷、补偿装置功率的随机分布和系统元件的随机故障,并且以电能充裕度最大、供电系统总投资和电压越限概率最小作为优化目标建立多目标优化模型.为了更高效、快速地计算各目标函数,文中对随机潮流算法进行部分改进,将离散随机变量的期望值和增量分开研究,并通过矩计算和转化半不变量,运用级数逼近得到节点电压和系统电能裕量的概率分布.采用并行加速的带有精英策略的非支配排序遗传算法(PNSGA-Ⅱ)求解Pareto最优解集,并结合算例分析说明了文中方法的可行性与优势.

  3. 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

  4. Social Intelligence: Next Generation Business Intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Troy Hiltbrand

    2010-09-01

    In order for Business Intelligence to truly move beyond where it is today, a shift in approach must occur. Currently, much of what is accomplished in the realm of Business Intelligence relies on reports and dashboards to summarize and deliver information to end users. As we move into the future, we need to get beyond these reports and dashboards to a point where we break out the individual metrics that are embedded in these reports and interact with these components independently. Breaking these pieces of information out of the confines of reports and dashboards will allow them to be dynamically assembled for delivery in the way that makes most sense to each consumer. With this change in ideology, Business Intelligence will move from the concept of collections of objects, or reports and dashboards, to individual objects, or information components. The Next Generation Business Intelligence suite will translate concepts popularized in Facebook, Flickr, and Digg into enterprise worthy communication vehicles.

  5. Optimizing Classification in Intelligence Processing

    Science.gov (United States)

    2010-12-01

    ACC Classification Accuracy AUC Area Under the ROC Curve CI Competitive Intelligence COMINT Communications Intelligence DoD Department of...indispensible tool to support a national leader’s decision making process, competitive intelligence (CI) has emerged in recent decades as an environment meant...effectiveness for the intelligence product in competitive intelligence environment: accuracy, objectivity, usability, relevance, readiness, and timeliness

  6. The Anatomy of Moral Intelligence.

    Science.gov (United States)

    Boss, Judith A.

    1994-01-01

    Argues that moral intelligence is one of the separate, autonomous multiple intelligences. The essay discusses moral development as a function of cognitive/analytical development, the relationship between moral reasoning and moral conduct, the biological basis of moral intelligence, moral intelligence as a function of social intelligence, and…

  7. 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...

  8. Hybrid Baryons

    CERN Document Server

    Page, P R

    2003-01-01

    We review the status of hybrid baryons. The only known way to study hybrids rigorously is via excited adiabatic potentials. Hybrids can be modelled by both the bag and flux-tube models. The low-lying hybrid baryon is N 1/2^+ with a mass of 1.5-1.8 GeV. Hybrid baryons can be produced in the glue-rich processes of diffractive gamma N and pi N production, Psi decays and p pbar annihilation.

  9. 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.

  10. 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.

  11. Intelligence analysis – the royal discipline of Competitive Intelligence

    National Research Council Canada - National Science Library

    Bartes, František

    ... 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...

  12. Can Intelligence Explode?

    CERN Document Server

    Hutter, Marcus

    2013-01-01

    The technological singularity refers to a hypothetical scenario in which technological advances virtually explode. The most popular scenario is the creation of super-intelligent algorithms that recursively create ever higher intelligences. It took many decades for these ideas to spread from science fiction to popular science magazines and finally to attract the attention of serious philosophers. David Chalmers' (JCS 2010) article is the first comprehensive philosophical analysis of the singularity in a respected philosophy journal. The motivation of my article is to augment Chalmers' and to discuss some issues not addressed by him, in particular what it could mean for intelligence to explode. In this course, I will (have to) provide a more careful treatment of what intelligence actually is, separate speed from intelligence explosion, compare what super-intelligent participants and classical human observers might experience and do, discuss immediate implications for the diversity and value of life, consider po...

  13. Fractionating human intelligence.

    Science.gov (United States)

    Hampshire, Adam; Highfield, Roger R; Parkin, Beth L; Owen, Adrian M

    2012-12-20

    What makes one person more intellectually able than another? Can the entire distribution of human intelligence be accounted for by just one general factor? Is intelligence supported by a single neural system? Here, we provide a perspective on human intelligence that takes into account how general abilities or "factors" reflect the functional organization of the brain. By comparing factor models of individual differences in performance with factor models of brain functional organization, we demonstrate that different components of intelligence have their analogs in distinct brain networks. Using simulations based on neuroimaging data, we show that the higher-order factor "g" is accounted for by cognitive tasks corecruiting multiple networks. Finally, we confirm the independence of these components of intelligence by dissociating them using questionnaire variables. We propose that intelligence is an emergent property of anatomically distinct cognitive systems, each of which has its own capacity.

  14. 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.

  15. Knowledge Intelligence: A New Field in Business Intelligence

    Science.gov (United States)

    Nie, Guangli; Li, Xiuting; Zhang, Lingling; Zhang, Yuejin; Shi, Yong

    This paper discussed the development of business intelligence considering the development of data mining. Business intelligence plays an important role in producing up-to-data information for operative and strategic decision-making. We proposed a new kind of knowledge named intelligent knowledge gotten from data. We illustrated a way to combine the business intelligence and intelligent knowledge and proposed a way of the management of intelligent knowledge which is more structural than the traditional knowledge.

  16. 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

  17. 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

  18. Intelligence Essentials for Everyone

    Science.gov (United States)

    1999-06-01

    Larry Kahaner, Competitive Intelligence : From Black Ops to Boardrooms — How Businesses Gather, Analyze and Use Infor- mation to Succeed in the Global...32744.fm Page 2 Tuesday, June 22, 1999 9:42 AMauthorities. The Society of Competitive Intelligence Professionals...SCIP, Competitive Intelligence Review, 8, No. 3 (Fall 1997), unnumbered 8th page. 5 SCIP, 1995 SCIP Membership Directory (Alexandria, VA: SCIP, 1995

  19. Intelligence Analysis: Once Again

    Science.gov (United States)

    2008-02-01

    least touch on the subject of intelligence analysis. However, while still a large body of work, it is a considerably smaller set that specifically...meaning is influenced by the analyst’s mindset, mental model, or frame of mind . Kent (1949, p. 199) indicated “…an intelligence staff which must...or a top-down process are not unique to the intelligence literature. In the scientific literature, arguments date back to Descartes (1596- 1650

  20. Coping Intelligence: Efficient Life Stress Management

    Science.gov (United States)

    Libin, Elena

    2017-01-01

    Coping Intelligence is defined as efficient individual ways of managing life stress. This paper presents a new assessment instrument named Coping IQ (CIQ; Coping Intelligence Questionnaire). A measure is based on the Multidimensional Positive Coping Model, which includes three cross-cutting parameters that characterize coping strategy as efficient or inefficient, emotional, cognitive or behavioral, and active or passive. Results of the factor analysis verified a basic two-factor structure of the Coping Intelligence with the alternative solutions for efficient and inefficient coping strategies characterized via three basic modalities. The validity of the Coping IQ instrument showed an internal consistency ranging from 0.72 to 0.81. The unified methodology that underlies the new concept of Coping Intelligence, as well as Coping IQ assessment, is applicable for studying both clinical and general populations. CIQ parameters might serve as useful feedback while assessing changes in individual coping repertoire, for CIQ measures strategies that can be modified as a result of life experiences or educational training. Based on the study findings, Coping Intelligence is further defined by a broad repertoire of life skills required to solve successfully everyday stress and life adversities in order to achieve desired goals and maintain physical, mental, and social well-being.

  1. Computation and design of autonomous intelligent systems

    Science.gov (United States)

    Fry, Robert L.

    2008-04-01

    This paper describes a theory of intelligent systems and its reduction to engineering practice. The theory is based on a broader theory of computation wherein information and control are defined within the subjective frame of a system. At its most primitive level, the theory describes what it computationally means to both ask and answer questions which, like traditional logic, are also Boolean. The logic of questions describes the subjective rules of computation that are objective in the sense that all the described systems operate according to its principles. Therefore, all systems are autonomous by construct. These systems include thermodynamic, communication, and intelligent systems. Although interesting, the important practical consequence is that the engineering framework for intelligent systems can borrow efficient constructs and methodologies from both thermodynamics and information theory. Thermodynamics provides the Carnot cycle which describes intelligence dynamics when operating in the refrigeration mode. It also provides the principle of maximum entropy. Information theory has recently provided the important concept of dual-matching useful for the design of efficient intelligent systems. The reverse engineered model of computation by pyramidal neurons agrees well with biology and offers a simple and powerful exemplar of basic engineering concepts.

  2. Multifractal methodology

    CERN Document Server

    Salat, Hadrien; Arcaute, Elsa

    2016-01-01

    Various methods have been developed independently to study the multifractality of measures in many different contexts. Although they all convey the same intuitive idea of giving a "dimension" to sets where a quantity scales similarly within a space, they are not necessarily equivalent on a more rigorous level. This review article aims at unifying the multifractal methodology by presenting the multifractal theoretical framework and principal practical methods, namely the moment method, the histogram method, multifractal detrended fluctuation analysis (MDFA) and modulus maxima wavelet transform (MMWT), with a comparative and interpretative eye.

  3. 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.

  4. 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...

  5. The search for intelligence

    Science.gov (United States)

    Coffey, E. J.

    1980-12-01

    Implications of current understandings of the nature of human intelligence for the possibility of extraterrestrial intelligence are discussed. The perceptual theory of intelligence as the manipulation of perceptual images rather than language is introduced, and conditions leading to the ascendancy of man over other hominids with similar conceptual abilities are discussed, including the liberation of the hands from a locomotive function and the evolution of neoteny. It is argued that the specificity of the environmental, behavioral and physiological conditions which lead to the emergence of technologically oriented, and communicative intelligent creatures suggests that any SETI would most likely be fruitless.

  6. 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.

  7. 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. 

  8. 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...

  9. 77 FR 32952 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

    Science.gov (United States)

    2012-06-04

    ... of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: Department of Defense, Defense Intelligence Agency, National Intelligence... a closed meeting of the Defense Intelligence Agency National Intelligence University Board...

  10. 75 FR 76423 - Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting

    Science.gov (United States)

    2010-12-08

    ... of the Secretary Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting AGENCY: National Defense Intelligence College, Defense Intelligence Agency, Department of... a closed meeting of the Defense Intelligence Agency National Defense Intelligence College Board...

  11. 76 FR 28960 - Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting

    Science.gov (United States)

    2011-05-19

    ... of the Secretary Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting AGENCY: National Defense Intelligence College, Defense Intelligence Agency, Department of... a closed meeting of the Defense Intelligence Agency National Defense Intelligence College Board...

  12. Computational Intelligence in Exchange-Rate Forecasting

    OpenAIRE

    Andreou, Andreas S.; Zombanakis, George A.

    2006-01-01

    This paper applies computational intelligence methods to exchange rate forecasting. In particular, it employs neural network methodology in order to predict developments of the Euro exchange rate versus the U.S. Dollar and the Japanese Yen. Following a study of our series using traditional as well as specialized, non-parametric methods together with Monte Carlo simulations we employ selected Neural Networks (NNs) trained to forecast rate fluctuations. Despite the fact that the data series hav...

  13. Intelligent control of a cryogenic cooling plant based on blackboard system architecture.

    Science.gov (United States)

    Linkens, D A; Abbod, M F; Browne, A; Cade, N

    2000-01-01

    Intelligent system techniques have been rapidly assimilating into process control engineering, with many applications reported in the last decade. Intelligent control is bringing a new perspective as well as new challenges to process control. In this paper, a software architecture for a Blackboard for Integrated Intelligent Control Systems (BIICS) is described. The system is designed to simultaneously support multiple heterogeneous intelligent methodologies, such as neural networks. expert systems, fuzzy logic, neural networks and genetic algorithms. It will be shown how such methodologies can be readily assimilated into the software architecture. The BIICS system represents a multi-purpose platform for design and simulation of intelligent control paradigms for different kinds of processes. Currently the system utilizes intelligent control techniques (neuro-fuzzy and genetic optimization) for controlling a cryogenic plant used for superconductor testing at temperatures below 100 K.

  14. 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.       

  15. 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.

  16. Hybrid specification, storage, retrieval and runtime application of clinical guidelines.

    Science.gov (United States)

    Shahar, Y

    2006-06-01

    Clinical guidelines are a major tool in improving the quality of medical care. However, most guidelines are in free text, are not machine-comprehensible and are not easily accessible to clinicians at the point of care. We have designed and implemented a web-based, modular, distributed architecture, the Digital Electronic Guideline Library (DeGeL), which facilitates gradual conversion of clinical guidelines from text to a formal representation in the chosen target guideline ontology. The architecture supports guideline classification, semantic markup, context-sensitive search, browsing, run-time application and retrospective quality assessment. The DeGeL hybrid meta-ontology includes elements common to all guideline ontologies, such as semantic classification and domain knowledge; it also includes four content-representation formats: free text, semi-structured text, semi-formal representation and a formal representation. These formats support increasingly sophisticated computational tasks. Guidelines can thus be in a hybrid representation in which guidelines, and even parts of the same guideline, might exist at different formalisation levels. We have also developed and rigorously evaluated a methodology and an associated web-based tool, Uruz, for gradually structuring and semi-formalising free-text clinical guidelines. Finally, we have designed, implemented and evaluated a new approach, the hybrid runtime application model, for supporting runtime application of clinical guidelines that are not necessarily in a machine-comprehensible format; in particular, when the guideline is in a semi-formal representation and the patient's data are either in an electronic medical record or in a paper format. The tool implementing this new approach, the Spock module, is customised at this point to the Asbru guideline specification language and exploits the hybrid structure of guidelines in DeGeL. The Spock module also exploits our temporal-abstraction mediator to the patient

  17. Spiritual Intelligence: The Tenth Intelligence that Integrates All Other Intelligences.

    Science.gov (United States)

    Sisk, Dorothy

    2002-01-01

    This article discusses seven ways to develop spiritual intelligence, including: think about goals and identify values; access inner processes and use visualization to see goals fulfilled; integrate personal and universal vision; take responsibility for goals; develop a sense of community; focus on love and compassion; and take advantages of…

  18. 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.

  19. Research Methodology

    CERN Document Server

    Rajasekar, S; Philomination, P

    2006-01-01

    In this manuscript various components of research are listed and briefly discussed. The topics considered in this write-up cover a part of the research methodology paper of Master of Philosophy (M.Phil.) course and Doctor of Philosophy (Ph.D.) course. The manuscript is intended for students and research scholars of science subjects such as mathematics, physics, chemistry, statistics, biology and computer science. Various stages of research are discussed in detail. Special care has been taken to motivate the young researchers to take up challenging problems. Ten assignment works are given. For the benefit of young researchers a short interview with three eminent scientists is included at the end of the manuscript.

  20. Methodological advances

    Directory of Open Access Journals (Sweden)

    Lebreton, J.-D.

    2004-06-01

    Full Text Available The study of population dynamics has long depended on methodological progress. Among many striking examples, continuous time models for populations structured in age (Sharpe & Lotka, 1911 were made possible by progress in the mathematics of integral equations. Therefore the relationship between population ecology and mathematical and statistical modelling in the broad sense raises a challenge in interdisciplinary research. After the impetus given in particular by Seber (1982, the regular biennial EURING conferences became a major vehicle to achieve this goal. It is thus not surprising that EURING 2003 included a session entitled “Methodological advances”. Even if at risk of heterogeneity in the topics covered and of overlap with other sessions, such a session was a logical way of ensuring that recent and exciting new developments were made available for discussion, further development by biometricians and use by population biologists. The topics covered included several to which full sessions were devoted at EURING 2000 (Anderson, 2001 such as: individual covariates, Bayesian methods, and multi–state models. Some other topics (heterogeneity models, exploited populations and integrated modelling had been addressed by contributed talks or posters. Their presence among “methodological advances”, as well as in other sessions of EURING 2003, was intended as a response to their rapid development and potential relevance to biological questions. We briefly review all talks here, including those not published in the proceedings. In the plenary talk, Pradel et al. (in prep. developed GOF tests for multi–state models. Until recently, the only goodness–of–fit procedures for multistate models were ad hoc, and non optimal, involving use of standard tests for single state models (Lebreton & Pradel, 2002. Pradel et al. (2003 proposed a general approach based in particular on mixtures of multinomial distributions. Pradel et al. (in prep. showed

  1. 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). .

  2. Heidegger and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Diaz, G.

    1987-01-01

    The discipline of Artificial Intelligence, in its quest for machine intelligence, showed great promise as long as its areas of application were limited to problems of a scientific and situation neutral nature. The attempts to move beyond these problems to a full simulation of man's intelligence has faltered and slowed it progress, largely because of the inability of Artificial Intelligence to deal with human characteristic, such as feelings, goals, and desires. This dissertation takes the position that an impasse has resulted because Artificial Intelligence has never been properly defined as a science: its objects and methods have never been identified. The following study undertakes to provide such a definition, i.e., the required ground for Artificial Intelligence. The procedure and methods employed in this study are based on Heidegger's philosophy and techniques of analysis as developed in Being and Time. Results of this study show that both the discipline of Artificial Intelligence and the concerns of Heidegger in Being and Time have the same object; fundamental ontology. The application of Heidegger's conclusions concerning fundamental ontology unites the various aspects of Artificial Intelligence and provides the articulation which shows the parts of this discipline and how they are related.

  3. 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…

  4. Humanoid Intelligent Management System

    Institute of Scientific and Technical Information of China (English)

    DU Jun-ping; TU Xu-yan

    2004-01-01

    This paper proposes a concept and design strategy for the humanoid intelligent management system (HIMS) based on artificial life. Various topics are discussed including the design method and implementation techniques for the dual management scheme (DMS), humanoid intelligent management model (HIMM), central-decentralized management pattern, and multi-grade coordination function.

  5. 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…

  6. Intelligence Issues for Congress

    Science.gov (United States)

    2007-02-27

    and Prosecution Act of 2006, both by Elizabeth B. Bazan . authorization and defense appropriations acts, they include a substantial portion of the...Expands Rumsfeld’s Domain,” Washington Post, Jan . 23, 2005, p. A1. strategically analyze intelligence, and for failing to share intelligence with other

  7. 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…

  8. 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....

  9. Emotional Intelligence and Giftedness.

    Science.gov (United States)

    Mayer, John D.; Perkins, Donna M.; Caruso, David R.; Salovey, Peter

    2001-01-01

    Emotional intelligence and social behavior were explored in a study with 11 adolescents. Results found that those with higher emotional intelligence were better able to identify their own and others' emotions in situations, use that information to guide their actions, and resist peer pressure than others. (Contains references.) (Author/CR)

  10. Intelligent Tutoring Systems.

    Science.gov (United States)

    Anderson, John R.; And Others

    1985-01-01

    Cognitive psychology, artificial intelligence, and computer technology have advanced so much that it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors have been developed for teaching students to do proofs in geometry and to write computer programs in the LISP language. (JN)

  11. Emotional intelligence as a standard intelligence.

    Science.gov (United States)

    Mayer, J D; Salovey, P; Caruso, D R; Sitarenios, G

    2001-09-01

    The authors have claimed that emotional intelligence (EI) meets traditional standards for an intelligence (J. D. Mayer, D. R. Caruso, & P. Salovey, 1999). R. D. Roberts, M. Zeidner, and G. Matthews (2001) questioned whether that claim was warranted. The central issue raised by Roberts et al. concerning Mayer et al. (1999) is whether there are correct answers to questions on tests purporting to measure EI as a set of abilities. To address this issue (and others), the present authors briefly restate their view of intelligence, emotion, and EI. They then present arguments for the reasonableness of measuring EI as an ability, indicate that correct answers exist, and summarize recent data suggesting that such measures are, indeed, reliable.

  12. 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...

  13. 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 init......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...

  14. Intelligence and homosexuality.

    Science.gov (United States)

    Kanazawa, Satoshi

    2012-09-01

    The origin of preferences and values is an unresolved theoretical problem in behavioural sciences. The Savanna-IQ Interaction Hypothesis, derived from the Savanna Principle and a theory of the evolution of general intelligence, suggests that more intelligent individuals are more likely to acquire and espouse evolutionarily novel preferences and values than less intelligent individuals, but general intelligence has no effect on the acquisition and espousal of evolutionarily familiar preferences and values. Ethnographies of traditional societies suggest that exclusively homosexual behaviour was probably rare in the ancestral environment, so the Hypothesis would predict that more intelligent individuals are more likely to identify themselves as homosexual and engage in homosexual behaviour. Analyses of three large, nationally representative samples (two of which are prospectively longitudinal) from two different nations confirm the prediction.

  15. Intelligence and Prosocial Behavior

    DEFF Research Database (Denmark)

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

    2012-01-01

    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......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...... 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....

  16. 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…

  17. 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…

  18. 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.

  19. Instrumenting the Intelligence Analysis Process

    Energy Technology Data Exchange (ETDEWEB)

    Hampson, Ernest; Cowley, Paula J.

    2005-05-02

    The Advanced Research and Development Activity initiated the Novel Intelligence from Massive Data (NIMD) program to develop advanced analytic technologies and methodologies. In order to support this objective, researchers and developers need to understand what analysts do and how they do it. In the past, this knowledge generally was acquired through subjective feedback from analysts. NIMD established the innovative Glass Box Analysis (GBA) Project to instrument a live intelligence mission and unobtrusively capture and objectively study the analysis process. Instrumenting the analysis process requires tailor-made software hooks that grab data from a myriad of disparate application operations and feed into a complex relational database and hierarchical file store to collect, store, retrieve, and distribute analytic data in a manner that maximizes researchers’ understanding. A key to success is determining the correct data to collect and aggregate low-level data into meaningful analytic events. This paper will examine how the GBA team solved some of these challenges, continues to address others, and supports a growing user community in establishing their own GBA environments and/or studying the data generated by GBA analysts working in the Glass Box.

  20. A More Intelligent Literature Search

    Directory of Open Access Journals (Sweden)

    Michael G King

    2014-07-01

    Full Text Available Although the topic of study relates to an environmental/health issue, it is the methodology described which serves to showcase an embryonic form of a new “more intelligent” protocol of search algorithm. Through the implementation of this algorithm, an extensive automated literature base yielded a single credible solution to a previously unsolved problem. Faced with a distressing but entirely unexplained incidence of birth defects, the proposed model of knowledge scavenging worked through acknowledged gaps in understanding of increased (phosphate fertilizer, enabled the template of known facts regarding the interactions of phosphates with the processes of mammal (and other animal growth, of metabolic function, and of neurological development, and delivered a causal model which would not, at least not easily, derive from current literature search methods. Illustrating the practical value of a step forwards in the design of intelligent literature search, the present study provides a candidate cause to explain a cluster of bovine deformity

  1. Hybrid vehicles

    Energy Technology Data Exchange (ETDEWEB)

    West, J.G.W. [Electrical Machines (United Kingdom)

    1997-07-01

    The reasons for adopting hybrid vehicles result mainly from the lack of adequate range from electric vehicles at an acceptable cost. Hybrids can offer significant improvements in emissions and fuel economy. Series and parallel hybrids are compared. A combination of series and parallel operation would be the ideal. This can be obtained using a planetary gearbox as a power split device allowing a small generator to transfer power to the propulsion motor giving the effect of a CVT. It allows the engine to run at semi-constant speed giving better fuel economy and reduced emissions. Hybrid car developments are described that show the wide range of possible hybrid systems. (author)

  2. 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....

  3. 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…

  4. 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.

  5. 三维欧氏 Steiner 最小树的 Delaunay 四面体网格混合智能算法%A Hybrid Intelligent Algorithm Based on Delaunay Tetrahedron Mesh Generation for Euclidean Steiner Minimum Tree Problem in 3-space

    Institute of Scientific and Technical Information of China (English)

    王家桢; 马良; 张惠珍

    2015-01-01

    Euclidean Steiner minimum tree problem , a classical NP-hard problem in combination optimization , has been widely studied in many fields .Euclidean Steiner minimal tree problem in 3-space is the generalization of Euclidean Steiner minimum tree problem in 2-space .The research results on Euclidean Steiner minimal tree problem in 3-space have been rarely published because of their difficulties .In this paper , a hybrid intelligent method is designed by using Delaunay tetrahedron mesh generation technology to solve the Euclidean Steiner min -imal tree problem in 3-space , which can not only avoid falling into local optima , but also has good effects in solving large scale problems .Promising results are obtained by using this hybrid method coded in MATLAB to solve series of Euclidean Steiner minimum tree problem instances in 3-space .%Steiner最小树问题是组合优化中经典的NP难题,在许多实际问题中有着广泛的应用,而三维欧氏Stei-ner最小树问题是对二维欧氏Steiner最小树问题的推广。由于三维欧氏Steiner树问题的求解非常困难,至今为止的相关成果较为少见。本文针对该问题,利用Delaunay四面体网格剖分技术,提出了一种混合型智能求解方法,不仅可以尽量避免拓扑结构陷入局部最优,且对较大规模的问题求解亦有良好的效果。算法在Matlab环境下编程实现,经实例测试,获得了满意的效果。

  6. Intelligent Car System

    Directory of Open Access Journals (Sweden)

    Qasim Siddique

    2009-01-01

    Full Text Available In modern life the road safety has becomes the core issue. One single move of a driver can cause horrifying accident. The main goal of intelligent car system is to make communication with other cars on the road. The system is able to control to speed, direction and the distance between the cars the intelligent car system is able to recognize traffic light and is able to take decision according to it. This paper presents a framework of the intelligent car system. I validate several aspect of our system using simulation.

  7. Intelligent Car System

    CERN Document Server

    Siddique, Qasim

    2012-01-01

    In modern life the road safety has becomes the core issue. One single move of a driver can cause horrifying accident. The main goal of intelligent car system is to make communication with other cars on the road. The system is able to control to speed, direction and the distance between the cars the intelligent car system is able to recognize traffic light and is able to take decision according to it. This paper presents a framework of the intelligent car system. I validate several aspect of our system using simulation.

  8. Artificial intelligence: Human effects

    Energy Technology Data Exchange (ETDEWEB)

    Yazdani, M.; Narayanan, A.

    1984-01-01

    This book presents an up-to-date study of the interaction between the fast-growing discipline of artificial intelligence and other human endeavors. The volume explores the scope and limitations of computing, and presents a history of the debate on the possibility of machines achieving intelligence. The authors offer a state-of-the-art survey of Al, concentrating on the ''mind'' (language understanding) and the ''body'' (robotics) of intelligent computing systems.

  9. 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  

  10. Dividing Up Intelligence Education

    Directory of Open Access Journals (Sweden)

    Dr. Robert Clark

    2008-01-01

    Full Text Available At this year's annual conference of the International Association for Intelligence Education (IAFIE in Monterey, CA, the keynote speaker posed the question, "How much do you need intelligence education outside the beltway?" Which led to a second question discussed during the conference: "What should such education look like?" In short, what should we be teaching in universities? What should we leave to the intelligence community as training? And what could be done in either or both settings? The first question of any educational effort is:What are we preparing students for?

  11. 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...

  12. 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...

  13. 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...

  14. Strategic Alignment of Business Intelligence

    OpenAIRE

    Cederberg, Niclas

    2010-01-01

    This thesis is about the concept of strategic alignment of business intelligence. It is based on a theoretical foundation that is used to define and explain business intelligence, data warehousing and strategic alignment. By combining a number of different methods for strategic alignment a framework for alignment of business intelligence is suggested. This framework addresses all different aspects of business intelligence identified as relevant for strategic alignment of business intelligence...

  15. 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.

  16. 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.

  17. Hybridization of Evolutionary Mechanisms for Feature Subset Selection in Unsupervised Learning

    Science.gov (United States)

    Torres, Dolores; Ponce-de-León, Eunice; Torres, Aurora; Ochoa, Alberto; Díaz, Elva

    Feature subset selection for unsupervised learning, is a very important topic in artificial intelligence because it is the base for saving computational resources. In this implementation we use a typical testor’s methodology in order to incorporate an importance index for each variable. This paper presents the general framework and the way two hybridized meta-heuristics work in this NP-complete problem. The evolutionary mechanisms are based on the Univariate Marginal Distribution Algorithm (UMDA) and the Genetic Algorithm (GA). GA and UMDA - Estimation of Distribution Algorithm (EDA) use a very useful rapid operator implemented for finding typical testors on a very large dataset and also, both algorithms, have a local search mechanism for improving time and fitness. Experiments show that EDA is faster than GA because it has a better exploitation performance; nevertheless, GA’ solutions are more consistent.

  18. The role of decision speed in the construct of intelligence

    Directory of Open Access Journals (Sweden)

    Valentin Bucik

    2002-12-01

    Full Text Available A theory of general intelligence in Spearman's sense has been frequently verified via two complementary approaches, the one using psychometric and the other using experimental methodology. The results led to the conclusion that both, psychometric tests and elementary cognitive tasks in different experimental paradigms measure the same thing in substantial extent. The rapid, error free information processing, reflecting the efficiency of a nervous system with limited capacity, was supposed to be the essential component of the intellect. This view is often criticised by the authors who claim that high correlation between speed of information processing and psychometric intelligence is simply the consequence of the fact that some intelligence tests themselves are "speeded" and that mental speed is merely a marginal variable in both psychometric tests and elementary cognitive tasks. In our study we tested 88 subjects with three psychometric tests, measuring general intelligence in Spearman's sense. Parallel versions of those tests were created by splitting each of them into two equivalent halves by "odd-even" principle. One version was applied under strict time constraints and the other one without time pressure. In addition five speed-of-information-processing paradigms were applied. The relationship between the mental speed and general intelligence measured in timed and untimed conditions was examined. Results suggest that the role of speed of information processing is significant in determining general intelligence. Mental speed also seems to be relatively independent with regarding to time limitations in testing intelligence. The results are discussed in terms of the neural efficiency presumptions.

  19. 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?

  20. 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.

  1. 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.

  2. 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.

  3. Introduction to artificial intelligence

    Science.gov (United States)

    Cheeseman, P.; Gevarter, W.

    1986-01-01

    This paper presents an introductory view of Artificial Intelligence (AI). In addition to defining AI, it discusses the foundations on which it rests, research in the field, and current and potential applications.

  4. Intelligent Freigth Transport Systems

    DEFF Research Database (Denmark)

    Overø, Helene Martine; Larsen, Allan; Røpke, Stefan

    2009-01-01

    The Danish innovation project entitled “Intelligent Freight Transport Systems” aims at developing prototype systems integrating public intelligent transport systems (ITS) with the technology in vehicles and equipment as well as the IT-systems at various transport companies. The objective is to en......The Danish innovation project entitled “Intelligent Freight Transport Systems” aims at developing prototype systems integrating public intelligent transport systems (ITS) with the technology in vehicles and equipment as well as the IT-systems at various transport companies. The objective...... is to enhance the efficiency and lower the environmental impact in freight transport. In this paper, a pilot project involving real-time waste collection at a Danish waste collection company is described, and a solution approach is proposed. The problem corresponds to the dynamic version of the waste collection...... problem which can be formulated as a dynamic version of the vehicle routing problem with time windows (VRPTW)....

  5. 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....

  6. Creativity, Personality and Intelligence.

    Science.gov (United States)

    Wakefield, James A., Jr.; Goad, Nancy A.

    1981-01-01

    Creativity is discussed in terms of H. Eysenck's personality theory. Creative persons are characterized by introversion, neuroticism, psychoticism, and moderate to high intelligence. The literature is reviewed on similarities and differences between creativity and pathology. (Author/DB)

  7. Intelligent energy demand forecasting

    CERN Document Server

    Hong, Wei-Chiang

    2013-01-01

    This book offers approaches and methods to calculate optimal electric energy allocation, using evolutionary algorithms and intelligent analytical tools to improve the accuracy of demand forecasting. Focuses on improving the drawbacks of existing algorithms.

  8. Towards Intelligent Supply Chains

    DEFF Research Database (Denmark)

    Siurdyban, Artur; Møller, Charles

    2012-01-01

    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...... 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......, 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....

  9. Creativity, Personality and Intelligence.

    Science.gov (United States)

    Wakefield, James A., Jr.; Goad, Nancy A.

    1981-01-01

    Creativity is discussed in terms of H. Eysenck's personality theory. Creative persons are characterized by introversion, neuroticism, psychoticism, and moderate to high intelligence. The literature is reviewed on similarities and differences between creativity and pathology. (Author/DB)

  10. 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.

  11. 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.

  12. 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.

  13. Emergency Operations Intelligence Fusion

    Science.gov (United States)

    2010-06-01

    first responder with an internet access to become a sensor and provide additional intelligence to enhance relief efforts. The result is better resource management, faster decision cycles, and more importantly a reduction in loss of life due to delay or

  14. Intelligent Elements for ISHM

    Science.gov (United States)

    Schmalzel, John L.; Morris, Jon; Turowski, Mark; Figueroa, Fernando; Oostdyk, Rebecca

    2008-01-01

    There are a number of architecture models for implementing Integrated Systems Health Management (ISHM) capabilities. For example, approaches based on the OSA-CBM and OSA-EAI models, or specific architectures developed in response to local needs. NASA s John C. Stennis Space Center (SSC) has developed one such version of an extensible architecture in support of rocket engine testing that integrates a palette of functions in order to achieve an ISHM capability. Among the functional capabilities that are supported by the framework are: prognostic models, anomaly detection, a data base of supporting health information, root cause analysis, intelligent elements, and integrated awareness. This paper focuses on the role that intelligent elements can play in ISHM architectures. We define an intelligent element as a smart element with sufficient computing capacity to support anomaly detection or other algorithms in support of ISHM functions. A smart element has the capabilities of supporting networked implementations of IEEE 1451.x smart sensor and actuator protocols. The ISHM group at SSC has been actively developing intelligent elements in conjunction with several partners at other Centers, universities, and companies as part of our ISHM approach for better supporting rocket engine testing. We have developed several implementations. Among the key features for these intelligent sensors is support for IEEE 1451.1 and incorporation of a suite of algorithms for determination of sensor health. Regardless of the potential advantages that can be achieved using intelligent sensors, existing large-scale systems are still based on conventional sensors and data acquisition systems. In order to bring the benefits of intelligent sensors to these environments, we have also developed virtual implementations of intelligent sensors.

  15. Intelligence. Indochina Monographs,

    Science.gov (United States)

    1982-01-01

    literary pieces such as proverbs, folk songs, lyrical poems cad ritual chants. The composition of these songs and poems is simple, -•% the language...governing the composition of folk songs, lyrical poems and ritual chants helped sharpen the Communist propaganda technique to the point that every...Vietnam—United States—Free World intelligence community were great and constant. During this long war the entire intelligence program improved each

  16. 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.

  17. The Convergence of Intelligences

    Science.gov (United States)

    Diederich, Joachim

    Minsky (1985) argued an extraterrestrial intelligence may be similar to ours despite very different origins. ``Problem- solving'' offers evolutionary advantages and individuals who are part of a technical civilisation should have this capacity. On earth, the principles of problem-solving are the same for humans, some primates and machines based on Artificial Intelligence (AI) techniques. Intelligent systems use ``goals'' and ``sub-goals'' for problem-solving, with memories and representations of ``objects'' and ``sub-objects'' as well as knowledge of relations such as ``cause'' or ``difference.'' Some of these objects are generic and cannot easily be divided into parts. We must, therefore, assume that these objects and relations are universal, and a general property of intelligence. Minsky's arguments from 1985 are extended here. The last decade has seen the development of a general learning theory (``computational learning theory'' (CLT) or ``statistical learning theory'') which equally applies to humans, animals and machines. It is argued that basic learning laws will also apply to an evolved alien intelligence, and this includes limitations of what can be learned efficiently. An example from CLT is that the general learning problem for neural networks is intractable, i.e. it cannot be solved efficiently for all instances (it is ``NP-complete''). It is the objective of this paper to show that evolved intelligences will be constrained by general learning laws and will use task-decomposition for problem-solving. Since learning and problem-solving are core features of intelligence, it can be said that intelligences converge despite very different origins.

  18. Intelligent tutoring systems

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, J.R.; Boyle, C.F.; Reiser, B.J.

    1985-04-26

    Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP. 19 references, 2 figures.

  19. Binary Masking & Speech Intelligibility

    DEFF Research Database (Denmark)

    Boldt, Jesper

    The purpose of this thesis is to examine how binary masking can be used to increase intelligibility in situations where hearing impaired listeners have difficulties understanding what is being said. The major part of the experiments carried out in this thesis can be categorized as either experime...... mask using a directional system and a method for correcting errors in the target binary mask. The last part of the thesis, proposes a new method for objective evaluation of speech intelligibility....

  20. Solving Systems of Equations with Techniques from Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Irina Maria Terfaloaga

    2015-07-01

    Full Text Available A frequent problem in numerical analysis is solving the systems of equations. That problem has generated in time a great interest among mathematicians and computer scientists, as evidenced by the large number of numerical methods developed. Besides the classical numerical methods, in the last years were proposed methods inspired by techniques from artificial intelligence. Hybrid methods have been also proposed along the time [15, 19]. The goal of this study is to make a survey of methods inspired from artificial intelligence for solving systems of equations