Computational Intelligence and Decision Making Trends and Applications

CERN Document Server

Madureira, Ana; Marques, Viriato

2013-01-01

This book provides a general overview and original analysis of new developments and applications in several areas of Computational Intelligence and Information Systems. Computational Intelligence has become an important tool for engineers to develop and analyze novel techniques to solve problems in basic sciences such as physics, chemistry, biology, engineering, environment and social sciences.   The material contained in this book addresses the foundations and applications of Artificial Intelligence and Decision Support Systems, Complex and Biological Inspired Systems, Simulation and Evolution of Real and Artificial Life Forms, Intelligent Models and Control Systems, Knowledge and Learning Technologies, Web Semantics and Ontologies, Intelligent Tutoring Systems, Intelligent Power Systems, Self-Organized and Distributed Systems, Intelligent Manufacturing Systems and Affective Computing. The contributions have all been written by international experts, who provide current views on the topics discussed and pr...

Knowledge-based dialogue in Intelligent Decision Support Systems

International Nuclear Information System (INIS)

Hollnagel, E.

1987-01-01

The overall goal for the design of Intelligent Decision Support Systems (IDSS) is to enhance understanding of the process under all operating conditions. For an IDSS to be effective, it must: select or generate the right information; produce reliable and consistent information; allow flexible and effective operator interaction; relate information presentation to current plant status and problems; and make the presentation at the right time. Several ongoing R and D programs try to design and build IDSSs. A particular example is the ESPRIT project Graphics and Knowledge Based Diaglogue for Dynamic Systems (GRADIENT). This project, the problems it addresses, and its uses, are discussed here

Intelligent decision support systems for sustainable computing paradigms and applications

CERN Document Server

Abraham, Ajith; Siarry, Patrick; Sheng, Michael

2017-01-01

This unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective. Sustainable computing has expanded to become a significant research area covering the fields of computer science and engineering, electrical engineering and other engineering disciplines, and there has been an increase in the amount of literature on aspects sustainable computing such as energy efficiency and natural resources conservation that emphasizes the role of ICT (information and communications technology) in achieving system design and operation objectives. The energy impact/design of more efficient IT infrastructures is a key challenge in realizing new computing paradigms. The book explores the uses of computational intelligence (CI) techniques for intelligent decision support that can be explo...

Autonomous Driver Based on an Intelligent System of Decision-Making.

Science.gov (United States)

Czubenko, Michał; Kowalczuk, Zdzisław; Ordys, Andrew

The paper presents and discusses a system ( xDriver ) which uses an Intelligent System of Decision-making (ISD) for the task of car driving. The principal subject is the implementation, simulation and testing of the ISD system described earlier in our publications (Kowalczuk and Czubenko in artificial intelligence and soft computing lecture notes in computer science, lecture notes in artificial intelligence, Springer, Berlin, 2010, 2010, In Int J Appl Math Comput Sci 21(4):621-635, 2011, In Pomiary Autom Robot 2(17):60-5, 2013) for the task of autonomous driving. The design of the whole ISD system is a result of a thorough modelling of human psychology based on an extensive literature study. Concepts somehow similar to the ISD system can be found in the literature (Muhlestein in Cognit Comput 5(1):99-105, 2012; Wiggins in Cognit Comput 4(3):306-319, 2012), but there are no reports of a system which would model the human psychology for the purpose of autonomously driving a car. The paper describes assumptions for simulation, the set of needs and reactions (characterizing the ISD system), the road model and the vehicle model, as well as presents some results of simulation. It proves that the xDriver system may behave on the road as a very inexperienced driver.

Leveraging business intelligence to make better decisions: Part I.

Science.gov (United States)

Reimers, Mona

2014-01-01

Data is the new currency. Business intelligence tools will provide better performing practices with a competitive intelligence advantage that will separate the high performers from the rest of the pack. Given the investments of time and money into our data systems, practice leaders must work to take every advantage and look at the datasets as a potential goldmine of business intelligence decision tools. A fresh look at decision tools created from practice data will create efficiencies and improve effectiveness for end-users and managers.

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.

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

Advances in intelligent analysis of medical data and decision support systems

CERN Document Server

Iantovics, Barna

2013-01-01

This volume is a result of the fruitful and vivid discussions during the MedDecSup'2012 International Workshop bringing together a relevant body of knowledge, and new developments in the increasingly important field of medical informatics. This carefully edited book presents new ideas aimed at the development of intelligent processing of various kinds of medical information and the perfection of the contemporary computer systems for medical decision support. The book presents advances of the medical information systems for intelligent archiving, processing, analysis and search-by-content which will improve the quality of the medical services for every patient and of the global healthcare system. The book combines in a synergistic way theoretical developments with the practicability of the approaches developed and presents the last developments and achievements in  medical informatics to a broad range of readers: engineers, mathematicians, physicians, and PhD students.

Decision Support System Based on Computational Collective Intelligence in Campus Information Systems

Science.gov (United States)

Saito, Yoshihito; Matsuo, Tokuro

Education institutions such as universities have a lot of information including book information, equipment administrative information, student information, and several others. The institutions also have multiple information in time series. As collective intelligence in campus, integrating and reusing these preserved information regarding career and taking a class, university can effectively support students' decision making of their getting jobs and subjects choice. Our purpose of support is to increase student's motivation. In this paper, we focus on course record and job information included in students' information, and propose the method to analyze correlation between a pattern of taking class and job lined up. Afterwards, we propose a support system regarding getting a job and taking class by using our proposed method. For a student who has his/her favorite job to get, the system supports his/her decision making of lecture choice by recommending a set of appropriate lecture groups. On another hand, for a student who does not have favorite job to get, the system supports his/her decision making of getting job by presenting appropriate job families related with lecture group in which he/she has ever taken. The contribution of this paper is showing a concrete method to reuse the campus collective information, implementing a system, and user perspectives.

Intelligent Decision Support in Proportional–Stop-Loss Reinsurance Using Multiple Attribute Decision-Making (MADM

Directory of Open Access Journals (Sweden)

Shirley Jie Xuan Wang

2017-11-01

Full Text Available This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. This article focuses on adopting more than one optimality criteria under a more generic combinational design of commonly used reinsurance products, i.e., proportional reinsurance and stop-loss reinsurance. In terms of methodology, the significant contribution of the study the incorporation of the well-established decision analysis tool multiple-attribute decision-making (MADM into the modelling of reinsurance selection. To illustrate the feasibility of incorporating intelligent decision supporting systems in the reinsurance market, the study includes a numerical case study using the simulation software @Risk in modeling insurance claims, as well as programming in MATLAB to realize MADM. A list of managerial implications could be drawn from the case study results. Most importantly, when choosing the most appropriate type of reinsurance, insurance companies should base their decisions on multiple measurements instead of single-criteria decision-making models so that their decisions may be more robust.

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

OpenAIRE

Ajay Kumar Saxena; S. 0. Bhatnagar; P. K Saxena

2002-01-01

Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives p...

A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization

Directory of Open Access Journals (Sweden)

Tinggui Chen

2013-01-01

Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.

Decision-Making and the Interface between Human Intelligence and Artificial Intelligence. AIR 1987 Annual Forum Paper.

Science.gov (United States)

Henard, Ralph E.

Possible future developments in artificial intelligence (AI) as well as its limitations are considered that have implications for institutional research in higher education, and especially decision making and decision support systems. It is noted that computer software programs have been developed that store knowledge and mimic the decision-making…

Intelligent Decision Support and Big Data for Logistics and Supply Chain Management

DEFF Research Database (Denmark)

Voss, Stefan; Sebastian, Hans-Jürgen; Pahl, Julia

2017-01-01

Intelligent Decision Support and Big Data for Logistics and Supply Chain Management” features theoretical developments, real-world applications and information systems related to solving decision problems in logistics and supply chain management. Methods include optimization, heuristics, metaheur......Intelligent Decision Support and Big Data for Logistics and Supply Chain Management” features theoretical developments, real-world applications and information systems related to solving decision problems in logistics and supply chain management. Methods include optimization, heuristics......, metaheuristics and matheuristics, simulation, agent technologies, and descriptive methods. In a sense, we were and are representing the future of logistics over the years....

The Relationship of Business Intelligence Systems to Organizational Performance Benefits: A Structural Equation Modeling of Management Decision Making

Science.gov (United States)

Sparks, Betsy H.

2014-01-01

Business Intelligence is a major expenditure in many organizations and necessary for competitive advantage. These expenditures do not result in maximum benefits for the organization if the information obtained from the Business Intelligence System (BIS) is not used in the management decision-making process. This quantitative research study used an…

Challenging problems and solutions in intelligent systems

CERN Document Server

Grzegorzewski, Przemysław; Kacprzyk, Janusz; Owsiński, Jan; Penczek, Wojciech; Zadrożny, Sławomir

2016-01-01

This volume presents recent research, challenging problems and solutions in Intelligent Systems– covering the following disciplines: artificial and computational intelligence, fuzzy logic and other non-classic logics, intelligent database systems, information retrieval, information fusion, intelligent search (engines), data mining, cluster analysis, unsupervised learning, machine learning, intelligent data analysis, (group) decision support systems, intelligent agents and multi-agent systems, knowledge-based systems, imprecision and uncertainty handling, electronic commerce, distributed systems, etc. The book defines a common ground for sometimes seemingly disparate problems and addresses them by using the paradigm of broadly perceived intelligent systems. It presents a broad panorama of a multitude of theoretical and practical problems which have been successfully dealt with using the paradigm of intelligent computing.

Developing Information Systems for Competitive Intelligence Support.

Science.gov (United States)

Hohhof, Bonnie

1994-01-01

Discusses issues connected with developing information systems for competitive intelligence support; defines the elements of an effective competitive information system; and summarizes issues affecting system design and implementation. Highlights include intelligence information; information needs; information sources; decision making; and…

Decision support, analytics, and business intelligence

CERN Document Server

Power, Daniel J

2013-01-01

Competition is becoming more intense and decision makers are encountering increasing complexity, rapid change, and higher levels of risk. In many situations, the solution is more and better computerized decision support, especially analytics and business intelligence. Today managers need to learn about and understand computerized decision support. If a business is to succeed, managers must know much more about information technology solutions. This second edition of a powerful introductory book is targeted at busy managers and MBA students who need to grasp the basics of computerized decision support, including the following: What are analytics? What is a decision support system? How can managers identify opportunities to create innovative computerized support? Inside, the author addresses these questions and some 60 more fundamental questions that are key to understanding the rapidly changing realm of computerized decision support. In a short period of time, you'll "get up to speed" on decision support, anal...

An intelligent decision support system for management of petroleum-contaminated sites

International Nuclear Information System (INIS)

Liquang Geng; Chan, C.W.; Zhi Chen; Huang, G.H.

2001-01-01

Groundwater and soil contamination resulted from LNAPLs (light nonaqueous phase liquids) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies have been developed and implemented in the last two decades. They are classified as ex-situ and in-situ remediation techniques. One of the problems associated with ex-situ remediation is the cost of operation. In recent years, in-situ techniques have acquired popularity. However, the selection of the optimal techniques is difficult and insufficient expertise in the process may result in large inflation of expenses. This study presents an expert system (ES) for the management of petroleum contaminated sites in which a variety of artificial intelligence (AI) techniques were used to construct a support tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation. The results from some case studies indicate that the expert system can generate cost-effective remediation alternatives to assist decision-makers. (Author)

Intelligent Information Systems Institute

National Research Council Canada - National Science Library

Gomes, Carla

2004-01-01

...) at Cornell during the first three years of operation. IISI's mandate is threefold: To perform and stimulate research in computational and data-intensive methods for intelligent decision making systems...

Neuro-Based Artificial Intelligence Model for Loan Decisions

OpenAIRE

Shorouq F. Eletter; Saad G. Yaseen; Ghaleb A. Elrefae

2010-01-01

Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpr...

Intelligent systems in oil field development under uncertainty

Energy Technology Data Exchange (ETDEWEB)

Pacheco, Marco A.C.; Vellasco, Marley M.B.R. (eds.) [PUC-Rio, Rio de Janeiro (Brazil). Dept. of Electrical Engineering

2009-07-01

Intelligent Systems use a range of methodologies for analysis, pre-processing, storage, organization, enhancing and mining of operational data, turning it into useful information and knowledge for decision makers in business enterprises. These intelligent technologies for decision support have been used with success by companies and organizations that are looking for competitive advantages whenever the issues on forecast, optimization, risks analysis, fraud detection, and decision under uncertainties are presented. Intelligent Systems (IS) offer to managers and decision makers the best solutions for complex applications, normally considered difficult, very restrictive or even impossible. The use of such techniques leads to a revolutionary process which has a significant impact in the business management strategy, by providing on time, correct information, ready to use. Computational intelligence techniques, especially genetic algorithms, genetic programming, neural networks, fuzzy logic and neuro-fuzzy as well as modern finance theories, such as real options theory, are here presented and exemplified in oil and gas exploitation and production. This book is addressed to executives and students, directly involved or interested in intelligent management in different fields. (orig.)

Intelligent decision technology support in practice

CERN Document Server

Neves-Silva, Rui; Jain, Lakhmi; Phillips-Wren, Gloria; Watada, Junzo; Howlett, Robert

2016-01-01

This book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications.  Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative techniq...

The Intelligent Technologies of Electronic Information System

Science.gov (United States)

Li, Xianyu

2017-08-01

Based upon the synopsis of system intelligence and information services, this paper puts forward the attributes and the logic structure of information service, sets forth intelligent technology framework of electronic information system, and presents a series of measures, such as optimizing business information flow, advancing data decision capability, improving information fusion precision, strengthening deep learning application and enhancing prognostic and health management, and demonstrates system operation effectiveness. This will benefit the enhancement of system intelligence.

Intelligent system for accident identification in NPP

International Nuclear Information System (INIS)

Hernandez, J.L.

1998-01-01

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

Emotional Intelligence and Decision Making

Directory of Open Access Journals (Sweden)

A M Kustubayeva

2011-12-01

Full Text Available The results of the experimental research of the connection between the efficiency of decision making and emotional intelligence are presented in the article. The empirical data indicate that the ability to regulate emotion is an important indicator of the efficiency of decision making in the conditions of psychological experiment.

An intelligent system for helping petroleum industry risk management decision making

Energy Technology Data Exchange (ETDEWEB)

Barreto, Mara M.G.; Ebecken, Nelson F.F. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

1998-07-01

The objective of this paper is to present an intelligent system for helping in decision making about risk analysis in petroleum industry management. Such a system supports explicit inconsistencies in its knowledge bases, and is able to solve it by means of a decision's procedure, in which Fuzzy Logic is used. Expert Systems which knowledge bases carry out explicitly inconsistencies are called paraconsistent systems and were initially proposed by Da Costa and Subrahmanian. The defuzzyfication process of a paraconsistent model was already suggested by Barreto, Ebecken and Clement, and established by Barreto and Ebecken. In Barreto, Ebecken and Clemente show an application of this model for helping in decision making in a business situation. The system that will be presented here is a simulation of many possible applications of this model, and helps the analyses of risk business petroleum project's investment, and, it is desirable, can point out some possibilities of getting out difficulties when the risk is increased. In the introduction, we define some risk result's indicators to be considered, such as, petroleum business project duration, staffing, priority; and we define the system's logical structure. In the Overriding Part, firstly, we show the implemented system's , simulation, how it works, how to get outputs from the given and how to analyze the final results, and explicit the methods used in situations where the inconsistencies appear giving comments about the critical situations. Finally, in the conclusion, we comment the coherence of results, and give comments about some others applications of this kind of systems. (author)

Airline Applications of Business Intelligence Systems

Directory of Open Access Journals (Sweden)

Mihai ANDRONIE

2015-09-01

Full Text Available Airline industry is characterized by large quantities of complex, unstructured and rapid changing data that can be categorized as big data, requiring specialized analysis tools to explore it with the purpose of obtaining useful knowledge as decision support for companies that need to fundament their activities and improve the processes they are carrying on. In this context, business intelligence tools are valuable instruments that can optimally process airline related data so that the activities that are conducted can be optimized to maximize profits, while meeting customer requirements. An airline company that has access to large volumes of data (stored into conventional or big data repositories has two options to extract useful decision support information: processing data by using general-purpose business intelligence systems or processing data by using industry specific business intelligence systems. Each of these two options has both advantages and disadvantages for the airline companies that intend to use them. The present paper presents a comparative study of a number of general-purpose and airline industry specific business intelligence systems, together with their main advantages and disadvantages.

Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

Directory of Open Access Journals (Sweden)

Moteaal Asadi Shirzi

2007-03-01

Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

An intelligent, knowledge-based multiple criteria decision making advisor for systems design

Science.gov (United States)

Li, Yongchang

of an appropriate decision making method. Furthermore, some DMs may be exclusively using one or two specific methods which they are familiar with or trust and not realizing that they may be inappropriate to handle certain classes of the problems, thus yielding erroneous results. These issues reveal that in order to ensure a good decision a suitable decision method should be chosen before the decision making process proceeds. The first part of this dissertation proposes an MCDM process supported by an intelligent, knowledge-based advisor system referred to as Multi-Criteria Interactive Decision-Making Advisor and Synthesis process (MIDAS), which is able to facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. The second part of this dissertation presents an autonomous decision making advisor which is capable of dealing with ever-evolving real time information and making autonomous decisions under uncertain conditions. The advisor encompasses a Markov Decision Process (MDP) formulation which takes uncertainty into account when determines the best action for each system state. (Abstract shortened by UMI.)

Intelligent systems: A semiotic perspective. Volume I: Theoretical semiotics

Energy Technology Data Exchange (ETDEWEB)

Albus, J.; Meystel, A.; Quintero, R.

1996-12-31

This report contains the papers from the Proceedings of the 1996 International Multidisciplinary Conference - Theoretical Semiotics. General topics covered are: semiotic in biology: biologically inspired complex systems; intelligence in constructed complex systems; intelligence of learning and evolution; fuzzy logic and the mechanisms of generalization; information representation for decision making; sematic foundations; syntactics of intelligent systems: the kind of logic available; intelligence of recognition: the semiotic tools; and multiresolutional methods.

Intelligent decision-making models for production and retail operations

CERN Document Server

Guo, Zhaoxia

2016-01-01

This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.

The intelligent system for accident identification in NPP

International Nuclear Information System (INIS)

Hernandez, Jorge Luis.

1998-01-01

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

Modeling Common-Sense Decisions in Artificial Intelligence

Science.gov (United States)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation

Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease.

Science.gov (United States)

Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

2011-11-01

Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. To develop a clinical decision-support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision-support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k=0.68 (pdiagnosis. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery

Directory of Open Access Journals (Sweden)

Shu Tian

2015-01-01

Full Text Available The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a VidEo-Based Intelligent Recognitionand Decision (VEBIRD system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VEBIRD comprises a robust eye (iris detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VEBIRD’s effectiveness.

Towards An Intelligent Model-Based Decision Support System For An Integrated Oil Company (EGPC)

International Nuclear Information System (INIS)

Khorshid, M.; Hassan, H.; Abdel Latife, M.A.

2004-01-01

Decision Support System (DSS) is an interactive, flexible and adaptable computer-based support system specially developed for supporting the solution of unstructured management problems [31] DSS has become widespread for oil industry domain in recent years. The computer-based DSS, which were developed and implemented in oil industry, are used to address the complex short-term planning and operational issues associated with downstream industry. Most of these applications concentrate on the data-centered tools, while the model-centered applications of DSS are still very limited up till now [20]. This study develops an Intelligent Model-Based DSS for an integrated oil company, to help policy makers and petroleum planner in improving the effectiveness of the strategic planning in oil sector. This domain basically imposes semi-structured or unstructured decisions and involves a very complex modeling process

Interfacing An Intelligent Decision-Maker To A Real-Time Control System

Science.gov (United States)

Evers, D. C.; Smith, D. M.; Staros, C. J.

1984-06-01

This paper discusses some of the practical aspects of implementing expert systems in a real-time environment. There is a conflict between the needs of a process control system and the computational load imposed by intelligent decision-making software. The computation required to manage a real-time control problem is primarily concerned with routine calculations which must be executed in real time. On most current hardware, non-trivial AI software should not be forced to operate under real-time constraints. In order for the system to work efficiently, the two processes must be separated by a well-defined interface. Although the precise nature of the task separation will vary with the application, the definition of the interface will need to follow certain fundamental principles in order to provide functional separation. This interface was successfully implemented in the expert scheduling software currently running the automated chemical processing facility at Lockheed-Georgia. Potential applications of this concept in the areas of airborne avionics and robotics will be discussed.

Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

Science.gov (United States)

Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

2006-01-01

There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

System Interface for an Integrated Intelligent Safety System (ISS for Vehicle Applications

Directory of Open Access Journals (Sweden)

Mahammad A. Hannan

2010-01-01

Full Text Available This paper deals with the interface-relevant activity of a vehicle integrated intelligent safety system (ISS that includes an airbag deployment decision system (ADDS and a tire pressure monitoring system (TPMS. A program is developed in LabWindows/CVI, using C for prototype implementation. The prototype is primarily concerned with the interconnection between hardware objects such as a load cell, web camera, accelerometer, TPM tire module and receiver module, DAQ card, CPU card and a touch screen. Several safety subsystems, including image processing, weight sensing and crash detection systems, are integrated, and their outputs are combined to yield intelligent decisions regarding airbag deployment. The integrated safety system also monitors tire pressure and temperature. Testing and experimentation with this ISS suggests that the system is unique, robust, intelligent, and appropriate for in-vehicle applications.

Intelligent systems and soft computing for nuclear science and industry

International Nuclear Information System (INIS)

Ruan, D.; D'hondt, P.; Govaerts, P.; Kerre, E.E.

1996-01-01

The second international workshop on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS) addresses topics related to intelligent systems and soft computing for nuclear science and industry. The proceedings contain 52 papers in different fields such as radiation protection, nuclear safety (human factors and reliability), safeguards, nuclear reactor control, production processes in the fuel cycle, dismantling, waste and disposal, decision making, and nuclear reactor control. A clear link is made between theory and applications of fuzzy logic such as neural networks, expert systems, robotics, man-machine interfaces, and decision-support techniques by using modern and advanced technologies and tools. The papers are grouped in three sections. The first section (Soft computing techniques) deals with basic tools to treat fuzzy logic, neural networks, genetic algorithms, decision-making, and software used for general soft-computing aspects. The second section (Intelligent engineering systems) includes contributions on engineering problems such as knowledge-based engineering, expert systems, process control integration, diagnosis, measurements, and interpretation by soft computing. The third section (Nuclear applications) focusses on the application of soft computing and intelligent systems in nuclear science and industry

Development of intelligent supervisory control system

International Nuclear Information System (INIS)

Takizawa, Y.; Fukumoto, A.; Makino, M.; Takiguchi, S.

1994-01-01

The objective of the development of an intelligent supervisory control system for next generation plants is enhancement of the operational reliability by applying the recent outcome of artificial intelligence and computer technologies. This system consists of the supervisory control and monitoring for automatic operation, the equipment operation support for historical data management and for test scheduling, the operators' decision making support for accidental plant situations and the human-friendly interface of these support functions. The verification test results showed the validity of the functions realized by this system for the next generation control room. (author)

Business intelligence and decision making tools - New trends on romanian market

Directory of Open Access Journals (Sweden)

Ph.D. Silviu Cojocaru

2012-05-01

Full Text Available Despite the limits imposed by the computer’s impossibility to perfectly duplicate the human reasoning, the information systems that assist decision making and the business intelligence components are considered nowadays compulsory instruments of the modern manager; most of the daily decision procedures, the information required by the decision making process together with the information search and retrieval techniques are taken over completely by these systems. Furthermore, their continuous development, doubled the improvement of computers’ performances, offer increased possibilities to take over major parts of some of the most intense reasoning activities performed by humans

International Conference on Intelligent and Interactive Systems and Applications

CERN Document Server

Patnaik, Srikanta; Yu, Zhengtao

2017-01-01

This book provides the latest research findings and developments in the field of interactive intelligent systems, addressing diverse areas such as autonomous systems, Internet and cloud computing, pattern recognition and vision systems, mobile computing and intelligent networking, and e-enabled systems. It gathers selected papers from the International Conference on Intelligent and Interactive Systems and Applications (IISA2016) held on June 25–26, 2016 in Shanghai, China. Interactive intelligent systems are among the most important multi-disciplinary research and development domains of artificial intelligence, human–computer interaction, machine learning and new Internet-based technologies. Accordingly, these systems embrace a considerable number of application areas such as autonomous systems, expert systems, mobile systems, recommender systems, knowledge-based and semantic web-based systems, virtual communication environments, and decision support systems, to name a few. To date, research on interactiv...

Overview of Intelligent Systems and Operations Development

Science.gov (United States)

Pallix, Joan; Dorais, Greg; Penix, John

2004-01-01

To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.

The intelligent system for accident identification in nuclear power plant

International Nuclear Information System (INIS)

Hernandez, Jorge Luis.

1998-01-01

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

Management Intelligent Systems : First International Symposium

CERN Document Server

Martínez-López, Francisco; Rodríguez, Juan

2012-01-01

The 2012 International Symposium on Management Intelligent Systems is believed to be the first international forum to present and discuss original, rigorous and significant contributions on Artificial Intelligence-based (AI) solutions—with a strong, practical logic and, preferably, with empirical applications—developed to aid the management of organizations in multiple areas, activities, processes and problem-solving; i.e., what we propose to be named as Management Intelligent Systems (MiS). The three-day event aimed to bring together researchers interested in this promising interdisciplinary field who came from areas as varied as management, marketing, and business in general, computer science, artificial intelligence, statistics, etc. This volume presents the proceedings of these activities in a collection of contributions with many original approaches. They address diverse Management and Business areas of application such as decision support, segmentation of markets, CRM, product design, service person...

An intelligent agent for optimal river-reservoir system management

Science.gov (United States)

Rieker, Jeffrey D.; Labadie, John W.

2012-09-01

A generalized software package is presented for developing an intelligent agent for stochastic optimization of complex river-reservoir system management and operations. Reinforcement learning is an approach to artificial intelligence for developing a decision-making agent that learns the best operational policies without the need for explicit probabilistic models of hydrologic system behavior. The agent learns these strategies experientially in a Markov decision process through observational interaction with the environment and simulation of the river-reservoir system using well-calibrated models. The graphical user interface for the reinforcement learning process controller includes numerous learning method options and dynamic displays for visualizing the adaptive behavior of the agent. As a case study, the generalized reinforcement learning software is applied to developing an intelligent agent for optimal management of water stored in the Truckee river-reservoir system of California and Nevada for the purpose of streamflow augmentation for water quality enhancement. The intelligent agent successfully learns long-term reservoir operational policies that specifically focus on mitigating water temperature extremes during persistent drought periods that jeopardize the survival of threatened and endangered fish species.

Intelligent Decision-Making System with Green Pervasive Computing for Renewable Energy Business in Electricity Markets on Smart Grid

Directory of Open Access Journals (Sweden)

Park JongHyuk

2009-01-01

Full Text Available This paper is about the intelligent decision-making system for the smart grid based electricity market which requires distributed decision making on the competitive environments composed of many players and components. It is very important to consider the renewable energy and emission problem which are expected to be monitored by wireless communication networks. It is very difficult to predict renewable energy outputs and emission prices over time horizon, so it could be helpful to catch up those data on real time basis using many different kinds of communication infrastructures. On this backgrounds this paper provides an algorithm to make an optimal decision considering above factors.

Artificial Intelligence Framework for Simulating Clinical Decision-Making: A Markov Decision Process Approach

OpenAIRE

Bennett, Casey C.; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This serves two potential functions: 1) a simulation environment for expl...

Logical Aspects Regarding the Conception of Intelligent Systems

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Vasile Mazilescu

2016-07-01

Full Text Available The present paper presents some logical aspects of symbolic AI Systems, applied to the Intelligent Systems design. The basic feature of these systems is represented by the processing of the imprecise and dynamic knowledge involved in the synthesis of some decisions. We consider that the paper tackles an up-to-date and little debated aspect especially in the field of decision fuzzy systems. Knowledge-based systems with real-time functioning bear features that the majority of classic systems do not have: reasoning is evolutionary and non-monotonous due to the dynamic nature of the application, and events can change the status of the expert management system. The management architectures based on symbolic techniques acquire characteristics specific to the domain problem and to the type of intelligent system based on a management knowledge structure.

Affordances and Constraints of Intelligent Decision Support for Military Command and Control : Three Case Studies of Support Systems

OpenAIRE

Leifler, Ola

2011-01-01

Researchers in military command and control (C2) have for several decades sought to help commanders by introducing automated, intelligent decision support systems. These systems are still not widely used, however, and some researchers argue that this may be due to those problems that are inherent in the relationship between the affordances of technology and the requirements by the specific contexts of work in military C2. In this thesis, we study some specific properties of three support tech...

Argumentative SOX Compliant and Quality Decision Support Intelligent Expert System over the Suppliers Selection Process

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Jesus Angel Fernandez Canelas

2013-01-01

Full Text Available The objective of this paper is to define a decision support system over SOX (Sarbanes-Oxley Act compatibility and quality of the Suppliers Selection Process based on Artificial Intelligence and Argumentation Theory knowledge and techniques. The present SOX Law, in effect nowadays, was created to improve financial government control over US companies. This law is a factor standard out United States due to several factors like present globalization, expansion of US companies, or key influence of US stock exchange markets worldwide. This paper constitutes a novel approach to this kind of problems due to following elements: (1 it has an optimized structure to look for the solution, (2 it has a dynamic learning method to handle court and control gonvernment bodies decisions, (3 it uses fuzzy knowledge to improve its performance, and (4 it uses its past accumulated experience to let the system evolve far beyond its initial state.

Intelligent Flight Support System (IFSS): A Real-time Intelligent Decision Support Prototype, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The integration of the analysis tools with the advanced visualization capabilities in The Intelligent Flight Support System (IFSS) can provide a unique method for...

Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

Science.gov (United States)

Bennett, Casey C; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal

The role of logistics information system in the business-decision process

OpenAIRE

Galicic, Vlado; Pilepic, Ljubica

2007-01-01

The development of logistics information systems that support decision-making, together with the use of business intelligence, provides assistance and support to logistics managers in the decision process, thereby impacting on the quality of business and productivity. Being better informed and having greater intelligence for decision-making can help to create new value and gain competitive advantage. Logistics business systems in a tourism destination appreciate the importance of information ...

Handling risk attitudes for preference learning and intelligent decision support

DEFF Research Database (Denmark)

Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt

2015-01-01

Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...

Markov decision processes in artificial intelligence

CERN Document Server

Sigaud, Olivier

2013-01-01

Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as Reinforcement Learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in Artificial Intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, Reinforcement Learning, Partially Observable MDPs, Markov games and the use of non-classical criteria). Then it presents more advanced research trends in the domain and gives some concrete examples using illustr

BUSINESS INTELLIGENCE TOOLS FOR DATA ANALYSIS AND DECISION MAKING

Directory of Open Access Journals (Sweden)

DEJAN ZDRAVESKI

2011-04-01

Full Text Available Every business is dynamic in nature and is affected by various external and internal factors. These factors include external market conditions, competitors, internal restructuring and re-alignment, operational optimization and paradigm shifts in the business itself. New regulations and restrictions, in combination with the above factors, contribute to the constant evolutionary nature of compelling, business-critical information; the kind of information that an organization needs to sustain and thrive. Business intelligence (“BI” is broad term that encapsulates the process of gathering information pertaining to a business and the market it functions in. This information when collated and analyzed in the right manner, can provide vital insights into the business and can be a tool to improve efficiency, reduce costs, reduce time lags and bring many positive changes. A business intelligence application helps to achieve precisely that. Successful organizations maximize the use of their data assets through business intelligence technology. The first data warehousing and decision support tools introduced companies to the power and benefits of accessing and analyzing their corporate data. Business users at every level found new, more sophisticated ways to analyze and report on the information mined from their vast data warehouses.Choosing a Business Intelligence offering is an important decision for an enterprise, one that will have a significant impact throughout the enterprise. The choice of a BI offering will affect people up and down the chain of command (senior management, analysts, and line managers and across functional areas (sales, finance, and operations. It will affect business users, application developers, and IT professionals. BI applications include the activities of decision support systems (DSS, query and reporting, online analyticalprocessing (OLAP, statistical analysis, forecasting, and data mining. Another way of phrasing this is

An Intelligent Support System for Energy Resources in the United States.

Science.gov (United States)

Rosenberg, S.

Based on artificial intelligence research, the frame based system for reasoning described in this paper is one of the components of an intelligent decision support system for an information system on petroleum resources and use which is being designed by the Information Methodology Research Project as the first step in the development of a…

Transformational Leadership Style as Predictor of Decision Making Styles: Moderating Role of Emotional Intelligence

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Rana Rashid Rehman

2012-12-01

Full Text Available The current study examines the relationship among transformational leadership style and decision making styles. It also determines the moderating role of emotional intelligence in predicting this relationship. Three hypotheses are generated for the study i.e., twohypotheses are to measure the relationship among transformational leadership style and decision making styles whereas third hypothesis is to assess the moderating effect of emotional intelligence. Questionnaire method is used to collect data from 113respondents. Regression analysis is utilized to study the relationship among transformational leadership style and decision making styles and step-wise regression analysis is used to study moderating effect of emotional intelligence. The study foundthat transformational leadership style strongly predicts rational and dependant decision making styles and weakly predict intuitive and spontaneous decision making styles while no association founds with avoidant decision making styles. Present research also foundthat emotional intelligence moderates the relationship among transformational leadership style and decision making styles.

Emotional Intelligence, Personality Traits and Career Decision Difficulties

Science.gov (United States)

Di Fabio, Annamaria; Palazzeschi, Letizia

2009-01-01

This study aims to take an in-depth look at the role of emotional intelligence and personality traits in relation to career decision difficulties. The Italian version of the Career Decision Difficulties Questionnaire (CDDQ), the Bar-On Emotional Quotient Inventory: Short (Bar-On EQ-i: S), and the Big Five Questionnaire (BFQ) were administered to…

Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

Science.gov (United States)

Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

1987-01-01

In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

Systems with artificial intelligence in nuclear power plant operation

International Nuclear Information System (INIS)

Bastl, W.; Felkel, L.

1989-01-01

The authors first summarize some developments made by GRS teams which can be regarded as the precursors of systems with artificial intelligence, and explain the basic characteristics of artificial intelligence, referring in particular to possible applications in nuclear engineering. The systems described are arranged in four groups according to applicability as follows: plant diagnosis and failure analysis, information systems and operating systems, control systems, assessment and decision aids. The working principle of the systems is explained by some examples giving details of the database and the interference processes. (orig./DG) [de

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...

From Management Information Systems to Business Intelligence: The Development of Management Information Needs

Directory of Open Access Journals (Sweden)

Gėlytė Kazakevičienė

2013-09-01

Full Text Available Despite the advances in IT, information systems intended for management informing did not uniformly fulfil the increased expectations of users; this can be said mostly about complex information needs. Although some of the technologies for supporting complicated insights, like management decision support systems and technologies, experienced reduction in interest both from researchers and practitioners, this did not reduce the importance of well-supported business informing and decision making. Being attributed to the group of intelligent systems and technologies, decision support (DS technologies have been largely supplemented by business intelligence (BI technologies. Both types of technologies are supported by respective information technologies, which often appear to be quite closely related. The objective of this paper is to define relations between simple and complex informing intended to satisfy different sets of needs and provided by different sets of support tools. The paper attempts to put together decision support and business intelligence technologies, based on common goals of sense-making and use of advanced analytical tools. A model of two interconnected cycles has been developed to relate the activities of decision support and business intelligence. Empirical data from earlier research is used to direct possible further insights into this area.

SAMS--a systems architecture for developing intelligent health information systems.

Science.gov (United States)

Yılmaz, Özgün; Erdur, Rıza Cenk; Türksever, Mustafa

2013-12-01

In this paper, SAMS, a novel health information system architecture for developing intelligent health information systems is proposed and also some strategies for developing such systems are discussed. The systems fulfilling this architecture will be able to store electronic health records of the patients using OWL ontologies, share patient records among different hospitals and provide physicians expertise to assist them in making decisions. The system is intelligent because it is rule-based, makes use of rule-based reasoning and has the ability to learn and evolve itself. The learning capability is provided by extracting rules from previously given decisions by the physicians and then adding the extracted rules to the system. The proposed system is novel and original in all of these aspects. As a case study, a system is implemented conforming to SAMS architecture for use by dentists in the dental domain. The use of the developed system is described with a scenario. For evaluation, the developed dental information system will be used and tried by a group of dentists. The development of this system proves the applicability of SAMS architecture. By getting decision support from a system derived from this architecture, the cognitive gap between experienced and inexperienced physicians can be compensated. Thus, patient satisfaction can be achieved, inexperienced physicians are supported in decision making and the personnel can improve their knowledge. A physician can diagnose a case, which he/she has never diagnosed before, using this system. With the help of this system, it will be possible to store general domain knowledge in this system and the personnel's need to medical guideline documents will be reduced.

Developmental reversals in risky decision making: intelligence agents show larger decision biases than college students.

Science.gov (United States)

Reyna, Valerie F; Chick, Christina F; Corbin, Jonathan C; Hsia, Andrew N

2014-01-01

Intelligence agents make risky decisions routinely, with serious consequences for national security. Although common sense and most theories imply that experienced intelligence professionals should be less prone to irrational inconsistencies than college students, we show the opposite. Moreover, the growth of experience-based intuition predicts this developmental reversal. We presented intelligence agents, college students, and postcollege adults with 30 risky-choice problems in gain and loss frames and then compared the three groups' decisions. The agents not only exhibited larger framing biases than the students, but also were more confident in their decisions. The postcollege adults (who were selected to be similar to the students) occupied an interesting middle ground, being generally as biased as the students (sometimes more biased) but less biased than the agents. An experimental manipulation testing an explanation for these effects, derived from fuzzy-trace theory, made the students look as biased as the agents. These results show that, although framing biases are irrational (because equivalent outcomes are treated differently), they are the ironical output of cognitively advanced mechanisms of meaning making.

Artificial intelligence and foreign policy decision-making

OpenAIRE

Berkoff, Russ H.

1997-01-01

Approved for public release; distribution is unlimited With the advent of a global information society, the US will seek to tap the potential of advanced computing capability to enhance its ability to conduct foreign policy decision making. This thesis explores the potential for improving individual and organizational decision making capabilities by means of artificial intelligence (AI). The use of AI will allow us to take advantage of the plethora of information available to obtain an edg...

An Intelligent Handover Management System for Future Generation Wireless Networks

Directory of Open Access Journals (Sweden)

Kassar Meriem

2008-01-01

Full Text Available Abstract Future generation wireless networks should provide to mobile users the best connectivity to services anywhere at anytime. The most challenging problem is the seamless intersystem/vertical mobility across heterogeneous wireless networks. In order to answer it, a vertical handover management system is needed. In our paper, we propose an intelligent solution answering user requirements and ensuring service continuity. We focus on a vertical handover decision strategy based on the context-awareness concept. The given strategy chooses the appropriate time and the most suitable access network among those available to perform a handover. It uses advanced decision algorithms (for more efficiency and intelligence and it is governed by handover policies as decision rules (for more flexibility and optimization. To maintain a seamless service continuity, handover execution is based on mobile IP functionalities. We study our decision system in a case of a 3G/UMTS-WLAN scenario and we discuss all the handover decision issues in our solution.

Establishment and application of Competitive Intelligence System in Mobile Devices

Directory of Open Access Journals (Sweden)

Anass El Haddadi

2011-12-01

Full Text Available The strategy concept has changed dramatically: from a long range planning to strategic planning then to strategic responsiveness. This response implies moving from a concept of change to a concept of continuous evolution. In our context, the competitive intelligence system presented aims to improve decision‐making in all aspects of business life, particularly for offensive and innovative decisions. In the paper we present XPlor EveryWhere, our competitive intelligence system based on a multidimensional analysis model for mobile devices. The objective of this system is to capture the information environment in all dimensions of a decision problem, with the exploitation of information by analyzing the evolution of their interactions

The potential for intelligent decision support systems to improve the quality and consistency of medication reviews.

Science.gov (United States)

Bindoff, I; Stafford, A; Peterson, G; Kang, B H; Tenni, P

2012-08-01

Drug-related problems (DRPs) are of serious concern worldwide, particularly for the elderly who often take many medications simultaneously. Medication reviews have been demonstrated to improve medication usage, leading to reductions in DRPs and potential savings in healthcare costs. However, medication reviews are not always of a consistently high standard, and there is often room for improvement in the quality of their findings. Our aim was to produce computerized intelligent decision support software that can improve the consistency and quality of medication review reports, by helping to ensure that DRPs relevant to a patient are overlooked less frequently. A system that largely achieved this goal was previously published, but refinements have been made. This paper examines the results of both the earlier and newer systems. Two prototype multiple-classification ripple-down rules medication review systems were built, the second being a refinement of the first. Each of the systems was trained incrementally using a human medication review expert. The resultant knowledge bases were analysed and compared, showing factors such as accuracy, time taken to train, and potential errors avoided. The two systems performed well, achieving accuracies of approximately 80% and 90%, after being trained on only a small number of cases (126 and 244 cases, respectively). Through analysis of the available data, it was estimated that without the system intervening, the expert training the first prototype would have missed approximately 36% of potentially relevant DRPs, and the second 43%. However, the system appeared to prevent the majority of these potential expert errors by correctly identifying the DRPs for them, leaving only an estimated 8% error rate for the first expert and 4% for the second. These intelligent decision support systems have shown a clear potential to substantially improve the quality and consistency of medication reviews, which should in turn translate into

13th International Conference Intelligent Autonomous Systems

CERN Document Server

Michael, Nathan; Berns, Karsten; Yamaguchi, Hiroaki

2016-01-01

This book describes the latest research accomplishments, innovations, and visions in the field of robotics as presented at the 13th International Conference on Intelligent Autonomous Systems (IAS), held in Padua in July 2014, by leading researchers, engineers, and practitioners from across the world. The contents amply confirm that robots, machines, and systems are rapidly achieving intelligence and autonomy, mastering more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision making. A wide range of research results and applications are covered, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions have been selected through a rigorous peer-review process and contain many exciting and visionary ideas that will further galvanize the research community, spurring novel research directions. The series of biennial IAS conferences ...

Intelligent decision support algorithm for distribution system restoration.

Science.gov (United States)

Singh, Reetu; Mehfuz, Shabana; Kumar, Parmod

2016-01-01

Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network's parameters. Thus, an intelligent algorithm incorporating hybrid fuzzy-grey relation, which can take into account the uncertainties and compare the sequences is discussed to analyse and restore the distribution system. The simulation studies are carried out to show the utility of the method by ranking the restoration plans for a typical distribution system. This algorithm also meets the smart grid requirements in terms of an automated restoration plan for the partial/full blackout of network.

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…

Operator support system using computational intelligence techniques

International Nuclear Information System (INIS)

Bueno, Elaine Inacio; Pereira, Iraci Martinez

2015-01-01

Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

Operator support system using computational intelligence techniques

Energy Technology Data Exchange (ETDEWEB)

Bueno, Elaine Inacio, E-mail: ebueno@ifsp.edu.br [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Sao Paulo, SP (Brazil); Pereira, Iraci Martinez, E-mail: martinez@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2015-07-01

Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

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

OpenAIRE

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

2017-01-01

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

Making intelligent systems team players. A guide to developing intelligent monitoring systems

Science.gov (United States)

Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

1995-01-01

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Intelligence from Space: Using Geographical Information Systems for Competitive Intelligence

NARCIS (Netherlands)

Hendriks, P.H.J.; Vriens, D.J.

2003-01-01

The spatial element, which is omnipresent in data and information relevant to organizations, is much underused in the decision-making processes within organizations. This applies also to decision-making within the domain of Competitive Intelligence. The chapter explores how the CI function may

Emotional Intelligence and risk taking in investment decision-making

OpenAIRE

Enrico Rubaltelli; Sergio Agnoli; Michela Rancan; Tiziana Pozzoli

2015-01-01

Previous work on investment decision-making suggested that emotions prevent investors from taking risks and from investing in a rational way, whereas other work found that there is great variability in people’s ability to manage and use emotional feedbacks. We hypothesized that people with high trait emotional intelligence should be more willing, than people with low trait emotional intelligence, to accept risks when making an investment. Data supported a model in which trait emotional intell...

Affective Decision Making in Artificial Intelligence : Making Virtual Characters With High Believability

OpenAIRE

Johansson, Anja

2012-01-01

Artificial intelligence is often used when creating believable virtual characters in games or in other types of virtual environments. The intelligent behavior these characters show to the player is often flawed, leading to a worse gameplay experience. In particular, there is often little or no emotional impact on the decision making of the characters. This thesis focuses on extending decision-making and pathfinding mechanisms for virtual characters, with a particular focus on the use of emoti...

SART: an intelligent assistant system for subway control

Directory of Open Access Journals (Sweden)

P. Brézillon

2000-12-01

Full Text Available One of the main characteristics of a subway line is its large transport capacity (e.g., about 60000 travelers per hour in the Parisian subway combined with a regular transport supply. The regularity is particularly important at rush time - peak hours - when an incident can provoke important delays. Experience shows that the consequences of an incident are highly dependent on the context in which the incident occurs (e.g., peak hours or not. The decisions taken by the operators are heavily relied on the incident context, and operators often make different decisions for the same incident in different contexts. The project SART (French acronym for Support system for traffic control aims at developing an intelligent decision support system able of helping the operator in making decisions to solve an incident occurring on a line. This system relies on the notion of context. Context includes information and knowledge on the situation that do not intervene directly in the incident solving, but constrain the way in which the operator will choose a strategy at each step of the incident solving. The paper describes the SART project and highlights how Artificial Intelligence (AI techniques can contributeto knowledge acquisition and knowledge representation associated with its context of use. Particularly we discuss the notion of context and show how we use this notion to solve a real-world problem.

14th International Conference on Intelligent Autonomous Systems

CERN Document Server

Hosoda, Koh; Menegatti, Emanuele; Shimizu, Masahiro; Wang, Hesheng

2017-01-01

This book describes the latest research advances, innovations, and visions in the field of robotics as presented by leading researchers, engineers, and practitioners from around the world at the 14th International Conference on Intelligent Autonomous Systems (IAS-14), held in Shanghai, China in July 2016. The contributions amply demonstrate that robots, machines and systems are rapidly achieving intelligence and autonomy, attaining more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision-making. They cover a wide range of research results and applications, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions were selected by means of a rigorous peer-review process and highlight many exciting and visionary ideas that will further galvanize the research community and spur novel research directions. The series of biennial IAS ...

Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

Science.gov (United States)

Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

2005-02-01

An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

An Intelligent Clinical Decision Support System for Patient-Specific Predictions to Improve Cervical Intraepithelial Neoplasia Detection

Directory of Open Access Journals (Sweden)

Panagiotis Bountris

2014-01-01

Full Text Available Nowadays, there are molecular biology techniques providing information related to cervical cancer and its cause: the human Papillomavirus (HPV, including DNA microarrays identifying HPV subtypes, mRNA techniques such as nucleic acid based amplification or flow cytometry identifying E6/E7 oncogenes, and immunocytochemistry techniques such as overexpression of p16. Each one of these techniques has its own performance, limitations and advantages, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this article we propose a clinical decision support system (CDSS, composed by artificial neural networks, intelligently combining the results of classic and ancillary techniques for diagnostic accuracy improvement. We evaluated this method on 740 cases with complete series of cytological assessment, molecular tests, and colposcopy examination. The CDSS demonstrated high sensitivity (89.4%, high specificity (97.1%, high positive predictive value (89.4%, and high negative predictive value (97.1%, for detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+. In comparison to the tests involved in this study and their combinations, the CDSS produced the most balanced results in terms of sensitivity, specificity, PPV, and NPV. The proposed system may reduce the referral rate for colposcopy and guide personalised management and therapeutic interventions.

An intelligent clinical decision support system for patient-specific predictions to improve cervical intraepithelial neoplasia detection.

Science.gov (United States)

Bountris, Panagiotis; Haritou, Maria; Pouliakis, Abraham; Margari, Niki; Kyrgiou, Maria; Spathis, Aris; Pappas, Asimakis; Panayiotides, Ioannis; Paraskevaidis, Evangelos A; Karakitsos, Petros; Koutsouris, Dimitrios-Dionyssios

2014-01-01

Nowadays, there are molecular biology techniques providing information related to cervical cancer and its cause: the human Papillomavirus (HPV), including DNA microarrays identifying HPV subtypes, mRNA techniques such as nucleic acid based amplification or flow cytometry identifying E6/E7 oncogenes, and immunocytochemistry techniques such as overexpression of p16. Each one of these techniques has its own performance, limitations and advantages, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this article we propose a clinical decision support system (CDSS), composed by artificial neural networks, intelligently combining the results of classic and ancillary techniques for diagnostic accuracy improvement. We evaluated this method on 740 cases with complete series of cytological assessment, molecular tests, and colposcopy examination. The CDSS demonstrated high sensitivity (89.4%), high specificity (97.1%), high positive predictive value (89.4%), and high negative predictive value (97.1%), for detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+). In comparison to the tests involved in this study and their combinations, the CDSS produced the most balanced results in terms of sensitivity, specificity, PPV, and NPV. The proposed system may reduce the referral rate for colposcopy and guide personalised management and therapeutic interventions.

NED-IIS: An Intelligent Information System for Forest Ecosystem Management

Science.gov (United States)

W.D. Potter; S. Somasekar; R. Kommineni; H.M. Rauscher

1999-01-01

We view Intelligent Information System (IIS) as composed of a unified knowledge base, database, and model base. The model base includes decision support models, forecasting models, and cvsualization models for example. In addition, we feel that the model base should include domain specific porblems solving modules as well as decision support models. This, then,...

The role of auditory spectro-temporal modulation filtering and the decision metric for speech intelligibility prediction

DEFF Research Database (Denmark)

Chabot-Leclerc, Alexandre; Jørgensen, Søren; Dau, Torsten

2014-01-01

Speech intelligibility models typically consist of a preprocessing part that transforms stimuli into some internal (auditory) representation and a decision metric that relates the internal representation to speech intelligibility. The present study analyzed the role of modulation filtering...... in the preprocessing of different speech intelligibility models by comparing predictions from models that either assume a spectro-temporal (i.e., two-dimensional) or a temporal-only (i.e., one-dimensional) modulation filterbank. Furthermore, the role of the decision metric for speech intelligibility was investigated...... subtraction. The results suggested that a decision metric based on the SNRenv may provide a more general basis for predicting speech intelligibility than a metric based on the MTF. Moreover, the one-dimensional modulation filtering process was found to be sufficient to account for the data when combined...

[Intelligent systems tools in the diagnosis of acute coronary syndromes: A systemic review].

Science.gov (United States)

Sprockel, John; Tejeda, Miguel; Yate, José; Diaztagle, Juan; González, Enrique

2017-03-27

Acute myocardial infarction is the leading cause of non-communicable deaths worldwide. Its diagnosis is a highly complex task, for which modelling through automated methods has been attempted. A systematic review of the literature was performed on diagnostic tests that applied intelligent systems tools in the diagnosis of acute coronary syndromes. A systematic review of the literature is presented using Medline, Embase, Scopus, IEEE/IET Electronic Library, ISI Web of Science, Latindex and LILACS databases for articles that include the diagnostic evaluation of acute coronary syndromes using intelligent systems. The review process was conducted independently by 2 reviewers, and discrepancies were resolved through the participation of a third person. The operational characteristics of the studied tools were extracted. A total of 35 references met the inclusion criteria. In 22 (62.8%) cases, neural networks were used. In five studies, the performances of several intelligent systems tools were compared. Thirteen studies sought to perform diagnoses of all acute coronary syndromes, and in 22, only infarctions were studied. In 21 cases, clinical and electrocardiographic aspects were used as input data, and in 10, only electrocardiographic data were used. Most intelligent systems use the clinical context as a reference standard. High rates of diagnostic accuracy were found with better performance using neural networks and support vector machines, compared with statistical tools of pattern recognition and decision trees. Extensive evidence was found that shows that using intelligent systems tools achieves a greater degree of accuracy than some clinical algorithms or scales and, thus, should be considered appropriate tools for supporting diagnostic decisions of acute coronary syndromes. Copyright © 2017 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

Directory of Open Access Journals (Sweden)

Muhammad Faisal Siddiqui

Full Text Available A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT, principal component analysis (PCA, and least squares support vector machine (LS-SVM are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%. Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities

An intelligent man-machine system for future nuclear power plants

International Nuclear Information System (INIS)

Takizawa, Yoji; Hattori, Yoshiaki; Itoh, Juichiro; Fukumoto, Akira

1994-01-01

The objective of the development of an intelligent man-machine system for future nuclear power plants is enhancement of operational reliability by applying recent advances in cognitive science, artificial intelligence, and computer technologies. To realize this objective, the intelligent man-machine system, aiming to support a knowledge-based decision making process in an operator's supervisory plant control tasks, consists of three main functions, i.e., a cognitive model-based advisor, a robust automatic sequence controller, and an ecological interface. These three functions have been integrated into a console-type nuclear power plant monitoring and control system as a validation test bed. The validation tests in which experienced operator crews participated were carried out in 1991 and 1992. The test results show the usefulness of the support functions and the validity of the system design approach

INTELLIGENT DECISION SUPPORT ON FOREX

Directory of Open Access Journals (Sweden)

V. A. Rybak

2014-01-01

Full Text Available A new technology of intelligent decision support on Forex, including forming algorithms of trading signals, rules for the training sample based on technical indicators, which have the highest correlation with the price, the method of reducing the number of losing trades, is proposed. The last is based on an analysis of the wave structure of the market, while the beginning of the cycle (the wave number one is offered to be identified using Bill Williams Oscillator (Awesome oscillator. The process chain of constructing neuro-fuzzy model using software package MatLab is described.

Business Intelligence Systems

Directory of Open Access Journals (Sweden)

Bogdan NEDELCU

2014-02-01

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

Implementing a Business Intelligence System for small and medium-sized enterprises

OpenAIRE

Sang, G.; Xu, Lai; de Vrieze, Paul Ton

2016-01-01

Over the years, Business Intelligence (BI) systems have become critically important to organizations due to the increasing fast-paced competition, the vast amount of daily generated data and the complexity of how to manage collected data. Business intelligence systems empower organizations to gain insights and to understand a clearer view of their vast data, business and customers, which help to make better decisions and hence produce better results and increase profit. BI refers to a collect...

The Development of Financial Information System and Business Intelligence Using Data Mining Concepts

OpenAIRE

PVD PRASAD

2014-01-01

One of the most emerging technologies is finance, becoming more amenable to data-driven modeling as large sets of financial data become available everywhere. So we are applying the data mining techniques in financial information system with Business Intelligence. A Business Intelligence System (BIS) can be described as an interactive, computer-based system designed to help decision-makers to solve unstructured problems. Using a combination of models, analytical techniques, and...

Intelligent power system data management systems (DBMS)

Energy Technology Data Exchange (ETDEWEB)

Middleton, A.; Macdonald, E. [GE Digital Energy, Markham, ON (Canada); Schreiner, Z. [Intelligent Process Solutions GmbH, Lindau (Germany); Bizjak, J. [Elektro Ljubljana d.d., Ljubljana (Slovenia)

2010-07-01

Network owners/operators from around the world have moved from electromechanical products to intelligent electronic devices (IEDs). Most networks have a multi-generation technology mix because protection assets have a normal application lifespan of between 10 and 40 years. Associated data capture and maintenance management regimes have therefore moved from paper based into digitized media, creating a significant increase in the volume of acquired data, such that there is now a mix of paper and digitized storage. Data is rarely consolidated or used for decision making in asset management processes once testing is completed, having a major impact on overall power system reliability. This paper presented the concept of intelligent operative maintenance management, now becoming more recognized in the industry. The concept was described as the management of operational data, resulting actions and responses, wherever and by whoever they are needed, without any additional overhead. The paper discussed new techniques of testing as well as planning and operative maintenance. The practical benefits of the new system were also presented, with particular reference to central management; simplification of routine protocols; secondary testing; and reduced cost of data handling. It was concluded that the main benefit from all of the techniques discussed in this paper is that experienced expert test engineers can focus more time upon making good, critical decisions to ensure that utilities maximize their customer service and safety regimes. 13 refs., 7 figs.

Intelligent monitoring, control, and security of critical infrastructure systems

CERN Document Server

Polycarpou, Marios

2015-01-01

This book describes the challenges that critical infrastructure systems face, and presents state of the art solutions to address them. How can we design intelligent systems or intelligent agents that can make appropriate real-time decisions in the management of such large-scale, complex systems? What are the primary challenges for critical infrastructure systems? The book also provides readers with the relevant information to recognize how important infrastructures are, and their role in connection with a society’s economy, security and prosperity. It goes on to describe state-of-the-art solutions to address these points, including new methodologies and instrumentation tools (e.g. embedded software and intelligent algorithms) for transforming and optimizing target infrastructures. The book is the most comprehensive resource to date for professionals in both the private and public sectors, while also offering an essential guide for students and researchers in the areas of modeling and analysis of critical in...

Combining NDE and fracture mechanics by artifical intelligence expert systems techniques

International Nuclear Information System (INIS)

Mucciardi, A.N.; Riccardella, P.C.

1986-01-01

This paper reports on the development of a PC-based expert system for non-destructive evaluation. Software tools from the expert systems subfield of artificial intelligence are being used to combine both NDE and fracture mechanics algorithms into one, unified package. The system incorporates elements of computer-enhanced ultrasonic signal processing, featuring artificial intelligence learning capability, state-of-the-art fracture mechanics analytical tools, and all relevant metallurgical and design data necessary to emulate the decisions of the panel(s) of experts typically involved in generating and dispositioning NDE data

Business intelligence and financial decision-making: a theoretical approach

OpenAIRE

Mary Julieth Murillo Junco; Gustavo Cáceres Castellanos

2013-01-01

This paper deals with a literature review about the origin, development and implementation of Business Intelligence focused directly to solving problems in the financial area of the different organizations. Wanted contextualize how it tools have been incorporated into the decision making processes of modern business. A feature of the way it makes decisions has to do with the rational use made of the information available, and it is in this field where information technology and communication ...

Operation and safety decision-making support expert system in NPP

International Nuclear Information System (INIS)

Wei Yanhui; Su Desong; Chen Weihua; Zhang Jianbo

2014-01-01

The article first reviewed three operation support systems currently used in NPP: real-time information surveillance system, important equipment surveillance system and plant process control and monitoring system, then presents the structure and function of three expert support sub-systems (intelligent alarm monitoring system, computer-based operating procedure support system, safety information expert decision support system). Finally the article discussed the meaning of a kind of operation decision making support system. (authors)

Transformational Leadership Style as Predictor of Decision Making Styles: Moderating Role of Emotional Intelligence

OpenAIRE

Rana Rashid Rehman; Ajmal Waheed

2012-01-01

The current study examines the relationship among transformational leadership style and decision making styles. It also determines the moderating role of emotional intelligence in predicting this relationship. Three hypotheses are generated for the study i.e., twohypotheses are to measure the relationship among transformational leadership style and decision making styles whereas third hypothesis is to assess the moderating effect of emotional intelligence. Questionnaire method is used to coll...

Intelligent System in Some Decision Classes' Environment

Directory of Open Access Journals (Sweden)

Mariusz Swiecicki

1999-01-01

Full Text Available One of the trends in the information theory of recent years is a dynamic development of decentralized, intelligent information systems. The systems in question are so complex that the classical methods of describing their dynamics, prove to be insufficient. One of the possible ways of describing them is by applying, the model of an agent which constitutes an independent entity existing in its own right. The agent has its own inventory of objectives and the ability to interact with the environment and adapt to the changes which take place in this environment. The paper presents the conception of autonomous agent as a cybcrnetic model of an autonomous system. lt is based on psychological and biological phenomena which may be observed in living organisms. The description of the system distinguishes between three basic functional blocks: correlator, homeostasis and accumulator; it contains a detailed account of the functions and mutual correlations and interactions. Subsequently, the paper presents a classification of interactions between correlator and homeostatis, as well as between homeostasis and accumulator. An analysis of the autonomous system from the point of view of the psychological and biological phenomena which take place in it, has allowed one to borrow certain educational methods from beha vioural psychology (clusical conditioning, instrumental conditioning and apply them to the teaching ofthese type of systems. The paper presents the implementation of these type of systems in artificial neuron networks. Subsequently, the authors show how in practical terms these type of systems may be taught by means of the above mentioned methods. Lastly, the paper presents the application of the above systems to the leaming process together with the discussion ofthe accompanying phenomena.

A fuzzy TOPSIS model to evaluate the Business Intelligence competencies of Port Community Systems

Directory of Open Access Journals (Sweden)

Ghazanfari Mehdi

2014-04-01

Full Text Available Evaluation of the Business Intelligence (BI competencies of port community systems before they are bought and deployed is a vital importance for establishment of a decision-support environment for managers. This study proposes a new model which provides a simple approach to the assessment of the BI competencies of port community systems in organization. This approach helps decision-makers to select an enterprise system with appropriate intelligence requirements to support the managers’ decision-making tasks. Thirtyfour criteria for BI specifications are determined from a thorough review of the literature. The proposed model uses the fuzzy TOPSIS technique, which employs fuzzy weights of the criteria and fuzzy judgments of port community systems to compute the evaluation scores and rankings. The application of the model is realized in the evaluation, ranking and selecting of the needed port community systems in a port and maritime organization, in order to validate the proposed model with a real application. With utilizing the proposed model organizations can assess, select, and purchase port community systems which will provide a better decision-support environment for their business systems.

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.

9th Asian Conference on Intelligent Information and Database Systems

CERN Document Server

Nguyen, Ngoc; Shirai, Kiyoaki

2017-01-01

This book presents recent research in intelligent information and database systems. The carefully selected contributions were initially accepted for presentation as posters at the 9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017) held from to 5 April 2017 in Kanazawa, Japan. While the contributions are of an advanced scientific level, several are accessible for non-expert readers. The book brings together 47 chapters divided into six main parts: • Part I. From Machine Learning to Data Mining. • Part II. Big Data and Collaborative Decision Support Systems, • Part III. Computer Vision Analysis, Detection, Tracking and Recognition, • Part IV. Data-Intensive Text Processing, • Part V. Innovations in Web and Internet Technologies, and • Part VI. New Methods and Applications in Information and Software Engineering. The book is an excellent resource for researchers and those working in algorithmics, artificial and computational intelligence, collaborative systems, decisio...

An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images

Science.gov (United States)

Chin Neoh, Siew; Srisukkham, Worawut; Zhang, Li; Todryk, Stephen; Greystoke, Brigit; Peng Lim, Chee; Alamgir Hossain, Mohammed; Aslam, Nauman

2015-01-01

This research proposes an intelligent decision support system for acute lymphoblastic leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with stimulating discriminant measures (SDM) of both within- and between-cluster scatter variances is proposed to produce robust segmentation of nucleus and cytoplasm of lymphocytes/lymphoblasts. Specifically, the proposed between-cluster evaluation is formulated based on the trade-off of several between-cluster measures of well-known feature extraction methods. The SDM measures are used in conjuction with Genetic Algorithm for clustering nucleus, cytoplasm, and background regions. Subsequently, a total of eighty features consisting of shape, texture, and colour information of the nucleus and cytoplasm sub-images are extracted. A number of classifiers (multi-layer perceptron, Support Vector Machine (SVM) and Dempster-Shafer ensemble) are employed for lymphocyte/lymphoblast classification. Evaluated with the ALL-IDB2 database, the proposed SDM-based clustering overcomes the shortcomings of Fuzzy C-means which focuses purely on within-cluster scatter variance. It also outperforms Linear Discriminant Analysis and Fuzzy Compactness and Separation for nucleus-cytoplasm separation. The overall system achieves superior recognition rates of 96.72% and 96.67% accuracies using bootstrapping and 10-fold cross validation with Dempster-Shafer and SVM, respectively. The results also compare favourably with those reported in the literature, indicating the usefulness of the proposed SDM-based clustering method. PMID:26450665

Business intelligence and financial decision-making: a theoretical approach

Directory of Open Access Journals (Sweden)

Mary Julieth Murillo Junco

2013-01-01

Full Text Available This paper deals with a literature review about the origin, development and implementation of Business Intelligence focused directly to solving problems in the financial area of the different organizations. Wanted contextualize how it tools have been incorporated into the decision making processes of modern business. A feature of the way it makes decisions has to do with the rational use made of the information available, and it is in this field where information technology and communication play a role today

25th International Conference on Industrial, Engineering & Other Applica- tions of Applied Intelligent Systems (IEA/AIE 2012)

CERN Document Server

Jiang, He; Ali, Moonis; Li, Mingchu; Modern Advances in Intelligent Systems and Tools

2012-01-01

Intelligent systems provide a platform to connect the research in artificial intelligence to real-world problem solving applications. Various intelligent systems have been developed to face real-world applications. This book discusses the modern advances in intelligent systems and the tools in applied artificial intelligence. It consists of twenty-three chapters authored by participants of the 25th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2012) which was held in Dalian, China. This book is divided into six parts, including Applied Intelligence, Cognitive Computing and Affective Computing, Data Mining and Intelligent Systems, Decision Support Systems, Machine Learning, and Natural Language Processing. Each part includes three to five chapters. In these chapters, many approaches, applications, restrictions, and discussions are presented. The material of each chapter is self-contained and was reviewed by at least two anonymous referees t...

Artificial Intelligence and Moral intelligence

Directory of Open Access Journals (Sweden)

Laura Pana

2008-07-01

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

Intelligent system for accident identification in NPP; Sistema inteligente para la identificacion de accidentes en centrales nucleares

Energy Technology Data Exchange (ETDEWEB)

Hernandez, J L [Centro Nacional de Seguridad Nuclear, La Habana (Cuba)

1999-12-31

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

Hardware-in-the-Loop Simulation of Distributed Intelligent Energy Management System for Microgrids

Directory of Open Access Journals (Sweden)

Dong-Jun Won

2013-07-01

Full Text Available Microgrids are autonomous low-voltage power distribution systems that contain multiple distributed energy resources (DERs and smart loads that can provide power system operation flexibility. To effectively control and coordinate multiple DERs and loads of microgrids, this paper proposes a distributed intelligent management system that employs a multi-agent-based control system so that delicate decision-making functions can be distributed to local intelligent agents. This paper presents the development of a hardware-in-the-loop simulation (HILS system for distributed intelligent management system for microgrids and its promising application to an emergency demand response program. In the developed HILS system, intelligent agents are developed using microcontrollers and ZigBee wireless communication technology. Power system dynamic models are implemented in real-time simulation environments using the Opal-RT system. This paper presents key features of the data communication and management schemes based on multi-agent concepts. The performance of the developed system is tested for emergency demand response program applications.

Dynamic vulnerability assessment and intelligent control for sustainable power systems

CERN Document Server

Gonzalez-Longatt, Francisco

2018-01-01

Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability as essment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protect...

Intelligent Integrated Health Management for a System of Systems

Science.gov (United States)

Smith, Harvey; Schmalzel, John; Figueroa, Fernando

2008-01-01

An intelligent integrated health management system (IIHMS) incorporates major improvements over prior such systems. The particular IIHMS is implemented for any system defined as a hierarchical distributed network of intelligent elements (HDNIE), comprising primarily: (1) an architecture (Figure 1), (2) intelligent elements, (3) a conceptual framework and taxonomy (Figure 2), and (4) and ontology that defines standards and protocols. Some definitions of terms are prerequisite to a further brief description of this innovation: A system-of-systems (SoS) is an engineering system that comprises multiple subsystems (e.g., a system of multiple possibly interacting flow subsystems that include pumps, valves, tanks, ducts, sensors, and the like); 'Intelligent' is used here in the sense of artificial intelligence. An intelligent element may be physical or virtual, it is network enabled, and it is able to manage data, information, and knowledge (DIaK) focused on determining its condition in the context of the entire SoS; As used here, 'health' signifies the functionality and/or structural integrity of an engineering system, subsystem, or process (leading to determination of the health of components); 'Process' can signify either a physical process in the usual sense of the word or an element into which functionally related sensors are grouped; 'Element' can signify a component (e.g., an actuator, a valve), a process, a controller, an actuator, a subsystem, or a system; The term Integrated System Health Management (ISHM) is used to describe a capability that focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) not just data to control systems for safe and effective operation. A major novel aspect of the present development is the concept of intelligent integration. The purpose of intelligent integration, as defined and

Wind power systems. Applications of computational intelligence

Energy Technology Data Exchange (ETDEWEB)

Wang, Lingfeng [Toledo Univ., OH (United States). Dept. of Electrical Engineering and Computer Science; Singh, Chanan [Texas A and M Univ., College Station, TX (United States). Electrical and Computer Engineering Dept.; Kusiak, Andrew (eds.) [Iowa Univ., Iowa City, IA (United States). Mechanical and Industrial Engineering Dept.

2010-07-01

Renewable energy sources such as wind power have attracted much attention because they are environmentally friendly, do not produce carbon dioxide and other emissions, and can enhance a nation's energy security. For example, recently more significant amounts of wind power are being integrated into conventional power grids. Therefore, it is necessary to address various important and challenging issues related to wind power systems, which are significantly different from the traditional generation systems. This book is a resource for engineers, practitioners, and decision-makers interested in studying or using the power of computational intelligence based algorithms in handling various important problems in wind power systems at the levels of power generation, transmission, and distribution. Researchers have been developing biologically-inspired algorithms in a wide variety of complex large-scale engineering domains. Distinguished from the traditional analytical methods, the new methods usually accomplish the task through their computationally efficient mechanisms. Computational intelligence methods such as evolutionary computation, neural networks, and fuzzy systems have attracted much attention in electric power systems. Meanwhile, modern electric power systems are becoming more and more complex in order to meet the growing electricity market. In particular, the grid complexity is continuously enhanced by the integration of intermittent wind power as well as the current restructuring efforts in electricity industry. Quite often, the traditional analytical methods become less efficient or even unable to handle this increased complexity. As a result, it is natural to apply computational intelligence as a powerful tool to deal with various important and pressing problems in the current wind power systems. This book presents the state-of-the-art development in the field of computational intelligence applied to wind power systems by reviewing the most up

Intelligent Traffic Information System a Real-Time Traffic Information System on the Shiraz Bypass

Directory of Open Access Journals (Sweden)

Sodagaran Amir

2016-01-01

Full Text Available Real-time traffic information system is an Intelligent Transportation System (ITS that allows commuters to make their traveling plan better. In this regard, an intelligent and real-time traffic information system was developed based on the video detection and an image processing algorithm was applied to measure traffic-flow according to the average speed of vehicles. Then, traffic status of each pass way is broadcasted to the electronic boards installed on all decision making entrance / exit. Different levels of congestion related to the routes ahead are shown on the boards with different colors in order to assist commuters. This system was implemented on the Shiraz Dry River’s bypasses which account as vital routes to moderate traffic of city center. Experimental results are promising due to the proximity of determined traffic status by the system compared to the detection done by traffic experts. Average speed improvement is another result of using this system. This intelligent system developed and implemented in Shiraz city for the first time in Iran.s.

Reference system architecture for trade promotion management: leveraging business intelligence technologies and decision support systems

NARCIS (Netherlands)

Balmus, Andra Bianca; Iacob, Maria Eugenia; van Sinderen, Marten J.; van Busschbach, Murk

Working towards gaining competitive advantage and establishing stable relationships with their supply chain intermediaries, fast moving consumer goods companies are currently focusing their attention on intelligent, goal-based funds investment. Traditional trade promotion management systems (TPMS),

An intelligent multi-media human-computer dialogue system

Science.gov (United States)

Neal, J. G.; Bettinger, K. E.; Byoun, J. S.; Dobes, Z.; Thielman, C. Y.

1988-01-01

Sophisticated computer systems are being developed to assist in the human decision-making process for very complex tasks performed under stressful conditions. The human-computer interface is a critical factor in these systems. The human-computer interface should be simple and natural to use, require a minimal learning period, assist the user in accomplishing his task(s) with a minimum of distraction, present output in a form that best conveys information to the user, and reduce cognitive load for the user. In pursuit of this ideal, the Intelligent Multi-Media Interfaces project is devoted to the development of interface technology that integrates speech, natural language text, graphics, and pointing gestures for human-computer dialogues. The objective of the project is to develop interface technology that uses the media/modalities intelligently in a flexible, context-sensitive, and highly integrated manner modelled after the manner in which humans converse in simultaneous coordinated multiple modalities. As part of the project, a knowledge-based interface system, called CUBRICON (CUBRC Intelligent CONversationalist) is being developed as a research prototype. The application domain being used to drive the research is that of military tactical air control.

Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

International Nuclear Information System (INIS)

Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M

2017-01-01

Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)

Intelligent Learning System using cognitive science theory and artificial intelligence methods

Energy Technology Data Exchange (ETDEWEB)

Cristensen, D.L.

1986-01-01

This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic is used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.

Decision Support for Software Process Management Teams: An Intelligent Software Agent Approach

National Research Council Canada - National Science Library

Church, Lori

2000-01-01

... to market, eliminate redundancy, and ease job stress. This thesis proposes a conceptual model for software process management decision support in the form of an intelligent software agent network...

[Artificial intelligence] AI for protection systems

Energy Technology Data Exchange (ETDEWEB)

Aggarwal, R.; Johns, A.

1997-12-31

The reliable operation of large power systems with small stability margins is highly dependent on control systems and protection devices. Progress in the field of microprocessor systems and demanding requirements in respect of the performance of protective relays are the reasons for digital device applications to power system protection. The superiority of numeric protection over its analogue alternatives is attributed to such factors as accurate extraction of the fundamental voltage and current components through filtering, functional benefits resulting from multi-processor design and extensive self-monitoring, etc. However, all these reasons have not led to a major impact on speed, sensitivity and selectivity of primary protective relays, and the gains are only marginal; this is so because conventional digital relays still rely on deterministic signal models and a heuristic approach for decision making, so that only a fraction of the information contained within voltage and current signals as well as knowledge about the plant to be protected is used. The performance of digital relays may be substantially improved if the decision making is based on elements of artificial intelligence (AI). (Author)

Reinforcement and Systemic Machine Learning for Decision Making

CERN Document Server

Kulkarni, Parag

2012-01-01

Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available-or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm-creating new learning applications and, ultimately, more intelligent machines. The first book of its kind in this new an

Group decision support system for customer-driven product design

Science.gov (United States)

Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada

2000-10-01

This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.

Combination of artificial intelligence and procedural language programs in a computer application system supporting nuclear reactor operations

International Nuclear Information System (INIS)

Town, G.G.; Stratton, R.C.

1985-01-01

A computer application system is described which provides nuclear reactor power plant operators with an improved decision support system. This system combines traditional computer applications such as graphics display with artificial intelligence methodologies such as reasoning and diagnosis so as to improve plant operability. This paper discusses the issues, and a solution, involved with the system integration of applications developed using traditional and artificial intelligence languages

Combination of artificial intelligence and procedural language programs in a computer application system supporting nuclear reactor operations

International Nuclear Information System (INIS)

Stratton, R.C.; Town, G.G.

1985-01-01

A computer application system is described which provides nuclear reactor power plant operators with an improved decision support system. This system combines traditional computer applications such as graphics display with artifical intelligence methodologies such as reasoning and diagnosis so as to improve plant operability. This paper discusses the issues, and a solution, involved with the system integration of applications developed using traditional and artificial intelligence languages

Is It Possible To Use Intelligent Systems To Design A Profitable Foreign Exchange Trading Agent?

OpenAIRE

Julian, Pomfret-Pudelsky

2009-01-01

In this paper, a trading agent is developed using a basket of intelligent systems with the goal of trading the GBPUSD currency pair profitably in the Foreign Exchange market. The basket of intelligent system consists of two regression models: a radial basis neural network and a TSK-fuzzy inference system; and three classification models: k-nearest neighbour, support vector machine and a decision tree. The trading strategy combines the predictions of each model using a Kalman-type filter to...

Challenges facing the distribution of an artificial-intelligence-based system for nursing.

Science.gov (United States)

Evans, S

1985-04-01

The marketing and successful distribution of artificial-intelligence-based decision-support systems for nursing face special barriers and challenges. Issues that must be confronted arise particularly from the present culture of the nursing profession as well as the typical organizational structures in which nurses predominantly work. Generalizations in the literature based on the limited experience of physician-oriented artificial intelligence applications (predominantly in diagnosis and pharmacologic treatment) must be modified for applicability to other health professions.

Intelligent environmental data warehouse

International Nuclear Information System (INIS)

Ekechukwu, B.

1998-01-01

Making quick and effective decisions in environment management are based on multiple and complex parameters, a data warehouse is a powerful tool for the over all management of massive environmental information. Selecting the right data from a warehouse is an important factor consideration for end-users. This paper proposed an intelligent environmental data warehouse system. It consists of data warehouse to feed an environmental researchers and managers with desire environmental information needs to their research studies and decision in form of geometric and attribute data for study area, and a metadata for the other sources of environmental information. In addition, the proposed intelligent search engine works according to a set of rule, which enables the system to be aware of the environmental data wanted by the end-user. The system development process passes through four stages. These are data preparation, warehouse development, intelligent engine development and internet platform system development. (author)

Adaptive intelligent power systems: Active distribution networks

International Nuclear Information System (INIS)

McDonald, Jim

2008-01-01

Electricity networks are extensive and well established. They form a key part of the infrastructure that supports industrialised society. These networks are moving from a period of stability to a time of potentially major transition, driven by a need for old equipment to be replaced, by government policy commitments to cleaner and renewable sources of electricity generation, and by change in the power industry. This paper looks at moves towards active distribution networks. The novel transmission and distribution systems of the future will challenge today's system designs. They will cope with variable voltages and frequencies, and will offer more flexible, sustainable options. Intelligent power networks will need innovation in several key areas of information technology. Active control of flexible, large-scale electrical power systems is required. Protection and control systems will have to react to faults and unusual transient behaviour and ensure recovery after such events. Real-time network simulation and performance analysis will be needed to provide decision support for system operators, and the inputs to energy and distribution management systems. Advanced sensors and measurement will be used to achieve higher degrees of network automation and better system control, while pervasive communications will allow networks to be reconfigured by intelligent systems

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

Science.gov (United States)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

Knowledge structure representation and automated updates in intelligent information management systems

Science.gov (United States)

Corey, Stephen; Carnahan, Richard S., Jr.

1990-01-01

A continuing effort to apply rapid prototyping and Artificial Intelligence techniques to problems associated with projected Space Station-era information management systems is examined. In particular, timely updating of the various databases and knowledge structures within the proposed intelligent information management system (IIMS) is critical to support decision making processes. Because of the significantly large amounts of data entering the IIMS on a daily basis, information updates will need to be automatically performed with some systems requiring that data be incorporated and made available to users within a few hours. Meeting these demands depends first, on the design and implementation of information structures that are easily modified and expanded, and second, on the incorporation of intelligent automated update techniques that will allow meaningful information relationships to be established. Potential techniques are studied for developing such an automated update capability and IIMS update requirements are examined in light of results obtained from the IIMS prototyping effort.

Towards an Understanding of the Role of Business Intelligence Systems in Organisational Knowing

DEFF Research Database (Denmark)

Shollo, Arisa; Galliers, Robert D.

2016-01-01

Recent advances in information technology (IT), such as the advent of business intelligence (BI) systems, have increased the ability of organisations to collect and analyse data to support decisions. There is little focus to date, however, on how BI systems might play a role in organisational...

Intelligent color recognition system using micro-controller

International Nuclear Information System (INIS)

Mohd Ashhar Khalid; Khairiah Yazid; Nur Aira Abd Rahman; Azaman Ahmad

2006-01-01

Color is widely used in categorizing the quality of products as well as a marker for automatic selection and discrimination of products. Most of color recognizing process is done manually and due to the fact that human perceived color differently, different of opinion frequently occur. This paper deals with the development of an intelligent color recognition system used for discriminating the ripeness of oil palm fruits into three categories namely ripe, under-ripe and un-ripe. In deciding the categories of fruit a sample belong, a technique of decision making similar to human thinking called neural network has been implemented. Implementation of neural network using a micro-controller is not so common, due to a limited capability in floating point calculation. To overcome the problem, a floating-point co-processor specially designed for micro-controller is used. The paper will report the system design and the network training and implementation methods. The effectiveness of the system compared to human decision method is also reported. (Author)

Fire auto alarm system intelligent trend

International Nuclear Information System (INIS)

Du Chengbao

1997-01-01

The author gives the course and trend of the fire alarm system going to more computerized and more intelligent. It is described that only the system applied artificial intelligent and confusion control is the true intelligent fire alarm system. The author gives the detailed analysis on the signal treatment of artificial intelligent applied to analogue fire alarm system as well as the alarm system controlled by confusion technology and artificial nervous net

Management Intelligent Systems : 2nd International Symposium

CERN Document Server

Martínez-López, Francisco; Vicari, Rosa; Prieta, Fernando

2013-01-01

This symposium was born as a research forum to present and discuss original, rigorous and significant contributions on Artificial Intelligence-based (AI) solutions—with a strong, practical logic and, preferably, with empirical applications—developed to aid the management of organizations in multiple areas, activities, processes and problem-solving; what we call Management Intelligent Systems (MiS).   This volume presents the proceedings of these activities in a collection of contributions with many original approaches. They address diverse Management and Business areas of application such as decision support, segmentation of markets, CRM, product design, service personalization, organizational design, e-commerce, credit scoring, workplace integration, innovation management, business database analysis, workflow management, location of stores, etc. A wide variety of AI techniques have been applied to these areas such as multi-objective optimization and evolutionary algorithms, classification algorithms, an...

A deep knowledge architecture for intelligent support of nuclear waste transportation decisions

International Nuclear Information System (INIS)

Batra, D.; Bowen, W.M.; Hill, T.R.; Weeks, K.D.

1988-01-01

The concept of intelligent decision support has been discussed and explored in several recent papers, one of which has suggested the use of a Deep Knowledge Architecture. This paper explores this concept through application to a specific decision environment. The complex problems involved in nuclear waste disposal decisions provide an excellent test case. The resulting architecture uses an integrated, multi-level model base to represent the deep knowledge of the problem. Combined with the surface level knowledge represented by the database, the proposed knowledge base complements that of the decision-maker, allowing analysis at a range of levels of decisions which may also occur at a range of levels

Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan.

Science.gov (United States)

Liao, Pei-Hung; Hsu, Pei-Ti; Chu, William; Chu, Woei-Chyn

2015-06-01

This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics. © The Author(s) 2013.

Intelligent Hypothermia Care System using Ant ‎Colony Optimization for Rules Prediction

Directory of Open Access Journals (Sweden)

Hayder Naser Khraibet

2017-12-01

Full Text Available Intelligent Hypothermia Care System (IHCS is an intelligence system uses set of methodologies, algorithms, architectures and processes to determine where patients in a postoperative recovery area must be sent. Hypothermia is a significant concern after surgery. This paper utilizes the classification task in data mining to propose an intelligent technique to predict where to send a patient after surgery: intensive care unit, general floor or home. To achieve this goal, this paper evaluates the performance of decision tree algorithm, exemplifying the deterministic approach, against the AntMiner algorithm, exemplifying the heuristic approach, to choose the best approach in detecting the patient’s status. Results show the outperformance of the heuristic approach. The implication of this proposal will be twofold: in hypothermia treatment and in the application of ant colony optimization

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...

Composable Analytic Systems for next-generation intelligence analysis

Science.gov (United States)

DiBona, Phil; Llinas, James; Barry, Kevin

2015-05-01

Lockheed Martin Advanced Technology Laboratories (LM ATL) is collaborating with Professor James Llinas, Ph.D., of the Center for Multisource Information Fusion at the University at Buffalo (State of NY), researching concepts for a mixed-initiative associate system for intelligence analysts to facilitate reduced analysis and decision times while proactively discovering and presenting relevant information based on the analyst's needs, current tasks and cognitive state. Today's exploitation and analysis systems have largely been designed for a specific sensor, data type, and operational context, leading to difficulty in directly supporting the analyst's evolving tasking and work product development preferences across complex Operational Environments. Our interactions with analysts illuminate the need to impact the information fusion, exploitation, and analysis capabilities in a variety of ways, including understanding data options, algorithm composition, hypothesis validation, and work product development. Composable Analytic Systems, an analyst-driven system that increases flexibility and capability to effectively utilize Multi-INT fusion and analytics tailored to the analyst's mission needs, holds promise to addresses the current and future intelligence analysis needs, as US forces engage threats in contested and denied environments.

DEVELOPMENT OF THE INTELLECTUAL AGENT-ORIENTED SYSTEM FOR DECISION SUPPORT AT ENTERPRISE

Directory of Open Access Journals (Sweden)

G. Chornous

2014-06-01

Full Text Available Actual status of management confirms usefulness and necessity for development of scientific modeling tools for decision-making processes based on distributed artificial intelligence. The paper presents opportunities of the agent – oriented approach to support operative and strategic management decisions at the pharmaceutical enterprise. It is argued that the combination of intelligent agents technology and Data Mining (DM produces a powerful synergistic effect. The basis of the intellectual agent – oriented DSS (AODSS is proposed to put a hybrid approach to the use of DM. Hybrid intelligent AODSS is represented numerous network of small agents, it provides concurrent operation execution, solutions distribution, knowledge management. Agents can be divided into groups: data agents, monitoring agents, agents for solutions search, modeling agents, impact agents and presentations agents. The result of research is development of AODSS created as a multi-level system wherein the project, process and environment levels are intercommunicated. The combination of intelligent technologies in AODSS allows involve rules, cases, a wide range of DM methods and models. The paper proposes a variant of AODSS implementation within the real enterprise IT-infrastructure based on SAP NetWeaver. The analysis results of the semi-commercial operation of the system assures that it can improve managerial decisions inasmuch as accuracy, consistency, flexibility, speed together form the basis of actual efficient solutions.

Handbook on Decision Making

CERN Document Server

Jain, Lakhmi C

2010-01-01

The present "Volume 1: Techniques and Applications" of the "Handbook on Decision Making" presents a useful collection of AI techniques, as well as other complementary methodologies, that are useful for the design and development of intelligent decision support systems. Application examples of how these intelligent decision support systems can be utilized to help tackle a variety of real-world problems in different domains, such as business, management, manufacturing, transportation and food industries, and biomedicine, are presented. The handbook includes twenty condensed c

A Framework for Knowledge Management and Automated Reasoning Applied on Intelligent Transport Systems

OpenAIRE

Feljan, Aneta Vulgarakis; Karapantelakis, Athanasios; Mokrushin, Leonid; Liang, Hongxin; Inam, Rafia; Fersman, Elena; Azevedo, Carlos R. B.; Raizer, Klaus; Souza, Ricardo S.

2017-01-01

Cyber-Physical Systems in general, and Intelligent Transport Systems (ITS) in particular use heterogeneous data sources combined with problem solving expertise in order to make critical decisions that may lead to some form of actions e.g., driver notifications, change of traffic light signals and braking to prevent an accident. Currently, a major part of the decision process is done by human domain experts, which is time-consuming, tedious and error-prone. Additionally, due to the intrinsic n...

New trends in computational collective intelligence

CERN Document Server

Kim, Sang-Wook; Trawiński, Bogdan

2015-01-01

This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

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.

Research of Classical and Intelligent Information System Solutions for Criminal Intelligence Analysis

OpenAIRE

Šimović, Vladimir

2001-01-01

The objective of this study is to present research on classical and intelligent information system solutions used in criminal intelligence analysis in Croatian security system theory. The study analyses objective and classical methods of information science, including artificial intelligence and other scientific methods. The intelligence and classical software solutions researched, proposed, and presented in this study were used in developing the integrated information system for the Croatian...

Motorcycle Start-stop System based on Intelligent Biometric Voice Recognition

Science.gov (United States)

Winda, A.; E Byan, W. R.; Sofyan; Armansyah; Zariantin, D. L.; Josep, B. G.

2017-03-01

Current mechanical key in the motorcycle is prone to bulgary, being stolen or misplaced. Intelligent biometric voice recognition as means to replace this mechanism is proposed as an alternative. The proposed system will decide whether the voice is belong to the user or not and the word utter by the user is ‘On’ or ‘Off’. The decision voice will be sent to Arduino in order to start or stop the engine. The recorded voice is processed in order to get some features which later be used as input to the proposed system. The Mel-Frequency Ceptral Coefficient (MFCC) is adopted as a feature extraction technique. The extracted feature is the used as input to the SVM-based identifier. Experimental results confirm the effectiveness of the proposed intelligent voice recognition and word recognition system. It show that the proposed method produces a good training and testing accuracy, 99.31% and 99.43%, respectively. Moreover, the proposed system shows the performance of false rejection rate (FRR) and false acceptance rate (FAR) accuracy of 0.18% and 17.58%, respectively. In the intelligent word recognition shows that the training and testing accuracy are 100% and 96.3%, respectively.

System for intelligent teleoperation research

International Nuclear Information System (INIS)

Orlando, N.E.

1983-01-01

The Automation Technology Branch of NASA Langley Research Center is developing a research capability in the field of artificial intelligence, particularly as applicable in teleoperator/robotics development for remote space operations. As a testbed for experimentation in these areas, a system concept has been developed and is being implemented. This system, termed DAISIE (Distributed Artificially Intelligent System for Interacting with the Environment), interfaces the key processes of perception, reasoning, and manipulation by linking hardware sensors and manipulators to a modular artificial intelligence (AI) software system in a hierarchical control structure. Verification experiments have been performed: one experiment used a blocksworld database and planner embedded in the DAISIE system to intelligently manipulate a simple physical environment; the other experiment implemented a joint-space collision avoidance algorithm. Continued system development is planned

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...

How can we get intelligent systems close to experiments

International Nuclear Information System (INIS)

Bock, R.K.; Ermolin, Y.; Krischer, W.; Ljuslin, C.; Lone, S.; Marchioro, A.; Zografos, K.

1989-01-01

For the high data rates expected at future multi-TeV hadronic colliders like the SSC, it is of utmost importance to take decisions in real time on partial data and as fast as possible. At a first level and shortest timescale, some customized electronics will reduce the rates. In a second phase, decisions have to use concepts closer to physics and hence imply the presence of some intelligence in the trigger. This paper considers various parallel computer or computer-like systems for their possibilities to be embedded as critical active elements in future detectors. The authors discuss the present activities and the pilot systems being built up as part of the LAA project at CERN. These activities aim at a better understanding of existing commercial systems, their design, and their limits of performance

Intelligent manipulation technique for multi-branch robotic systems

Science.gov (United States)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

Intelligent control systems 1990

International Nuclear Information System (INIS)

Shoureshi, R.

1991-01-01

The field of artificial intelligence (Al) has generated many useful ideas and techniques that can be integrated into the design of control systems. It is believed and, for special cases, has been demonstrated, that integration of Al into control systems would provide the necessary tools for solving many of the complex problems that present control techniques and Al algorithms are unable to do, individually. However, this integration requires the development of basic understanding and new fundamentals to provide scientific bases for achievement of its potential. This book presents an overview of some of the latest research studies in the area of intelligent control systems. These papers present techniques for formulation of intelligent control, and development of the rule-based control systems. Papers present applications of control systems in nuclear power plants and HVAC systems

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...

Intelligent Integrated System Health Management

Science.gov (United States)

Figueroa, Fernando

2012-01-01

Intelligent Integrated System Health Management (ISHM) is the management of data, information, and knowledge (DIaK) with the purposeful objective of determining the health of a system (Management: storage, distribution, sharing, maintenance, processing, reasoning, and presentation). Presentation discusses: (1) ISHM Capability Development. (1a) ISHM Knowledge Model. (1b) Standards for ISHM Implementation. (1c) ISHM Domain Models (ISHM-DM's). (1d) Intelligent Sensors and Components. (2) ISHM in Systems Design, Engineering, and Integration. (3) Intelligent Control for ISHM-Enabled Systems

Artificial intelligence based decision support for trumpeter swan management

Science.gov (United States)

Sojda, Richard S.

2002-01-01

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

Benefits of collective intelligence: Swarm intelligent foraging, an ethnographic research

Directory of Open Access Journals (Sweden)

Sivave Mashingaidze

2014-12-01

Full Text Available Wisdom of crowds; bees, colonies of ants, schools of fish, flocks of birds, and fireflies flashing synchronously are all examples of highly coordinated behaviors that emerge from collective, decentralized intelligence. This article is an ethnographic study of swarm intelligence foraging of swarms and the benefits derived from collective decision making. The author used using secondary data analysis to look at the benefits of swarm intelligence in decision making to achieve intended goals. Concepts like combined decision making and consensus were discussed and four principles of swarm intelligence were also discussed viz; coordination, cooperation, deliberation and collaboration. The research found out that collective decision making in swarms is the touchstone of achieving their goals. The research further recommended corporate to adopt collective intelligence for business sustainability.

A Decision Support System for Optimum Use of Fertilizers

Energy Technology Data Exchange (ETDEWEB)

R. L. Hoskinson; J. R. Hess; R. K. Fink

1999-07-01

The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

Intelligent Distributed Computing VI : Proceedings of the 6th International Symposium on Intelligent Distributed Computing

CERN Document Server

Badica, Costin; Malgeri, Michele; Unland, Rainer

2013-01-01

This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trus...

Intelligent Systems For Aerospace Engineering: An Overview

Science.gov (United States)

KrishnaKumar, K.

2003-01-01

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

Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey

Directory of Open Access Journals (Sweden)

Lefeng Cheng

2018-04-01

Full Text Available Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA, including expert system (EPS, artificial neural network (ANN, fuzzy theory, rough sets theory (RST, grey system theory (GST, swarm intelligence (SI algorithms, data mining technology, machine learning (ML, and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as

Consultation system with knowledge representation by decision rules

Energy Technology Data Exchange (ETDEWEB)

Senne, E L.F.; Simoni, P O

1982-04-01

The use of decision rules in the representation of empirical knowledge supplied by application domain experts is discussed. Based on this representation, a system is described which employs artificial intelligence techniques to yield inferences within a specific domain. Three modules composing the system are described: the acquisition one, that allows the insertion of new rules; the diagnostic one, that uses rules in the inference process; and the explanation one, that exhibits reasons for each system action.

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

CERN Document Server

Li, Tianrui

2012-01-01

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

The use of emotional intelligence capabilities in clinical reasoning and decision-making: A qualitative, exploratory study.

Science.gov (United States)

Hutchinson, Marie; Hurley, John; Kozlowski, Desirée; Whitehair, Leeann

2018-02-01

To explore clinical nurses' experiences of using emotional intelligence capabilities during clinical reasoning and decision-making. There has been little research exploring whether, or how, nurses employ emotional intelligence (EI) in clinical reasoning and decision-making. Qualitative phase of a larger mixed-methods study. Semistructured qualitative interviews with a purposive sample of registered nurses (n = 12) following EI training and coaching. Constructivist thematic analysis was employed to analyse the narrative transcripts. Three themes emerged: the sensibility to engage EI capabilities in clinical contexts, motivation to actively engage with emotions in clinical decision-making and incorporating emotional and technical perspectives in decision-making. Continuing to separate cognition and emotion in research, theorising and scholarship on clinical reasoning is counterproductive. Understanding more about nurses' use of EI has the potential to improve the calibre of decisions, and the safety and quality of care delivered. © 2017 John Wiley & Sons Ltd.

Power System for Intelligent House

Directory of Open Access Journals (Sweden)

Michal Jahelka

2010-01-01

Full Text Available Power supply of intelligent houses or house phones is possible to do with standard transformer with voltage stabilizer or with intelligent power supply. Standard solution can has as a result of failure fuse blown or fire occurrence. Intelligent power supply switch off power and tests with little current whether short circuit is removed. After it resume system power supply. At the same time it cares of system backup with accumulator, informs control system about short circuit or failure net power supply, or can switch off all system power after command from control system.

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

Science.gov (United States)

Szatkowski, Gerard P.; Schultz, Roger

1988-01-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Enhanced situation awareness and decision making for an intelligent reconfigurable reactor power controller

International Nuclear Information System (INIS)

Kenney, S.J.; Edwards, R.M.

1996-01-01

A Learning Automata based intelligent reconfigurable controller has been adapted for use as a reactor power controller to achieve improved reactor temperature performance. The intelligent reconfigurable controller is capable of enforcing either a classical or an optimal reactor power controller based on control performance feedback. Four control performance evaluation measures: dynamically estimated average quadratic temperature error, power, rod reactivity and rod reactivity rate were developed to provide feedback to the control decision component of the intelligent reconfigurable controller. Fuzzy Logic and Neural Network controllers have been studied for inclusion in the bank of controllers that form the intermediate level of an enhanced intelligent reconfigurable reactor power controller (IRRPC). The increased number of alternatives available to the supervisory level of the IRRPC requires enhanced situation awareness. Additional performance measures have been designed and a method for synthesizing them into a single indication of the overall performance of the currently enforced reactor power controller has been conceptualized. Modification of the reward/penalty scheme implemented in the existing IRRPC to increase the quality of the supervisory level decision process has been studied. The logogen model of human memory (Morton, 1969) and individual controller design information could be used to allocate reward to the most appropriate controller. Methods for allocating supervisory level attention were also studied with the goal of maximizing learning rate

Intelligent Data Analysis in the EMERCOM Information System

Science.gov (United States)

Elena, Sharafutdinova; Tatiana, Avdeenko; Bakaev, Maxim

2017-01-01

The paper describes an information system development project for the Russian Ministry of Emergency Situations (MES, whose international operations body is known as EMERCOM), which was attended by the representatives of both the IT industry and the academia. Besides the general description of the system, we put forward OLAP and Data Mining-based approaches towards the intelligent analysis of the data accumulated in the database. In particular, some operational OLAP reports and an example of multi-dimensional information space based on OLAP Data Warehouse are presented. Finally, we outline Data Mining application to support decision-making regarding security inspections planning and results consideration.

Artificial intelligence in robot control systems

Science.gov (United States)

Korikov, A.

2018-05-01

This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

A Proposed Business Intelligent Framework for Recommender Systems

Directory of Open Access Journals (Sweden)

Sitalakshmi Venkatraman

2017-11-01

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

Intelligence analysis – the royal discipline of Competitive Intelligence

Directory of Open Access Journals (Sweden)

František Bartes

2011-01-01

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

Selected business intelligence methods for decision-making support in a finance institution

OpenAIRE

Mezera, Filip; Křupka, Jiří

2017-01-01

This article deals with decision-making support methods’ implementation in a medium size financial company with international operations. The objective of this article is to show the abilities of these methods to precise decision-making of management. At the beginning of this article there is briefly described the existing situation in this business sector in Central Europe. After that part Business Intelligence methods are described as well as the reasons while these methods have been introd...

A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

Science.gov (United States)

Wu, G. Gordon

1995-01-01

Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

The prediction of breast cancer biopsy outcomes using two CAD approaches that both emphasize an intelligible decision process

International Nuclear Information System (INIS)

Elter, M.; Schulz-Wendtland, R.; Wittenberg, T.

2007-01-01

Mammography is the most effective method for breast cancer screening available today. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. To reduce the high number of unnecessary breast biopsies, several computer-aided diagnosis (CAD) systems have been proposed in the last several years. These systems help physicians in their decision to perform a breast biopsy on a suspicious lesion seen in a mammogram or to perform a short term follow-up examination instead. We present two novel CAD approaches that both emphasize an intelligible decision process to predict breast biopsy outcomes from BI-RADS findings. An intelligible reasoning process is an important requirement for the acceptance of CAD systems by physicians. The first approach induces a global model based on decison-tree learning. The second approach is based on case-based reasoning and applies an entropic similarity measure. We have evaluated the performance of both CAD approaches on two large publicly available mammography reference databases using receiver operating characteristic (ROC) analysis, bootstrap sampling, and the ANOVA statistical significance test. Both approaches outperform the diagnosis decisions of the physicians. Hence, both systems have the potential to reduce the number of unnecessary breast biopsies in clinical practice. A comparison of the performance of the proposed decision tree and CBR approaches with a state of the art approach based on artificial neural networks (ANN) shows that the CBR approach performs slightly better than the ANN approach, which in turn results in slightly better performance than the decision-tree approach. The differences are statistically significant (p value <0.001). On 2100 masses extracted from the DDSM database, the CRB approach for example resulted in an area under the ROC curve of A(z)=0.89±0.01, the decision-tree approach in A(z)=0.87±0

Novel applications of intelligent systems

CERN Document Server

Kasabov, Nikola; Filev, Dimitar; Jotsov, Vladimir

2016-01-01

In this carefully edited book some selected results of theoretical and applied research in the field of broadly perceived intelligent systems are presented. The problems vary from industrial to web and problem independent applications. All this is united under the slogan: "Intelligent systems conquer the world”. The book brings together innovation projects with analytical research, invention, retrieval and processing of knowledge and logical applications in technology. This book is aiming to a wide circle of readers and particularly to the young generation of IT/ICT experts who will build the next generations of intelligent systems.

Trends in ambient intelligent systems the role of computational intelligence

CERN Document Server

Khan, Mohammad; Abraham, Ajith

2016-01-01

This book demonstrates the success of Ambient Intelligence in providing possible solutions for the daily needs of humans. The book addresses implications of ambient intelligence in areas of domestic living, elderly care, robotics, communication, philosophy and others. The objective of this edited volume is to show that Ambient Intelligence is a boon to humanity with conceptual, philosophical, methodical and applicative understanding. The book also aims to schematically demonstrate developments in the direction of augmented sensors, embedded systems and behavioral intelligence towards Ambient Intelligent Networks or Smart Living Technology. It contains chapters in the field of Ambient Intelligent Networks, which received highly positive feedback during the review process. The book contains research work, with in-depth state of the art from augmented sensors, embedded technology and artificial intelligence along with cutting-edge research and development of technologies and applications of Ambient Intelligent N...

ENGINEERING OF UNIVERSITY INTELLIGENT LEARNING SYSTEMS

Directory of Open Access Journals (Sweden)

Vasiliy M. Trembach

2016-01-01

Full Text Available In the article issues of engineering intelligent tutoring systems of University with adaptation are considered. The article also dwells on some modern approaches to engineering of information systems. It shows the role of engineering e-learning devices (systems in system engineering. The article describes the basic principles of system engineering and these principles are expanded regarding to intelligent information systems. The structure of intelligent learning systems with adaptation of the individual learning environments based on services is represented in the article.

A Decision Support System for Optimum Use of Fertilizers

Energy Technology Data Exchange (ETDEWEB)

Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

1999-07-01

The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

Stupid Tutoring Systems, Intelligent Humans

Science.gov (United States)

Baker, Ryan S.

2016-01-01

The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…

Intelligent technology for construction of tutoring integrated expert systems: new aspects

Directory of Open Access Journals (Sweden)

Galina V. Rybina

2017-01-01

Full Text Available The main aim of this paper is to acquaint readers of the journal “Open Education” with the accumulated experience of construction and practical use in the educational process of Cybernetics Department of the National Research Nuclear University MEPhI of a special class of intelligent tutoring systems, based on the architectures of tutoring integrated expert systems. The development is carried out on the problem-oriented methodology basis and intelligent software environment of AT-TECHNOLOGY workbench. They provide automation of support of all the stages of construction and maintenance of the life cycle of such systems.In the context of basic models, methods, algorithms and tools that implement the conceptual foundations of a problem-oriented methodology, and which are evolutionarily developed and experimentally investigated in the process of constructing various architectures of training integrated expert systems, including webbased ones, some features of the generalized model of intellectual learning and its components are considered (in particular, the competence-based model of the trainee, the adaptive tutoring model, the ontology model of the course /discipline et al. as well as methods and means of their realization in the current versions of tutoring integrated expert systems.In current versions of tutoring integrated expert systems examples of implementation of typical intelligent tutoring problems are described for the generalized ontology “Intelligent systems and technologies” (individual planning of the method of studying the training course, intelligent analysis of training tasks, intelligent support for decision making.A brief description of the conceptual foundations of the model of the intelligent software environment of the AT-TECHNOLOGY workbench is given and a description of some components of the model is presented with a focus on the basic components – intelligent planner, standard design procedures and reusable

Supporting the personnel reliability decision-making process with artificial intelligence

International Nuclear Information System (INIS)

Harte, D.C.

1991-01-01

Recent legislation concerning personnel security has vastly increased the responsibility and accountability of the security manager. Access authorization, fitness for duty, and personnel security access programs require decisions regarding an individual's trustworthiness and reliability based on the findings of a background investigation. While these guidelines provide significant data and are useful as a tool, limited resources are available to the adjudicator of derogatory information on what is and is not acceptable in terms of granting access to sensitive areas of nuclear plants. The reason why one individual is deemed unacceptable and the next acceptable may be questioned and cause discriminatory accusations. This paper is continuation of discussion on workforce reliability, focusing on the use of artificial intelligence to support the decisions of a security manager. With this support, the benefit of previous decisions helps ensure consistent adjudication of background investigations

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...

Decision Fusion System for Bolted Joint Monitoring

Directory of Open Access Journals (Sweden)

Dong Liang

2015-01-01

Full Text Available Bolted joint is widely used in mechanical and architectural structures, such as machine tools, industrial robots, transport machines, power plants, aviation stiffened plate, bridges, and steel towers. The bolt loosening induced by flight load and environment factor can cause joint failure leading to a disastrous accident. Hence, structural health monitoring is critical for the bolted joint detection. In order to realize a real-time and convenient monitoring and satisfy the requirement of advanced maintenance of the structure, this paper proposes an intelligent bolted joint failure monitoring approach using a developed decision fusion system integrated with Lamb wave propagation based actuator-sensor monitoring method. Firstly, the basic knowledge of decision fusion and classifier selection techniques is briefly introduced. Then, a developed decision fusion system is presented. Finally, three fusion algorithms, which consist of majority voting, Bayesian belief, and multiagent method, are adopted for comparison in a real-world monitoring experiment for the large aviation aluminum plate. Based on the results shown in the experiment, a big potential in real-time application is presented that the method can accurately and rapidly identify the bolt loosening by analyzing the acquired strain signal using proposed decision fusion system.

Emotional Intelligence and School Leadership

Science.gov (United States)

Gray, David

2009-01-01

Emotional intelligence is the cornerstone of every decision a principal makes; solving problems and making judgments are part of a leader's system of values and beliefs. Mayer and Salovney (1997) described emotionally intelligent leaders as those who are able to perceive and understand emotions and to regulate emotions to foster emotional and…

Artificial intelligence - New tools for aerospace project managers

Science.gov (United States)

Moja, D. C.

1985-01-01

Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

OpenAIRE

Bo Sun; Qiang Feng; Songjie Li

2012-01-01

According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

An engineering approach to modelling, decision support and control for sustainable systems.

Science.gov (United States)

Day, W; Audsley, E; Frost, A R

2008-02-12

Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems.

Trait Emotional Intelligence Is Related to Risk Taking when Adolescents Make Deliberative Decisions

Directory of Open Access Journals (Sweden)

Angelo Panno

2016-08-01

Full Text Available Most forms of risky behavior reach their peak during adolescence. A prominent line of research is exploring the relationship between people’s emotional self-efficacy and risk taking, but little is known about this relationship in the cognitive-deliberative domain among adolescents. The main aim of the present study consists in investigating whether trait EI (Emotional Intelligence is positively related to risk taking under predominantly cognitive-deliberative conditions among adolescents. Ninety-four adolescents played the cold version of the Columbia Card Task one month following an assessment of their trait EI. Results showed that trait EI is associated with risk taking under cognitive-deliberative conditions among adolescents. Moreover, the present research showed that trait EI is related to risk taking through the decision makers’ self-motivation. These results provide novel insights into research investigating the connections between emotional intelligence, decision science and adolescence research.

Business intelligence appliances in nuclear plant information system

International Nuclear Information System (INIS)

Bai Zhe; Zou Yuanhao

2012-01-01

With the widely use of information system, the enterprise has accumulated large amount of business data. It is urgent and complicated task to manipulate the massive and complex data collation, dig out the useful knowledge which can assist business managers and technical staff with decision-making and error analysis. At present, the business intelligence is in its initial stage in nuclear power plants (NPP), most of the plants start to show and analyze the data at the end-user interface, then go further with Data Mining gradually. By the basis of Data Warehouse. Online Analytical Processing and Data Mining technology, the data can be extracted, transformed and loaded. After the processing, the data is converted into useful information for plant managers to have different perspectives of decision-making and technical staff to analyse errors. (authors)

The Role of Personality Traits, Core Self-Evaluation, and Emotional Intelligence in Career Decision-Making Difficulties

Science.gov (United States)

Di Fabio, Annamaria; Palazzeschi, Letizia; Bar-On, Reuven

2012-01-01

This study examines the role of personality traits, core self-evaluation, and emotional intelligence (EI) in career decision-making difficulties. Italian university students (N = 232) responded to questions on the Big Five Questionnaire, Core Self-Evaluation Scale, Bar-On Emotional Quotient Inventory, and Career Decision-Making Difficulties…

Considerations on Accounting Intelligent Systems Importance

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available Managers begin to realize the importance of artificial intelligence technologies for their organizations. Knowledge is today seen as the main organizational resource and that is what intelligent systems are about: manipulating knowledge. In this paper we highlight the main reasons that an accountant can bring to his managers to emphasize this idea: intelligent systems are really needful in modern accounting.

Reasoning methods in medical consultation systems: artificial intelligence approaches.

Science.gov (United States)

Shortliffe, E H

1984-01-01

It has been argued that the problem of medical diagnosis is fundamentally ill-structured, particularly during the early stages when the number of possible explanations for presenting complaints can be immense. This paper discusses the process of clinical hypothesis evocation, contrasts it with the structured decision making approaches used in traditional computer-based diagnostic systems, and briefly surveys the more open-ended reasoning methods that have been used in medical artificial intelligence (AI) programs. The additional complexity introduced when an advice system is designed to suggest management instead of (or in addition to) diagnosis is also emphasized. Example systems are discussed to illustrate the key concepts.

Artificial intelligence in power system optimization

CERN Document Server

Ongsakul, Weerakorn

2013-01-01

With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

Cognitive logical systems with artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Liss, E

1983-09-01

The simulation of cognitive processes for the purpose of the technical development of learning systems with intelligent behavior is a basic object of the young interdisciplinary cognition science which is based upon artificial intelligence, cognitive psychology, computer science, linguistics and pedagogics. Cognitive systems may be described as knowledge-based logical systems. Based on structural and functional principles of intelligent automata and elementary information processing systems with structural learning capability the future process, machine and robot controls, advising units and fifth generation computers may be developed.

A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

Science.gov (United States)

Becker, Lee A.

1987-01-01

Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

Intelligent Freigth Transport Systems

DEFF Research Database (Denmark)

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

2009-01-01

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......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...

The role of soft computing in intelligent machines.

Science.gov (United States)

de Silva, Clarence W

2003-08-15

An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.

Some Steps towards Intelligent Computer Tutoring Systems.

Science.gov (United States)

Tchogovadze, Gotcha G.

1986-01-01

Describes one way of structuring an intelligent tutoring system (ITS) in light of developments in artificial intelligence. A specialized intelligent operating system (SIOS) is proposed for software for a network of microcomputers, and it is postulated that a general learning system must be used as a basic framework for the SIOS. (Author/LRW)

Software for Intelligent System Health Management

Science.gov (United States)

Trevino, Luis C.

2004-01-01

This viewgraph presentation describes the characteristics and advantages of autonomy and artificial intelligence in systems health monitoring. The presentation lists technologies relevant to Intelligent System Health Management (ISHM), and some potential applications.

Self-Adaptive Systems for Machine Intelligence

CERN Document Server

He, Haibo

2011-01-01

This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide application

Exploring the moderating effect of social intelligence on the relationship between entrepreneurial decision-making strategy and SME sustainable performance

Directory of Open Access Journals (Sweden)

Muhd Yusuf Dayang Hasliza

2018-01-01

Full Text Available The study reveals that causation, rather than effectuation, decision-making strategy is a more significant predictor of sustainable performance of SMEs. However, social intelligence was not found to be a significant moderator of entrepreneurial decision-making-sustainable performance relationship. The study uses data from a survey among 91 technology-based SMEs (TBS in Malaysia and employs structural equation modelling techniques for data analysis. A new instrument to measure all three variables of entrepreneurial decision-making strategy, social intelligence, and venture performance is proposed based on adoption and adaptation of existing validated scales available in literature.

Design and implementation of the standards-based personal intelligent self-management system (PICS).

Science.gov (United States)

von Bargen, Tobias; Gietzelt, Matthias; Britten, Matthias; Song, Bianying; Wolf, Klaus-Hendrik; Kohlmann, Martin; Marschollek, Michael; Haux, Reinhold

2013-01-01

Against the background of demographic change and a diminishing care workforce there is a growing need for personalized decision support. The aim of this paper is to describe the design and implementation of the standards-based personal intelligent care systems (PICS). PICS makes consistent use of internationally accepted standards such as the Health Level 7 (HL7) Arden syntax for the representation of the decision logic, HL7 Clinical Document Architecture for information representation and is based on a open-source service-oriented architecture framework and a business process management system. Its functionality is exemplified for the application scenario of a patient suffering from congestive heart failure. Several vital signs sensors provide data for the decision support system, and a number of flexible communication channels are available for interaction with patient or caregiver. PICS is a standards-based, open and flexible system enabling personalized decision support. Further development will include the implementation of components on small computers and sensor nodes.

Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

Energy Technology Data Exchange (ETDEWEB)

Jha, Sumit Kumar [University of Central Florida, Orlando; Pullum, Laura L [ORNL; Ramanathan, Arvind [ORNL

2016-01-01

Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

Intelligent systems engineering methodology

Science.gov (United States)

Fouse, Scott

1990-01-01

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

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems

Directory of Open Access Journals (Sweden)

Sang-Il Oh

2017-01-01

Full Text Available To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN. The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226 × 370 image, whereas the original selective search method extracted approximately 10 6 × n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset.

Business Intelligence Systems Accounting Integration in Romania. a Comparative Analysis

Directory of Open Access Journals (Sweden)

Daniela Postolache (Males

2010-12-01

Full Text Available Business Intelligence (BI systems have penetrated the Romanian market, providing a real decision support by integrating and synthesizing a large variety of information available in real time, anywhere in the world, including through mobile terminals. This study examines the BI solutions promoted in Romania through Internet sites written in Romanian, in terms of how the accounting information integration is done. Our paper highlights the most used economic and financial indicators and most often selected tools by BI systems developers to assist decisions. The writing bring forward the lack of transparency of the analyzed sites towards of configuration details of economic instruments, which we consider likely to delay the managers from Romania in order to become familiar with BI solutions, and it represent a weakness of this products promotion.

The need for operating guidelines and a decision making framework applicable to the discovery of non-intelligent extraterrestrial life

Science.gov (United States)

Race, Margaret S.; Randolph, Richard O.

While formal principles have been adopted for the eventuality of detecting intelligent life in our galaxy (SETI Principles), no such guidelines exist for the discovery of non-intelligent extraterrestrial life within the solar system. Current scientifically based planetary protection policies for solar system exploration address how to undertake exploration, but do not provide clear guidance on what to do if and when life is detected. Considering that martian life could be detected under several different robotic and human exploration scenarios in the coming decades, it is appropriate to anticipate how detection of non-intelligent, microbial life could impact future exploration missions and activities, especially on Mars. This paper discusses a proposed set of interim guidelines based loosely on the SETI Principles and addresses issues extending from the time of discovery through future handling and treatment of extraterrestrial life on Mars or elsewhere. Based on an analysis of both scientific and ethical considerations, there is a clear need for developing operating protocols applicable at the time of discovery and a decision making framework that anticipates future missions and activities, both robotic and human. There is growing scientific confidence that the discovery of extraterrestrial life in some form is nearly inevitable. If and when life is discovered beyond Earth, non-scientific dimensions may strongly influence decisions about the nature and scope of future missions and activities. It is appropriate to encourage international discussion and consideration of the issues prior to an event of such historical significance.

Improving societal acceptance of rad waste management policy decisions: an approach based on complex intelligence

International Nuclear Information System (INIS)

Rao, Suman

2008-01-01

In today's context elaborate public participation exercises are conducted around the world to elicit and incorporate societal risk perceptions into nuclear policy Decision-Making. However, on many occasions, such as in the case of rad waste management, the society remains unconvinced about these decisions. This naturally leads to the questions: are techniques for incorporating societal risk perceptions into the rad waste policy decision making processes sufficiently mature? How could societal risk perceptions and legal normative principles be better integrated in order to render the decisions more equitable and convincing to society? Based on guidance from socio-psychological research this paper postulates that a critical factor for gaining/improving societal acceptance is the quality and adequacy of criteria for option evaluation that are used in the policy decision making. After surveying three rad waste public participation cases, the paper identifies key lacunae in criteria abstraction processes as currently practiced. A new policy decision support model CIRDA: Complex Intelligent Risk Discourse Abstraction model that is based on the heuristic of Risk-Risk Analysis is proposed to overcome these lacunae. CIRDA's functionality of rad waste policy decision making is modelled as a policy decision-making Abstract Intelligent Agent and the agent program/abstraction mappings are presented. CIRDA is then applied to a live (U.K.) rad waste management case and the advantages of this method as compared to the Value Tree Method as practiced in the GB case are demonstrated. (author)

Modeling the prediction of business intelligence system effectiveness.

Science.gov (United States)

Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

2016-01-01

Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

Operational and real-time Business Intelligence

Directory of Open Access Journals (Sweden)

Daniela Ioana SANDU

2008-01-01

Full Text Available A key component of a company’s IT framework is a business intelligence (BI system. BI enables business users to report on, analyze and optimize business operations to reduce costs and increase revenues. Organizations use BI for strategic and tactical decision making where the decision-making cycle may span a time period of several weeks (e.g., campaign management or months (e.g., improving customer satisfaction.Competitive pressures coming from a very dynamic business environment are forcing companies to react faster to changing business conditions and customer requirements. As a result, there is now a need to use BI to help drive and optimize business operations on a daily basis, and, in some cases, even for intraday decision making. This type of BI is usually called operational business intelligence and real-time business intelligence.

BUSINESS INTELLIGENCE IN DECISION MAKING ON THE LABOR MARKET OF THE REPUBLIC OF MOLDOVA

Directory of Open Access Journals (Sweden)

Galina GLOBA

2013-12-01

Full Text Available Implementation of the business intelligence concept is enabling new opportunities for the labor market research and management. Labor market intelligence means a competent decision making process in the labor market. Such process should be based on the comprehensive set of analytical technologies and tools. The analysis of online information available at websites of state organizations working in the labor market of the Republic of Moldova has shown that many them are still at the very beginning of the effective data using.

Integrated human-machine intelligence in space systems

Science.gov (United States)

Boy, Guy A.

1992-01-01

The integration of human and machine intelligence in space systems is outlined with respect to the contributions of artificial intelligence. The current state-of-the-art in intelligent assistant systems (IASs) is reviewed, and the requirements of some real-world applications of the technologies are discussed. A concept of integrated human-machine intelligence is examined in the contexts of: (1) interactive systems that tolerate human errors; (2) systems for the relief of workloads; and (3) interactive systems for solving problems in abnormal situations. Key issues in the development of IASs include the compatibility of the systems with astronauts in terms of inputs/outputs, processing, real-time AI, and knowledge-based system validation. Real-world applications are suggested such as the diagnosis, planning, and control of enginnered systems.

Intelligent Transportation Control based on Proactive Complex Event Processing

Directory of Open Access Journals (Sweden)

Wang Yongheng

2016-01-01

Full Text Available Complex Event Processing (CEP has become the key part of Internet of Things (IoT. Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligent transportation control. In this paper, we propose a proactive CEP architecture and method for intelligent transportation control. Based on basic CEP technology and predictive analytic technology, a networked distributed Markov decision processes model with predicting states is proposed as sequential decision model. A Q-learning method is proposed for this model. The experimental evaluations show that this method works well when used to control congestion in in intelligent transportation systems.

Intelligent autonomous systems 12. Vol. 2. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Lee, Sukhan [Sungkyunkwan Univ., Gyeonggi-Do (Korea, Republic of). College of Information and Communication Engineering; Yoon, Kwang-Joon [Konkuk Univ., Seoul (Korea, Republic of); Cho, Hyungsuck [Daegu Gyeongbuk Institute of Science and Technology, Daegu (Korea, Republic of); Lee, Jangmyung (eds.) [Pusan National Univ. (Korea, Republic of). Dept. of Electronics Engineering

2013-02-01

Recent research in Intelligent and Autonomous Systems. Volume 2 of the proceedings of the 12th International Conference IAS-12, held June 26-29, 2012, jeju Island, Korea. Written by leading experts in the field. Intelligent autonomous systems are emerged as a key enabler for the creation of a new paradigm of services to humankind, as seen by the recent advancement of autonomous cars licensed for driving in our streets, of unmanned aerial and underwater vehicles carrying out hazardous tasks on-site, and of space robots engaged in scientific as well as operational missions, to list only a few. This book aims at serving the researchers and practitioners in related fields with a timely dissemination of the recent progress on intelligent autonomous systems, based on a collection of papers presented at the 12th International Conference on Intelligent Autonomous Systems, held in Jeju, Korea, June 26-29, 2012. With the theme of ''Intelligence and Autonomy for the Service to Humankind, the conference has covered such diverse areas as autonomous ground, aerial, and underwater vehicles, intelligent transportation systems, personal/domestic service robots, professional service robots for surgery/rehabilitation, rescue/security and space applications, and intelligent autonomous systems for manufacturing and healthcare. This volume 2 includes contributions devoted to Service Robotics and Human-Robot Interaction and Autonomous Multi-Agent Systems and Life Engineering.

Decision Exploration Lab : A Visual Analytics Solution for Decision Management

NARCIS (Netherlands)

Broeksema, Bertjan; Baudel, Thomas; Telea, Alex; Crisafulli, Paolo

2013-01-01

We present a visual analytics solution designed to address prevalent issues in the area of Operational Decision Management (ODM). In ODM, which has its roots in Artificial Intelligence (Expert Systems) and Management Science, it is increasingly important to align business decisions with business

The intelligent energy system for tomorrow

Energy Technology Data Exchange (ETDEWEB)

Larsen, Hans; Morthorst, Poul Erik; Bindslev, Henrik; Sonderberg Petersen, Leif

2010-09-15

In a future energy system non-fossil fuels have taken the lead, end-use technologies are highly efficient and closely interlinked to supply through intelligent energy systems. Climate change issues, security of supply and economic development need to be pursued concurrently. This calls for flexible and intelligent energy system infrastructures that effectively accommodate large amounts of fluctuating renewable energy and let the end-user interact with the supply through advanced ICT. The second important characteristic is intelligent integration of the entire transport sector. The third key area is advanced energy storage facilities in the system and the introduction of super-grids.

A Spatially Intelligent Public Participation System for the Environmental Impact Assessment Process

Directory of Open Access Journals (Sweden)

Lei Lei

2013-05-01

Full Text Available An environmental impact assessment (EIA is a decision-making process that evaluates the possible significant effects that a proposed project may exert on the environment. The EIA scoping and reviewing stages often involve public participation. Although its importance has long been recognized, public participation in the EIA process is often regarded as ineffective, due to time, budget, resource, technical and procedural constraints, as well as the complexity of environmental information. Geographic Information System (GIS and Volunteer Geographic Information (VGI have the potential to contribute to data collection, sharing and presentation, utilize local user-generated content to benefit decision-making and increase public outreach. This research integrated GIS, VGI, social media tools, data mining and mobile technology to design a spatially intelligent framework that presented and shared EIA information effectively to the public. A spatially intelligent public participative system (SIPPS was also developed as a proof-of-concept of the framework. The research selected the Tehachapi Renewable Transmission Project (TRTP as the pilot study area. Survey questionnaires were designed to collect feedback and conduct evaluation. Results show that SIPPS was able to improve the effectiveness of public participation, promote environmental awareness and achieve good system usability.

A general framework for intelligent recommender systems

Directory of Open Access Journals (Sweden)

Jose Aguilar

2017-07-01

Full Text Available In this paper, we propose a general framework for an intelligent recommender system that extends the concept of a knowledge-based recommender system. The intelligent recommender system exploits knowledge, learns, discovers new information, infers preferences and criticisms, among other things. For that, the framework of an intelligent recommender system is defined by the following components: knowledge representation paradigm, learning methods, and reasoning mechanisms. Additionally, it has five knowledge models about the different aspects that we can consider during a recommendation: users, items, domain, context and criticisms. The mix of the components exploits the knowledge, updates it and infers, among other things. In this work, we implement one intelligent recommender system based on this framework, using Fuzzy Cognitive Maps (FCMs. Next, we test the performance of the intelligent recommender system with specialized criteria linked to the utilization of the knowledge in order to test the versatility and performance of the framework.

Curricular Design for Intelligent Systems in Geosciences Using Urban Groundwater Studies.

Science.gov (United States)

Cabral-Cano, E.; Pierce, S. A.; Fuentes-Pineda, G.; Arora, R.

2016-12-01

Geosciences research frequently focuses on process-centered phenomena, studying combinations of physical, geological, chemical, biological, ecological, and anthropogenic factors. These interconnected Earth systems can be best understood through the use of digital tools that should be documented as workflows. To develop intelligent systems, it is important that geoscientists and computing and information sciences experts collaborate to: (1) develop a basic understanding of the geosciences and computing and information sciences disciplines so that the problem and solution approach are clear to all stakeholders, and (2) implement the desired intelligent system with a short turnaround time. However, these interactions and techniques are seldom covered in traditional Earth Sciences curricula. We have developed an exchange course on Intelligent Systems for Geosciences to support workforce development and build capacity to facilitate skill-development at the undergraduate student-level. The first version of this course was offered jointly by the University of Texas at Austin and the Universidad Nacional Autónoma de México as an intensive, study-abroad summer course. Content included: basic Linux introduction, shell scripting and high performance computing, data management, experts systems, field data collection exercises and basics of machine learning. Additionally, student teams were tasked to develop a term projects that centered on applications of Intelligent Systems applied to urban and karst groundwater systems. Projects included expert system and reusable workflow development for subsidence hazard analysis in Celaya, Mexico, a classification model to analyze land use change over a 30 Year Period in Austin, Texas, big data processing and decision support for central Texas groundwater case studies and 3D mapping with point cloud processing at three Texas field sites. We will share experiences and pedagogical insights to improve future versions of this course.

Application of computational intelligence in emerging power systems

African Journals Online (AJOL)

... in the electrical engineering applications. This paper highlights the application of computational intelligence methods in power system problems. Various types of CI methods, which are widely used in power system, are also discussed in the brief. Keywords: Power systems, computational intelligence, artificial intelligence.

A Framework for a General Purpose Intelligent Control System for Particle Accelerators. Phase II Final Report

International Nuclear Information System (INIS)

Westervelt, Robert; Klein, William; Kroupa, Michael; Olsson, Eric; Rothrock, Rick

1999-01-01

Vista Control Systems, Inc. has developed a portable system for intelligent accelerator control. The design is general in scope and is thus configurable to a wide range of accelerator facilities and control problems. The control system employs a multi-layer organization in which knowledge-based decision making is used to dynamically configure lower level optimization and control algorithms

Solar-Based Fuzzy Intelligent Water Sprinkle System

Directory of Open Access Journals (Sweden)

Riza Muhida

2012-03-01

Full Text Available A solar-based intelligent water sprinkler system project that has been developed to ensure the effectiveness in watering the plant is improved by making the system automated. The control system consists of an electrical capacitance soil moisture sensor installed into the ground which is interfaced to a controller unit of Motorola 68HC11 Handy board microcontroller. The microcontroller was programmed based on the decision rules made using fuzzy logic approach on when to water the lawn. The whole system is powered up by the solar energy which is then interfaced to a particular type of irrigation timer for plant fertilizing schedule and rain detector through a simple design of rain dual-collector tipping bucket. The controller unit automatically disrupted voltage signals sent to the control valves whenever irrigation was not needed. Using this system we combined the logic implementation in the area of irrigation and weather sensing equipment, and more efficient water delivery can be made possible. 

Student Modeling in an Intelligent Tutoring System

Science.gov (United States)

1996-12-17

Multi-Agent Architecture." Advances in Artificial Intelligence : Proceedings of the 12 th Brazilian Symposium on Aritificial Intelligence , edited by...STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D-27 DIMTVMON* fCKAJWINT A Appr"v*d t=i...Air Force Base, Ohio AFIT/GCS/ENG/96D-27 STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D

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.

Information for the user in design of intelligent systems

Science.gov (United States)

Malin, Jane T.; Schreckenghost, Debra L.

1993-01-01

Recommendations are made for improving intelligent system reliability and usability based on the use of information requirements in system development. Information requirements define the task-relevant messages exchanged between the intelligent system and the user by means of the user interface medium. Thus, these requirements affect the design of both the intelligent system and its user interface. Many difficulties that users have in interacting with intelligent systems are caused by information problems. These information problems result from the following: (1) not providing the right information to support domain tasks; and (2) not recognizing that using an intelligent system introduces new user supervisory tasks that require new types of information. These problems are especially prevalent in intelligent systems used for real-time space operations, where data problems and unexpected situations are common. Information problems can be solved by deriving information requirements from a description of user tasks. Using information requirements embeds human-computer interaction design into intelligent system prototyping, resulting in intelligent systems that are more robust and easier to use.

Approaches for Intelligent Traffic System: A Survey

OpenAIRE

Pratishtha Gupta; G.N Purohit; Amrita Dadhich

2012-01-01

This survey presents various approaches for intelligent traffic systems. The potential research fields in which Intelligent Traffic System emerges as an important application area are highlighted andvarious issues have been identified which need to be handled while developing such a system for an urban area, where an efficient traffic management has become the need of hour.A model is also proposed capable of managing intelligent traffic system using CCTV cameras and WAN. The proposed model wi...

Design, Development and Implementation of Decision Support Systems for Private Equity Investment

OpenAIRE

Vroomen, Paul

2017-01-01

The objective of this research is to design, develop and implement an intelligent decision support system (IDSS) for making rational private equity investment decisions. (Private equity investments are capital investments in enterprises that are not traded on public equity markets; they include Equity Buy-Out, Venture Capital, and the new Equity Crowd Funding (ECF) asset classes). The design and development of the IDSS requires the integration of investment science (valuation theory, portfoli...

A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

Science.gov (United States)

Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

2014-01-01

This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.

Eighth International Conference on Intelligent Systems and Knowledge Engineering

CERN Document Server

Li, Tianrui; ISKE 2013; Foundations of Intelligent Systems; Knowledge Engineering and Management; Practical Applications of Intelligent Systems

2014-01-01

"Foundations of Intelligent Systems" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but not limited to: Artificial Intelligence Theories, Pattern Recognition, Intelligent System Models, Speech Recognition, Computer Vision, Multi-Agent Systems, Machine Learning, Soft Computing and Fuzzy Systems, Biological Inspired Computation, Game Theory, Cognitive Systems and Information Processing, Computational Intelligence, etc. The proceedings are benefit for both researchers and practitioners who want to utilize intelligent methods in their specific research fields. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University...

Integrated system of structural health monitoring and intelligent management for a cable-stayed bridge.

Science.gov (United States)

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

Artificial intelligence and information-control systems of robots - 87

International Nuclear Information System (INIS)

Plander, I.

1987-01-01

Independent research areas of artificial intelligence represent the following problems: automatic problem solving and new knowledge discovering, automatic program synthesis, natural language, picture and scene recognition and understanding, intelligent control systems of robots equipped with sensoric subsystems, dialogue of two knowledge systems, as well as studying and modelling higher artificial intelligence attributes, such as emotionality and personality. The 4th Conference draws on the problems treated at the preceding Conferences, and presents the most recent knowledge on the following topics: theoretical problems of artificial intelligence, knowledge-based systems, expert systems, perception and pattern recognition, robotics, intelligent computer-aided design, special-purpose computer systems for artificial intelligence and robotics

Artificial intelligence: Neural network model as the multidisciplinary team member in clinical decision support to avoid medical mistakes

Directory of Open Access Journals (Sweden)

Igor Vyacheslavovich Buzaev

2016-09-01

Full Text Available Objective: The continuous uninterrupted feedback system is the essential part of any well-organized system. We propose aLYNX concept that is a possibility to use an artificial intelligence algorithm or a neural network model in decision-making system so as to avoid possible mistakes and to remind the doctors to review tactics once more in selected cases. Method: aLYNX system includes: registry with significant factors, decisions and results; machine learning process based on this registry data; the use of the machine learning results as the adviser. We show a possibility to build a computer adviser with a neural network model for making a choice between coronary aortic bypass surgery (CABG and percutaneous coronary intervention (PCI in order to achieve a higher 5-year survival rate in patients with angina based on the experience of 5107 patients. Results: The neural network was trained by 4679 patients who achieved 5-year survival. Among them, 2390 patients underwent PCI and 2289 CABG. After training, the correlation coefficient (r of the network was 0.74 for training, 0.67 for validation, 0.71 for test and 0.73 for total. Simulation of the neural network function has been performed after training in the two groups of patients with known 5-year outcome. The disagreement rate was significantly higher in the dead patient group than that in the survivor group between neural network model and heart team [16.8% (787/4679 vs. 20.3% (87/428, P = 0.065]. Conclusion: The study shows the possibility to build a computer adviser with a neural network model for making a choice between CABG and PCI in order to achieve a higher 5-year survival rate in patients with angina. Keywords: Coronary artery bypass grafting, Percutaneous coronary intervention, Artificial intelligence, Decision making

Business Intelligence from User Generated Content: Online Opinion Formation in Purchasing Decisions in High-Tech Markets

OpenAIRE

Setiya , Karan; Ubacht , Jolien; Cunningham , Scott; Oruç , Sertaç

2016-01-01

Part 6: Data Acquisition, Management and Analytics; International audience; User Generated Content (UGC) requires new business intelligence methods to understand the influence of online opinion formation on customer purchasing decisions. We developed a conceptual model for deriving business intelligence from tweets, based on the Classical Model of Consensus Formation and the Theory of Planned Behaviour. We applied the model to the dynamic high-tech smartphone market by means of three case stu...

Advanced approaches to intelligent information and database systems

CERN Document Server

Boonjing, Veera; Chittayasothorn, Suphamit

2014-01-01

This book consists of 35 chapters presenting different theoretical and practical aspects of Intelligent Information and Database Systems. Nowadays both Intelligent and Database Systems are applied in most of the areas of human activities which necessitates further research in these areas. In this book various interesting issues related to the intelligent information models and methods as well as their advanced applications, database systems applications, data models and their analysis, and digital multimedia methods and applications are presented and discussed both from the practical and theoretical points of view. The book is organized in four parts devoted to intelligent systems models and methods, intelligent systems advanced applications, database systems methods and applications, and multimedia systems methods and applications. The book will be interesting for both practitioners and researchers, especially graduate and PhD students of information technology and computer science, as well more experienced ...

Research and Development of a Network-Based Intelligent Maintenance Information System

Institute of Scientific and Technical Information of China (English)

ZANG Tie-gang; YANG Ming-zhong; GUO Shun-sheng

2003-01-01

A maintenance information system is an important part of equipment management. An intelli gent maintenance information system ( IMIS) is a synthesis of network technology, information technology and intelligent technology. The IMIS is used to finish flexible maintenance decision-making and fast maintenance planning, which helps enterprises to effectively reduce maintenance cost and increase working efficiency. Because the IMIS integrates advanced technologies, its performance is better than a traditional one.The difference between an IMIS and a traditional maintenance information system, and the functions, structure, important realizations, and application of an IMIS are discussed in this paper.

Cost-effective implementation of intelligent systems

Science.gov (United States)

Lum, Henry, Jr.; Heer, Ewald

1990-01-01

Significant advances have occurred during the last decade in knowledge-based engineering research and knowledge-based system (KBS) demonstrations and evaluations using integrated intelligent system technologies. Performance and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent system technologies can be realized. In this paper the rationale and potential benefits for typical examples of application projects that demonstrate an increase in productivity through the use of intelligent system technologies are discussed. These demonstration projects have provided an insight into additional technology needs and cultural barriers which are currently impeding the transition of the technology into operational environments. Proposed methods which addresses technology evolution and implementation are also discussed.

Intelligent Lighting Control System

OpenAIRE

García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

2014-01-01

This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

Computational Intelligence for Engineering Systems

CERN Document Server

Madureira, A; Vale, Zita

2011-01-01

"Computational Intelligence for Engineering Systems" provides an overview and original analysis of new developments and advances in several areas of computational intelligence. Computational Intelligence have become the road-map for engineers to develop and analyze novel techniques to solve problems in basic sciences (such as physics, chemistry and biology) and engineering, environmental, life and social sciences. The contributions are written by international experts, who provide up-to-date aspects of the topics discussed and present recent, original insights into their own experien

Intelligent decision aids for abnormal events in nuclear power plants

International Nuclear Information System (INIS)

Kafka, P.; Polke, H.

1988-01-01

German nuclear power plants are characterized by a high degree of automation, not only for normal operation but also for abnormal events. Therefore the role of the operating personnel is mainly a supervisory function. Nevertheless, for a spectrum of unexpected events the operating personnel have to react with manual recovery actions. In order to minimize human error in such recovery actions, different kinds of intelligent decision aid support the operators today. In this paper such aids are discussed and one of them is described in more detail. (author)

Internet-based intelligent information processing systems

CERN Document Server

Tonfoni, G; Ichalkaranje, N S

2003-01-01

The Internet/WWW has made it possible to easily access quantities of information never available before. However, both the amount of information and the variation in quality pose obstacles to the efficient use of the medium. Artificial intelligence techniques can be useful tools in this context. Intelligent systems can be applied to searching the Internet and data-mining, interpreting Internet-derived material, the human-Web interface, remote condition monitoring and many other areas. This volume presents the latest research on the interaction between intelligent systems (neural networks, adap

Intelligent fractions learning system: implementation

CSIR Research Space (South Africa)

Smith, Andrew C

2011-05-01

Full Text Available Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2011 ISBN: 978-1-905824-24-3 An Intelligent Fractions Learning System: Implementation Andrew Cyrus SMITH1, Teemu H. LAINE2 1CSIR... to fractions. Our aim with the current research project is to extend the existing UFractions learning system to incorporate automatic data capturing. ?Intelligent UFractions? allows a teacher to remotely monitor the children?s progress during...

Intelligent Systems and Advanced User Interfaces for Design, Operation, and Maintenance of Command Management Systems

Science.gov (United States)

Mitchell, Christine M.

1998-01-01

Historically Command Management Systems (CMS) have been large, expensive, spacecraft-specific software systems that were costly to build, operate, and maintain. Current and emerging hardware, software, and user interface technologies may offer an opportunity to facilitate the initial formulation and design of a spacecraft-specific CMS as well as a to develop a more generic or a set of core components for CMS systems. Current MOC (mission operations center) hardware and software include Unix workstations, the C/C++ and Java programming languages, and X and Java window interfaces representations. This configuration provides the power and flexibility to support sophisticated systems and intelligent user interfaces that exploit state-of-the-art technologies in human-machine systems engineering, decision making, artificial intelligence, and software engineering. One of the goals of this research is to explore the extent to which technologies developed in the research laboratory can be productively applied in a complex system such as spacecraft command management. Initial examination of some of the issues in CMS design and operation suggests that application of technologies such as intelligent planning, case-based reasoning, design and analysis tools from a human-machine systems engineering point of view (e.g., operator and designer models) and human-computer interaction tools, (e.g., graphics, visualization, and animation), may provide significant savings in the design, operation, and maintenance of a spacecraft-specific CMS as well as continuity for CMS design and development across spacecraft with varying needs. The savings in this case is in software reuse at all stages of the software engineering process.

Intelligence, mapping, and geospatial exploitation system (IMAGES)

Science.gov (United States)

Moellman, Dennis E.; Cain, Joel M.

1998-08-01

This paper provides further detail to one facet of the battlespace visualization concept described in last year's paper Battlespace Situation Awareness for Force XXI. It focuses on the National Imagery and Mapping Agency (NIMA) goal to 'provide customers seamless access to tailorable imagery, imagery intelligence, and geospatial information.' This paper describes Intelligence, Mapping, and Geospatial Exploitation System (IMAGES), an exploitation element capable of CONUS baseplant operations or field deployment to provide NIMA geospatial information collaboratively into a reconnaissance, surveillance, and target acquisition (RSTA) environment through the United States Imagery and Geospatial Information System (USIGS). In a baseplant CONUS setting IMAGES could be used to produce foundation data to support mission planning. In the field it could be directly associated with a tactical sensor receiver or ground station (e.g. UAV or UGV) to provide near real-time and mission specific RSTA to support mission execution. This paper provides IMAGES functional level design; describes the technologies, their interactions and interdependencies; and presents a notional operational scenario to illustrate the system flexibility. Using as a system backbone an intelligent software agent technology, called Open Agent ArchitectureTM (OAATM), IMAGES combines multimodal data entry, natural language understanding, and perceptual and evidential reasoning for system management. Configured to be DII COE compliant, it would utilize, to the extent possible, COTS applications software for data management, processing, fusion, exploitation, and reporting. It would also be modular, scaleable, and reconfigurable. This paper describes how the OAATM achieves data synchronization and enables the necessary level of information to be rapidly available to various command echelons for making informed decisions. The reasoning component will provide for the best information to be developed in the timeline

Towards an Understanding of the Role of Business Intelligence Systems in Organizational Knowing

DEFF Research Database (Denmark)

Shollo, Arisa; Galliers, Robert D.

2013-01-01

Advances in information technology (IT) have increased the ability of organizations to collect and analyze intelligence to support decisions. Over the last two decades the concept of business intelligence (BI) and actual BI technologies have gained prominence. Recent studies provide evidence...

DECISION SUPPORT SYSTEMS IN MILITARY ACTIONS: NECESSITY, POSSIBILITIES AND CONSTRAINTS

Directory of Open Access Journals (Sweden)

Elena ŞUŞNEA

2012-01-01

Full Text Available Nowadays, modern organizations cannot resort to the decision-making process without relying on information and communication technology if they want to be successful. Thus, besides information as an important input of this process, the tools and techniques used by decision-makers are equally important in the support and validation of their decisions. All this is also valid for the military organizations and their specific tasks and activities. A fortiori military commanders face some of the most diff cult and high-stake decision issues meaningful not only at the level of the military, but also for the humankind. Under these circumstances and as a result of an increase in the diversity and complexity of conflict situations, in the information and technology means employed by opponents in warfare and in the amount of information needed to be processed in real time, decision support systems become a necessity. Starting from the aforementioned inevitable requirement, the aim of this article is to emphasize the possibilities and constraints in developing an intelligent decision support system that assists commanders in making scientific decisions on time, under the right circumstances, for the right costs.

A fuzzy intelligent system for land consolidation - a case study in Shunde, China

Science.gov (United States)

Wang, J.; Ge, A.; Hu, Y.; Li, C.; Wang, L.

2015-04-01

Traditionally, potential evaluation methods for farmland consolidation have depended mainly on the experts' experiences, statistical computations or subjective adjustments. Some biases usually exist in the results. Thus, computer-aided technology has become essential. In this study, an intelligent evaluation system based on a fuzzy decision tree was established, and this system can deal with numerical data, discrete data and symbolic data. When the original land data are input, the level of potential of the agricultural land for development will be output by this new model. The provision of objective proof for decision making by authorities in rural management is helpful. Agricultural land data characteristically comprise large volumes, complex varieties and more indexes. In land consolidation, it is very important to construct an effective index system. We needed to select a group of indexes useful for land consolidation according to the concrete demand. In this paper, a fuzzy measure, which can describe the importance of a single feature or a group of features, is adopted to accomplish the selection of specific features. A fuzzy integral that is based on a fuzzy measure is a type of fusion tool. We obtained the optimal solution for a fuzzy measure by solving a fuzzy integral. The fuzzy integrals can be transformed to a set of linear equations. We applied the L1-norm regularization method to solve the linear equations, and we found a solution with the fewest nonzero elements for the fuzzy measure; this solution shows the contribution of corresponding features or the combinations of decisions. This algorithm provides a quick and optimal way to identify the land index system when preparing to conduct the research, such as we describe herein, on land consolidation. Shunde's "Three Old" consolidation project provides the data for this work. Our estimation system was compared with a conventional evaluation system that is still accepted by the public. Our results prove

Increases in Emotional Intelligence After an Online Training Program Are Associated With Better Decision-Making on the Iowa Gambling Task.

Science.gov (United States)

Alkozei, Anna; Smith, Ryan; Demers, Lauren A; Weber, Mareen; Berryhill, Sarah M; Killgore, William D S

2018-01-01

Higher levels of emotional intelligence have been associated with better inter and intrapersonal functioning. In the present study, 59 healthy men and women were randomized into either a three-week online training program targeted to improve emotional intelligence ( n = 29), or a placebo control training program targeted to improve awareness of nonemotional aspects of the environment ( n = 30). Compared to placebo, participants in the emotional intelligence training group showed increased performance on the total emotional intelligence score of the Mayer-Salovey-Caruso Emotional Intelligence Test, a performance measure of emotional intelligence, as well as subscales of perceiving emotions and facilitating thought. Moreover, after emotional intelligence training, but not after placebo training, individuals displayed the ability to arrive at optimal performance faster (i.e., they showed a faster learning rate) during an emotion-guided decision-making task (i.e., the Iowa Gambling Task). More specifically, although both groups showed similar performance at the start of the Iowa Gambling Task from pre- to posttraining, the participants in the emotional intelligence training group learned to choose more advantageous than disadvantageous decks than those in the placebo training group by the time they reached the "hunch" period of the task (i.e., the point in the task when implicit task learning is thought to have occurred). Greater total improvements in performance on the Iowa Gambling Task from pre- to posttraining in the emotional intelligence training group were also positively correlated with pre- to posttraining changes in Mayer-Salovey-Caruso Emotional Intelligence Test scores, in particular with changes in the ability to perceive emotions. The present study provides preliminary evidence that emotional intelligence can be trained with the help of an online training program targeted at adults; it also suggests that changes in emotional intelligence, as a

Intelligent monitoring-based safety system of massage robot

Institute of Scientific and Technical Information of China (English)

胡宁; 李长胜; 王利峰; 胡磊; 徐晓军; 邹雲鹏; 胡玥; 沈晨

2016-01-01

As an important attribute of robots, safety is involved in each link of the full life cycle of robots, including the design, manufacturing, operation and maintenance. The present study on robot safety is a systematic project. Traditionally, robot safety is defined as follows: robots should not collide with humans, or robots should not harm humans when they collide. Based on this definition of robot safety, researchers have proposed ex ante and ex post safety standards and safety strategies and used the risk index and risk level as the evaluation indexes for safety methods. A massage robot realizes its massage therapy function through applying a rhythmic force on the massage object. Therefore, the traditional definition of safety, safety strategies, and safety realization methods cannot satisfy the function and safety requirements of massage robots. Based on the descriptions of the environment of massage robots and the tasks of massage robots, the present study analyzes the safety requirements of massage robots; analyzes the potential safety dangers of massage robots using the fault tree tool; proposes an error monitoring-based intelligent safety system for massage robots through monitoring and evaluating potential safety danger states, as well as decision making based on potential safety danger states; and verifies the feasibility of the intelligent safety system through an experiment.

The Synthesis of Intelligent Real-Time Systems

Science.gov (United States)

1990-11-09

Synthesis of Intelligent Real - Time Systems . The purpose of the effort was to develop and extend theories and techniques that facilitate the design and...implementation of intelligent real - time systems . In particular, Teleos has extended situated-automata theory to apply to situations in which the system has

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

Science.gov (United States)

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

2014-01-01

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

Artificial Intelligence and Spacecraft Power Systems

Science.gov (United States)

Dugel-Whitehead, Norma R.

1997-01-01

This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

Integrated System of Structural Health Monitoring and Intelligent Management for a Cable-Stayed Bridge

Directory of Open Access Journals (Sweden)

Bin Chen

2014-01-01

Full Text Available It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province. The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

Applications of artificial intelligence technology to wastewater treatment fields in China

Institute of Scientific and Technical Information of China (English)

QING Xiao-xia; WANG Bo; MENG De-tao

2005-01-01

Current applications of artificial intelligence technology to wastewater treatment in China are summarized. Wastewater treatment plants use expert system mainly in the operation decision-making and fault diagnosis of system operation, use artificial neuron network for system modeling, water quality forecast and soft measure, and use fuzzy control technology for the intelligence control of wastewater treatment process. Finally, the main problems in applying artificial intelligence technology to wastewater treatment in China are analyzed.

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

Directory of Open Access Journals (Sweden)

Bo Sun

2012-01-01

Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

Development of an intelligent hydroinformatic system for real-time monitoring and assessment of civil infrastructure

Science.gov (United States)

Cahill, Paul; Michalis, Panagiotis; Solman, Hrvoje; Kerin, Igor; Bekic, Damir; Pakrashi, Vikram; McKeogh, Eamon

2017-04-01

With the effects of climate change becoming more apparent, extreme weather events are now occurring with greater frequency throughout the world. Such extreme events have resulted in increased high intensity flood events which are having devastating consequences on hydro-structures, especially on bridge infrastructure. The remote and often inaccessible nature of such bridges makes inspections problematic, a major concern if safety assessments are required during and after extreme flood events. A solution to this is the introduction of smart, low cost sensing solutions at locations susceptible to hydro-hazards. Such solutions can provide real-time information on the health of the bridge and its environments, with such information aiding in the mitigation of the risks associated with extreme weather events. This study presents the development of an intelligent system for remote, real-time monitoring of hydro-hazards to bridge infrastructure. The solution consists of two types of remote monitoring stations which have the capacity to monitor environmental conditions and provide real-time information to a centralized, big data database solution, from which an intelligent decision support system will accommodate the results to control and manage bridge, river and catchment assets. The first device developed as part of the system is the Weather Information Logging Device (WILD), which monitors rainfall, temperature and air and soil moisture content. The ability of the WILD to monitor rainfall in real time enables flood early warning alerts and predictive river flow conditions, thereby enabling decision makers the ability to make timely and effective decisions about critical infrastructures in advance of extreme flood events. The WILD is complemented by a second monitoring device, the Bridge Information Recording Device (BIRD), which monitors water levels at a given location in real-time. The monitoring of water levels of a river allows for, among other applications

A Review of Automated Decision Support System

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... Intelligence AI that enable decision automation based on existing facts, knowledge ... The growing reliance on data impacts dynamic data extraction and retrieval of the ... entertainment, medical, and the web. III. DECISION ...

Conceptual Model of Business Value of Business Intelligence Systems

OpenAIRE

Popovič, Aleš; Turk, Tomaž; Jaklič, Jurij

2010-01-01

With advances in the business intelligence area, there is an increasing interest for the introduction of business intelligence systems into organizations. Although the opinion about business intelligence and its creation of business value is generally accepted, economic justification of investments into business intelligence systems is not always clear. Measuring the business value of business intelligence in practice is often not carried out due to the lack of measurement methods and resourc...

Computational red teaming risk analytics of big-data-to-decisions intelligent systems

CERN Document Server

Abbass, Hussein A

2015-01-01

Written to bridge the information needs of management and computational scientists, this book presents the first comprehensive treatment of Computational Red Teaming (CRT).  The author describes an analytics environment that blends human reasoning and computational modeling to design risk-aware and evidence-based smart decision making systems. He presents the Shadow CRT Machine, which shadows the operations of an actual system to think with decision makers, challenge threats, and design remedies. This is the first book to generalize red teaming (RT) outside the military and security domains and it offers coverage of RT principles, practical and ethical guidelines. The author utilizes Gilbert’s principles for introducing a science. Simplicity: where the book follows a special style to make it accessible to a wide range of  readers. Coherence:  where only necessary elements from experimentation, optimization, simulation, data mining, big data, cognitive information processing, and system thinking are blend...

A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

DEFF Research Database (Denmark)

Lynggaard, Per

2013-01-01

A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where...... the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented...... distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more...

Depending on Data: Business Intelligence Systems Drive Reform

Science.gov (United States)

Halligan, Tom

2010-01-01

As more community colleges focus on using data to improve educational outcomes, many administrators are considering business intelligence applications that promise a path toward more informed decisions. Getting there, leaders say, requires more than installing some out-of-the-box solution; it requires changing the culture and finding skilled…

Patterns and Intelligent Systems

International Nuclear Information System (INIS)

Cordes, Gail A.

2003-01-01

The recognition and analysis of evolving patterns provides a unifying concept for studying and implementing intelligent information processing for open feedback control systems within the nuclear industry. Control is considered as influence of a large system to achieve the goals of the human (who might or might not be part of an open feedback loop) and is not limited to operation of a component within a nuclear power plant. The intelligent control system includes open logic and can automatically react to new data in an unprogrammed way. This application of evolving patterns integrates current research developments in human cognition and scientific semiotics with traditional feedback control. A preliminary implementation of such a system using existing computational techniques is postulated, and tools that are lacking at this time are identified. Proof-of-concept applications for the nuclear industry are referenced

Handbook on Decision Making Vol 2 Risk Management in Decision Making

CERN Document Server

Lu, Jie; Zhang, Guangquan

2012-01-01

This book presents innovative theories, methodologies, and techniques in the field of risk management and decision making. It introduces new research developments and provides a comprehensive image of their potential applications to readers interested in the area. The collection includes: computational intelligence applications in decision making, multi-criteria decision making under risk, risk modelling,forecasting and evaluation, public security and community safety, risk management in supply chain and other business decision making, political risk management and disaster response systems. The book is directed to academic and applied researchers working on risk management, decision making, and management information systems.

Intelligent transportation systems problems and perspectives

CERN Document Server

Pamuła, Wiesław

2016-01-01

This book presents a discussion of problems encountered in the deployment of Intelligent Transport Systems (ITS). It puts emphasis on the early tasks of designing and proofing the concept of integration of technologies in Intelligent Transport Systems. In its first part the book concentrates on the design problems of urban ITS. The second part of the book features case studies representative for the different modes of transport. These are freight transport, rail transport and aerospace transport encompassing also space stations. The book provides ideas for deployment which may be developed by scientists and engineers engaged in the design of Intelligent Transport Systems. It can also be used in the training of specialists, students and post-graduate students in universities and transport high schools.    .

Fixed Point Learning Based Intelligent Traffic Control System

Science.gov (United States)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

Computational intelligence techniques in health care

CERN Document Server

Zhou, Wengang; Satheesh, P

2016-01-01

This book presents research on emerging computational intelligence techniques and tools, with a particular focus on new trends and applications in health care. Healthcare is a multi-faceted domain, which incorporates advanced decision-making, remote monitoring, healthcare logistics, operational excellence and modern information systems. In recent years, the use of computational intelligence methods to address the scale and the complexity of the problems in healthcare has been investigated. This book discusses various computational intelligence methods that are implemented in applications in different areas of healthcare. It includes contributions by practitioners, technology developers and solution providers.

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.

2nd International Conference on Advanced Intelligent Systems and Informatics

CERN Document Server

Shaalan, Khaled; Gaber, Tarek; Azar, Ahmad; Tolba, M

2017-01-01

This book gathers the proceedings of the 2nd International Conference on Advanced Intelligent Systems and Informatics (AISI2016), which took place in Cairo, Egypt during October 24–26, 2016. This international interdisciplinary conference, which highlighted essential research and developments in the field of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE) and sponsored by the IEEE Computational Intelligence Society (Egypt chapter) and the IEEE Robotics and Automation Society (Egypt Chapter). The book’s content is divided into four main sections: Intelligent Language Processing, Intelligent Systems, Intelligent Robotics Systems, and Informatics.

Business intelligence and mobile technology research an information systems engineering perspective

CERN Document Server

Laouar, Mohamed Ridda

2014-01-01

All business organizations strive for increasing their growth by seizing new opportunities, reducing enterprise costs, attracting new customers and retaining old customers. In doing so, business intelligence and analytics allow business organizations to make better plans, informed decisions, and monitor their progress towards planned goals and objectives. The more disruptive power of IT technologies comes synergistically. Individual IT technologies do not work in isolation. Business intellige...

Artificial intelligence executive summary

International Nuclear Information System (INIS)

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

1984-01-01

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

Modeling of biological intelligence for SCM system optimization.

Science.gov (United States)

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Science.gov (United States)

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

Artificial intelligence in cardiology

OpenAIRE

Bonderman, Diana

2017-01-01

Summary Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiol...

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

Science.gov (United States)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land

Blindness in designing intelligent systems

Science.gov (United States)

Denning, Peter J.

1988-01-01

New investigations of the foundations of artificial intelligence are challenging the hypothesis that problem solving is the cornerstone of intelligence. New distinctions among three domains of concern for humans--description, action, and commitment--have revealed that the design process for programmable machines, such as expert systems, is based on descriptions of actions and induces blindness to nonanalytic action and commitment. Design processes focusing in the domain of description are likely to yield programs like burearcracies: rigid, obtuse, impersonal, and unable to adapt to changing circumstances. Systems that learn from their past actions, and systems that organize information for interpretation by human experts, are more likely to be successful in areas where expert systems have failed.

Intelligent Home Control System Based on ARM10

Science.gov (United States)

Chen, G. X.; Jiang, J.; Zhong, L. H.

2017-10-01

Intelligent home is becoming the hot spot of social attention in the 21st century. When it is in China, it is a really new industry. However, there is no doubt that Intelligent home will become a new economic growth point of social development; it will change the life-style of human being. To develop the intelligent home, we should keep up with the development trend of technology. This is the reason why I talk about the intelligent home control system here. In this paper, intelligent home control system is designed for alarm and remote control on gas- leaking, fire disaster, earthquake prediction, etc., by examining environmental changes around house. When the Intelligent home control system has detected an accident occurs, the processor will communicate with the GSM module, informing the house keeper the occurrence of accident. User can receive and send the message to the system to cut the power by mobile phone. The system can get access to DCCthrough ARM10 JTAG interface, using DCC to send and receive messages. At the same time, the debugger on the host is mainly used to receive the user’s command and send it to the debug component in the target system. The data that returned from the target system is received and displayed to the user in a certain format.

DEVELOPMENT OF THE INTELLECTUAL AGENT-ORIENTED SYSTEM FOR DECISION SUPPORT AT ENTERPRISE

OpenAIRE

G. Chornous

2014-01-01

Actual status of management confirms usefulness and necessity for development of scientific modeling tools for decision-making processes based on distributed artificial intelligence. The paper presents opportunities of the agent – oriented approach to support operative and strategic management decisions at the pharmaceutical enterprise. It is argued that the combination of intelligent agents technology and Data Mining (DM) produces a powerful synergistic effect. The basis of the intellectual ...

Use of artificial intelligence in supervisory control

Science.gov (United States)

Cohen, Aaron; Erickson, Jon D.

1989-01-01

Viewgraphs describing the design and testing of an intelligent decision support system called OFMspert are presented. In this expert system, knowledge about the human operator is represented through an operator/system model referred to as the OFM (Operator Function Model). OFMspert uses the blackboard model of problem solving to maintain a dynamic representation of operator goals, plans, tasks, and actions given previous operator actions and current system state. Results of an experiment to assess OFMspert's intent inferencing capability are outlined. Finally, the overall design philosophy for an intelligent tutoring system (OFMTutor) for operators of complex dynamic systems is summarized.

12th International Conference on Intelligent Autonomous Systems

CERN Document Server

Cho, Hyungsuck; Yoon, Kwang-Joon; Lee, Jangmyung

2013-01-01

Intelligent autonomous systems are emerged as a key enabler for the creation of a new paradigm of services to humankind, as seen by the recent advancement of autonomous cars licensed for driving in our streets, of unmanned aerial and underwater vehicles carrying out hazardous tasks on-site, and of space robots engaged in scientific as well as operational missions, to list only a few. This book aims at serving the researchers and practitioners in related fields with a timely dissemination of the recent progress on intelligent autonomous systems, based on a collection of papers presented at the 12th International Conference on Intelligent Autonomous Systems, held in Jeju, Korea, June 26-29, 2012. With the theme of “Intelligence and Autonomy for the Service to Humankind, the conference has covered such diverse areas as autonomous ground, aerial, and underwater vehicles, intelligent transportation systems, personal/domestic service robots, professional service robots for surgery/rehabilitation, rescue/security ...

STUDY OF BUSINESS INTELLIGENCE SYSTEM QUALITY

OpenAIRE

DENIC Nebojsa; VUJOVIC Vuk; PERENIC Goran; SPASIC Boban

2016-01-01

IT has made remarkable progress over the last years. Business intelligence systems have been developing as an important part of IT. Enterprises often fail to realize importance and necessity of implementation of business intelligence solutions. This paper will deal with the approach for assessment of business intelligence in enterprises, based on maturity models. The significance of this paper is in the development of new conceptual research models which do not apply the usual thesis on ma...

Intelligent Bus Stops in the Flexible Bus Systems

OpenAIRE

Razi Iqbal; Muhammad Usman Ghani

2014-01-01

The purpose of this paper is to discuss Intelligent Bus Stops in a special Demand Responsive Transit (DRT), the Flexible Bus System. These Intelligent Bus Stops are more efficient and information rich than Traditional Bus Stops. The real time synchronization of the Flexible Bus System makes it unique as compared to Traditional Bus Systems. The Main concern is to make Bus Stops intelligent and information rich. Buses are informed about the no. of passengers waiting at the upcoming ...

A Fuzzy ANP Model Integrated with Benefits, Opportunities, Costs, and Risks to Prioritize Intelligent Power Grid Systems

Directory of Open Access Journals (Sweden)

Hsing Hung Chen

2013-01-01

Full Text Available Although growth of renewable energy is envisaged, many concerns are critical like the ability to maintain the balance between demands and supply and the variability, noncontrollability, and flexibility of the sources. Then, what will be the future concerns about the main composition of intelligent power grid systems in the future? There is no such research tackled before. Thus, this paper first finds critical success criteria of intelligent power grid systems and then constructs a multiple criteria and decision making model to help in identifying the suitable trends under complex economic performance, environmental impacts, and rapid technological and marketing changes. After empirical demonstration, the paper summarizes that the most suitable composition of future intelligent power grid systems should be constituted by “DHT” P2P grid, “C&D workflow” P2P scheduling, “GARCM” trustworthy P2P grid, and “multipurpose” grid applications in the future.

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…

Swarm Intelligence systems

International Nuclear Information System (INIS)

Beni, G.

1994-01-01

We review the characteristics of Swarm Intelligence and discuss systems exhibiting it. The recently developed mathematical description of Swarm behavior is also reviewed and discussed. The self-organization of Swarms is described as the reconfiguring asynchronously and conservatively of a distribution. Swarm reconfigurations are based on producing distributions that are solutions to systems of linear equations. Conservation and asynchronicity are related, respectively, to the global and local nature of the Swarm problem. The conditions for the convergence of the Swarm algorithm are presented. The important point is that, under very general conditions, the Swarm reconfigures in a time which is independent of the size of the Swarm. This fact implies that a centralized controller can never reconfigure as fast as a Swarm provided the size of the Swarm is large enough. This result is related to the unpredictability of the Swarm, a basic property of Swarm Intelligence. Finally, the conditions under which Swarm algorithms become of practical importance are discussed and examples given. (author)

Decision-making and cognitive abilities: A review of associations between Iowa Gambling Task performance, executive functions, and intelligence.

Science.gov (United States)

Toplak, Maggie E; Sorge, Geoff B; Benoit, André; West, Richard F; Stanovich, Keith E

2010-07-01

The Iowa Gambling Task (IGT) has been used to study decision-making differences in many different clinical and developmental samples. It has been suggested that IGT performance captures abilities that are separable from cognitive abilities, including executive functions and intelligence. The purpose of the current review was to examine studies that have explicitly examined the relationship between IGT performance and these cognitive abilities. We included 43 studies that reported correlational analyses with IGT performance, including measures of inhibition, working memory, and set-shifting as indices of executive functions, as well as measures of verbal, nonverbal, and full-scale IQ as indices of intelligence. Overall, only a small proportion of the studies reported a statistically significant relationship between IGT performance and these cognitive abilities. The majority of studies reported a non-significant relationship. Of the minority of studies that reported statistically significant effects, effect sizes were, at best, small to modest, and confidence intervals were large, indicating that considerable variability in performance on the IGT is not captured by current measures of executive function and intelligence. These findings highlight the separability between decision-making on the IGT and cognitive abilities, which is consistent with recent conceptualizations that differentiate rationality from intelligence. 2010 Elsevier Ltd. All rights reserved.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

Science.gov (United States)

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

Directory of Open Access Journals (Sweden)

Monica Villaverde

2015-11-01

Full Text Available The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Dynamical cognitive services for ambient intelligence environments

NARCIS (Netherlands)

Acampora, G.; Loia, V.; Lee, C.-S.; Wang, M.-H.

2009-01-01

Ambient Intelligence systems are more than a simple integration among computer technologies, indeed, their design can strongly depend upon psychology and social sciences aspects describing, analyzing and forecasting the human being status during the system's decision making. Consequently, if from a

Integrating Hypermedia Objects In An Intelligent Tutoring System

Directory of Open Access Journals (Sweden)

Emilia PECHEANU

2001-12-01

Full Text Available The paper describes the internal architecture of an Intelligent Tutoring System, CS-Tutor. The architectural design of the tutorial system was developed in a collaborative work at the Department of Computer Science of the University of Galati and the Department of Applied Informatics of the Faculty of Computer Science of Iasi. Intelligent Tutoring Systems (ITS are software packages which use the Artificial Intelligence techniques to aid in learning of some subject or skill. In recent years, Hypermedia has been gained the interest of many researchers working in the teaching field of study. The CS-Tutor internal architecture is based upon integrating Hypermedia Objects in an Intelligent Knowledge-Based frame.

International Conference on Intelligent Unmanned Systems (ICIUS)

CERN Document Server

Kartidjo, Muljowidodo; Yoon, Kwang-Joon; Budiyono, Agus; Autonomous Control Systems and Vehicles : Intelligent Unmanned Systems

2013-01-01

The International Conference on Intelligent Unmanned Systems 2011 was organized by the International Society of Intelligent Unmanned Systems and locally by the Center for Bio-Micro Robotics Research at Chiba University, Japan. The event was the 7th conference continuing from previous conferences held in Seoul, Korea (2005, 2006), Bali, Indonesia (2007), Nanjing, China (2008), Jeju, Korea (2009), and Bali, Indonesia (2010). ICIUS 2011 focused on both theory and application, primarily covering the topics of robotics, autonomous vehicles, intelligent unmanned technologies, and biomimetics. We invited seven keynote speakers who dealt with related state-of-the-art technologies including unmanned aerial vehicles (UAVs) and micro air vehicles (MAVs), flapping wings (FWs), unmanned ground vehicles (UGVs), underwater vehicles (UVs), bio-inspired robotics, advanced control, and intelligent systems, among others. This book is a collection of excellent papers that were updated after presentation at ICIUS2011. All papers ...

Computational Intelligence in Information Systems Conference

CERN Document Server

Au, Thien-Wan; Omar, Saiful

2017-01-01

This book constitutes the Proceedings of the Computational Intelligence in Information Systems conference (CIIS 2016), held in Brunei, November 18–20, 2016. The CIIS conference provides a platform for researchers to exchange the latest ideas and to present new research advances in general areas related to computational intelligence and its applications. The 26 revised full papers presented in this book have been carefully selected from 62 submissions. They cover a wide range of topics and application areas in computational intelligence and informatics.

Intelligent computational systems for space applications

Science.gov (United States)

Lum, Henry; Lau, Sonie

Intelligent computational systems can be described as an adaptive computational system integrating both traditional computational approaches and artificial intelligence (AI) methodologies to meet the science and engineering data processing requirements imposed by specific mission objectives. These systems will be capable of integrating, interpreting, and understanding sensor input information; correlating that information to the "world model" stored within its data base and understanding the differences, if any; defining, verifying, and validating a command sequence to merge the "external world" with the "internal world model"; and, controlling the vehicle and/or platform to meet the scientific and engineering mission objectives. Performance and simulation data obtained to date indicate that the current flight processors baselined for many missions such as Space Station Freedom do not have the computational power to meet the challenges of advanced automation and robotics systems envisioned for the year 2000 era. Research issues which must be addressed to achieve greater than giga-flop performance for on-board intelligent computational systems have been identified, and a technology development program has been initiated to achieve the desired long-term system performance objectives.

Components of a Business Intelligence software solution

OpenAIRE

Daniel BALACEANU

2007-01-01

Business intelligence (BI) is a business management term which refers to applications and technologies which are used to gather, provide access to, and analyze data and information about company operations. Business intelligence systems can help companies have a more comprehensive knowledge of the factors affecting their business, such as metrics on sales, production, internal operations, and they can help companies to make better business decisions.

Empirical evaluation of decision support systems: Needs, definitions, potential methods, and an example pertaining to waterfowl management

Science.gov (United States)

Sojda, R.S.

2007-01-01

Decision support systems are often not empirically evaluated, especially the underlying modelling components. This can be attributed to such systems necessarily being designed to handle complex and poorly structured problems and decision making. Nonetheless, evaluation is critical and should be focused on empirical testing whenever possible. Verification and validation, in combination, comprise such evaluation. Verification is ensuring that the system is internally complete, coherent, and logical from a modelling and programming perspective. Validation is examining whether the system is realistic and useful to the user or decision maker, and should answer the question: “Was the system successful at addressing its intended purpose?” A rich literature exists on verification and validation of expert systems and other artificial intelligence methods; however, no single evaluation methodology has emerged as preeminent. At least five approaches to validation are feasible. First, under some conditions, decision support system performance can be tested against a preselected gold standard. Second, real-time and historic data sets can be used for comparison with simulated output. Third, panels of experts can be judiciously used, but often are not an option in some ecological domains. Fourth, sensitivity analysis of system outputs in relation to inputs can be informative. Fifth, when validation of a complete system is impossible, examining major components can be substituted, recognizing the potential pitfalls. I provide an example of evaluation of a decision support system for trumpeter swan (Cygnus buccinator) management that I developed using interacting intelligent agents, expert systems, and a queuing system. Predicted swan distributions over a 13-year period were assessed against observed numbers. Population survey numbers and banding (ringing) studies may provide long term data useful in empirical evaluation of decision support.

The foundations of plant intelligence.

Science.gov (United States)

Trewavas, Anthony

2017-06-06

Intelligence is defined for wild plants and its role in fitness identified. Intelligent behaviour exhibited by single cells and systems similarity between the interactome and connectome indicates neural systems are not necessary for intelligent capabilities. Plants sense and respond to many environmental signals that are assessed to competitively optimize acquisition of patchily distributed resources. Situations of choice engender motivational states in goal-directed plant behaviour; consequent intelligent decisions enable efficient gain of energy over expenditure. Comparison of swarm intelligence and plant behaviour indicates the origins of plant intelligence lie in complex communication and is exemplified by cambial control of branch function. Error correction in behaviours indicates both awareness and intention as does the ability to count to five. Volatile organic compounds are used as signals in numerous plant interactions. Being complex in composition and often species and individual specific, they may represent the plant language and account for self and alien recognition between individual plants. Game theory has been used to understand competitive and cooperative interactions between plants and microbes. Some unexpected cooperative behaviour between individuals and potential aliens has emerged. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.

Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System

Directory of Open Access Journals (Sweden)

Mert Bal

2014-01-01

Full Text Available The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

Science.gov (United States)

Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

2014-01-01

The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

Large Efficient Intelligent Heating Relay Station System

Science.gov (United States)

Wu, C. Z.; Wei, X. G.; Wu, M. Q.

2017-12-01

The design of large efficient intelligent heating relay station system aims at the improvement of the existing heating system in our country, such as low heating efficiency, waste of energy and serious pollution, and the control still depends on the artificial problem. In this design, we first improve the existing plate heat exchanger. Secondly, the ATM89C51 is used to control the whole system and realize the intelligent control. The detection part is using the PT100 temperature sensor, pressure sensor, turbine flowmeter, heating temperature, detection of user end liquid flow, hydraulic, and real-time feedback, feedback signal to the microcontroller through the heating for users to adjust, realize the whole system more efficient, intelligent and energy-saving.

Microcomputer Intelligence for Technical Training (MITT): The evolution of an intelligent tutoring system

Science.gov (United States)

Norton, Jeffrey E.; Wiederholt, Bradley J.; Johnson, William B.

1990-01-01

Microcomputer Intelligence for Technical Training (MITT) uses Intelligent Tutoring System (OTS) technology to deliver diagnostic training in a variety of complex technical domains. Over the past six years, MITT technology has been used to develop training systems for nuclear power plant diesel generator diagnosis, Space Shuttle fuel cell diagnosis, and message processing diagnosis for the Minuteman missile. Presented here is an overview of the MITT system, describing the evolution of the MITT software and the benefits of using the MITT system.

Beyond IQ: A Latent State-Trait Analysis of General Intelligence, Dynamic Decision Making, and Implicit Learning

Science.gov (United States)

Danner, Daniel; Hagemann, Dirk; Schankin, Andrea; Hager, Marieke; Funke, Joachim

2011-01-01

The present study investigated cognitive performance measures beyond IQ. In particular, we investigated the psychometric properties of dynamic decision making variables and implicit learning variables and their relation with general intelligence and professional success. N = 173 employees from different companies and occupational groups completed…

Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

Science.gov (United States)

Yaratan, Huseyin

2003-01-01

An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

Intelligent interactive multimedia systems and services in practice

CERN Document Server

Virvou, Maria; Jain, Lakhmi; Howlett, Robert; Watanabe, Toyohide

2015-01-01

This research book presents some specific multimedia systems that have been developed and applied in practice. More specifically, it consists of an editorial, an introductory chapter and six chapters as below.   ·         Use of Multi-attribute Decision Making for Combining Audio-Lingual and Visual-Facial Modalities in Emotion Recognition. ·         Cooperative Learning assisted by Automatic Classification within Social Networking Services. ·         Improving Peer-to-Peer Communication in e-Learning by Development of an Advanced Messaging System. ·         Fuzzy-based Digital Video Stabilization in Static Scenes. ·         Development of Architecture, Information Archive and Multimedia Formats for Digital e-Libraries. ·         Layered Ontological Image for Intelligent Interaction to extend User Capabilities on Multimedia Systems in a Folksonomy Driven Environment.  

Using generic tool kits to build intelligent systems

Science.gov (United States)

Miller, David J.

1994-01-01

The Intelligent Systems and Robots Center at Sandia National Laboratories is developing technologies for the automation of processes associated with environmental remediation and information-driven manufacturing. These technologies, which focus on automated planning and programming and sensor-based and model-based control, are used to build intelligent systems which are able to generate plans of action, program the necessary devices, and use sensors to react to changes in the environment. By automating tasks through the use of programmable devices tied to computer models which are augmented by sensing, requirements for faster, safer, and cheaper systems are being satisfied. However, because of the need for rapid cost-effect prototyping and multi-laboratory teaming, it is also necessary to define a consistent approach to the construction of controllers for such systems. As a result, the Generic Intelligent System Controller (GISC) concept has been developed. This concept promotes the philosophy of producing generic tool kits which can be used and reused to build intelligent control systems.

An overview of artificial intelligence applications to safeguards

International Nuclear Information System (INIS)

Johnson, C.E.

1987-01-01

The rapidly growing discipline of artificial intelligence (AI) has delivered a number of expert systems that aid analyses of processes and procedures by emulating the analysis and decisions of experts. Expert systems have not reached the point of replacing experts, but can provide assistance in their absence. In narrow domains, expert systems can relieve the expert of less demanding analyses and decisions, freeing him/her for more important tasks. Safeguards experts are in great demand, and the decision processes they perform are not always well-defined. The general area of safeguards analysis is representative of the type of activity that benefits from the assistance provided by AI techniques. The American Nuclear Society is holding a topical meeting, Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry, on August 31-September 2, 1987. The technical papers cover a number of applications of potential benefit to safeguards and the safeguards interface with facility operations. This paper is a technical review of papers presented at the topical meeting

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...

Intelligent Transportation Systems : critical standards

Science.gov (United States)

1999-06-01

Intelligent Transportation Systems (ITS) standards are industry-consensus standards that provide the details about how different systems interconnect and communicate information to deliver the ITS user services described in the National ITS Architect...

A comprehensive review on intelligent surveillance systems

Directory of Open Access Journals (Sweden)

Sutrisno Warsono Ibrahim

2016-05-01

Full Text Available Intelligent surveillance system (ISS has received growing attention due to the increasing demand on security and safety. ISS is able to automatically analyze image, video, audio or other type of surveillance data without or with limited human intervention. The recent developments in sensor devices, computer vision, and machine learning have an important role in enabling such intelligent system. This paper aims to provide general overview of intelligent surveillance system and discuss some possible sensor modalities and their fusion scenarios such as visible camera (CCTV, infrared camera, thermal camera and radar. This paper also discusses main processing steps in ISS: background-foreground segmentation, object detection and classification, tracking, and behavioral analysis.

Vision Guided Intelligent Robot Design And Experiments

Science.gov (United States)

Slutzky, G. D.; Hall, E. L.

1988-02-01

The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

Determining Difficulty of Questions in Intelligent Tutoring Systems

Science.gov (United States)

Gunel, Korhan; Asliyan, Rifat

2009-01-01

The object of this study is to model the level of a question difficulty by a differential equation at a pre-specified domain knowledge, to be used in an educational support system. For this purpose, we have developed an intelligent tutoring system for mathematics education. Intelligent Tutoring Systems are computer systems designed for improvement…

Artificial Intelligent Platform as Decision Tool for Asset Management, Operations and Maintenance.

Science.gov (United States)

2018-01-04

An Artificial Intelligence (AI) system has been developed and implemented for water, wastewater and reuse plants to improve management of sensors, short and long term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it is able to simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.

A Note on Systems Intelligence in Knowledge Management

Science.gov (United States)

Sasaki, Yasuo

2017-01-01

Purpose: This paper aims to show that systems intelligence (SI) can be a useful perspective in knowledge management, particularly in the context of the socialization, externalization, combination and internalization (SECI) model. SI is a recently developed systemic concept, a certain kind of human intelligence based on a systems thinking…

An Advanced IoT-based System for Intelligent Energy Management in Buildings

Directory of Open Access Journals (Sweden)

Vangelis Marinakis

2018-02-01

Full Text Available The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to the lack of semantics. This paper presents an advanced Internet of Things (IoT based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings’ energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building’s data (e.g., energy management systems, energy production, energy prices, weather data and end-users’ behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information.

An Advanced IoT-based System for Intelligent Energy Management in Buildings.

Science.gov (United States)

Marinakis, Vangelis; Doukas, Haris

2018-02-16

The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT) solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to the lack of semantics. This paper presents an advanced Internet of Things (IoT) based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings' energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building's data (e.g., energy management systems), energy production, energy prices, weather data and end-users' behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information.

An Advanced IoT-based System for Intelligent Energy Management in Buildings

Science.gov (United States)

Doukas, Haris

2018-01-01

The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT) solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to the lack of semantics. This paper presents an advanced Internet of Things (IoT) based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings’ energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building’s data (e.g., energy management systems), energy production, energy prices, weather data and end-users’ behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information. PMID:29462957

Innovative applications of artificial intelligence

Science.gov (United States)

Schorr, Herbert; Rappaport, Alain

Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

Review of real-time on-line decision support system RODOS

International Nuclear Information System (INIS)

Rossi, J.

1997-01-01

RODOS (Real Time Off-site Decision Support System) is a research project, which aims at the development of a versatile decision support system for management of reactor accident off-site consequence assessments in real-time in Europe and in the western parts of the former Soviet Union. The system employs both local and regional environmental radiation monitoring results and meteorological forecasts by means of which the software prepares consistent predictions ranging from the release area to long distances covering all temporal phases of the accident. The data to be obtained from the environment will be processed and based on the mathematical and physical models and it will be prepared to intelligibly form about the prevalent or future environmental radiation situation. The software is intended for operative use of radiation safety authorities. Furthermore, the software is suitable for education and training of rescue field personnel. (refs.)

How to Improve Artificial Intelligence through Web

Directory of Open Access Journals (Sweden)

Adrian LUPASC

2005-10-01

Full Text Available Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers maymake their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced intoWeb Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logiclayer. The Intelligent Wireless Web’s significant potential for rapidly completing information transactions may take an important contribution toglobal worker productivity. Artificial intelligence can be defined as the study of the ways in which computers can be made to perform cognitivetasks. Examples of such tasks include understanding natural language statements, recognizing visual patterns or scenes, diagnosing diseases orillnesses, solving mathematical problems, performing financial analyses, learning new procedures for solving problems. The term expert system canbe considered to be a particular type of knowledge-based system. An expert system is a system in which the knowledge is deliberately represented“as it is”. Expert systems are applications that make decisions in real-life situations that would otherwise be performed by a human expert. They areprograms designed to mimic human performance at specialized, constrained problem-solving tasks. They are constructed as a collection of IF-THENproduction rules combined with a reasoning engine that applies those rules, either in a forward or backward direction, to specific problems.

Decision-making conflict and the neural efficiency hypothesis of intelligence: a functional near-infrared spectroscopy investigation.

Science.gov (United States)

Di Domenico, Stefano I; Rodrigo, Achala H; Ayaz, Hasan; Fournier, Marc A; Ruocco, Anthony C

2015-04-01

Research on the neural efficiency hypothesis of intelligence (NEH) has revealed that the brains of more intelligent individuals consume less energy when performing easy cognitive tasks but more energy when engaged in difficult mental operations. However, previous studies testing the NEH have relied on cognitive tasks that closely resemble psychometric tests of intelligence, potentially confounding efficiency during intelligence-test performance with neural efficiency per se. The present study sought to provide a novel test of the NEH by examining patterns of prefrontal activity while participants completed an experimental paradigm that is qualitatively distinct from the contents of psychometric tests of intelligence. Specifically, participants completed a personal decision-making task (e.g., which occupation would you prefer, dancer or chemist?) in which they made a series of forced choices according to their subjective preferences. The degree of decisional conflict (i.e., choice difficulty) between the available response options was manipulated on the basis of participants' unique preference ratings for the target stimuli, which were obtained prior to scanning. Evoked oxygenation of the prefrontal cortex was measured using 16-channel continuous-wave functional near-infrared spectroscopy. Consistent with the NEH, intelligence predicted decreased activation of the right inferior frontal gyrus (IFG) during low-conflict situations and increased activation of the right-IFG during high-conflict situations. This pattern of right-IFG activity among more intelligent individuals was complemented by faster reaction times in high-conflict situations. These results provide new support for the NEH and suggest that the neural efficiency of more intelligent individuals generalizes to the performance of cognitive tasks that are distinct from intelligence tests. Copyright © 2015 Elsevier Inc. All rights reserved.

16th International Conference on Intelligent Systems Design and Applications

CERN Document Server

Abraham, Ajith; Gamboa, Dorabela; Novais, Paulo

2017-01-01

This book comprises selected papers from the 16th International Conference on Intelligent Systems Design and Applications (ISDA’16), which was held in Porto, Portugal from December 1 to16, 2016. ISDA 2016 was jointly organized by the Portugual-based Instituto Superior de Engenharia do Porto and the US-based Machine Intelligence Research Labs (MIR Labs) to serve as a forum for the dissemination of state-of-the-art research and development of intelligent systems, intelligent technologies, and applications. The papers included address a wide variety of themes ranging from theories to applications of intelligent systems and computational intelligence area and provide a valuable resource for students and researchers in academia and industry alike. .

An Intelligent System for Aggression De-escalation Training

NARCIS (Netherlands)

Bosse, T.; Gerritsen, C.; de Man, J.

2016-01-01

Artificial Intelligence techniques are increasingly being used to develop smart training applications for professionals in various domains. This paper presents an intelligent training system that enables professionals in the public domain to practice their aggression de-escalation skills. The system

Business Intelligence Issues for Sustainability Projects

Directory of Open Access Journals (Sweden)

Mihaela Muntean

2018-01-01

Full Text Available Business intelligence (BI is an umbrella term for strategies, technologies, and information systems used by the companies to extract from large and various data, according to the value chain, relevant knowledge to support a wide range of operational, tactical, and strategic business decisions. Sustainability, as an integrated part of the corporate business, implies the integration of the new approach at all levels: business model, performance management system, business intelligence project, and data model. Both business intelligence issues presented in this paper represent the contribution of the author in modeling data for supporting further BI approaches in corporate sustainability initiatives. Multi-dimensional modeling has been used to ground the proposals and to introduce the key performance indicators. The démarche is strengthened with implementation aspects and reporting examples. More than ever, in the Big Data era, bringing together business intelligence methods and tools with corporate sustainability is recommended.

International Conference on Intelligent Technologies and Engineering System (ICITES 2012)

CERN Document Server

Huang, Yi-Cheng; Intelligent Technologies and Engineering Systems

2013-01-01

This book concentrates on intelligent technologies as it relates to engineering systems. The book covers the following topics: networking, signal processing, artificial intelligence, control and software engineering, intelligent electronic circuits and systems, communications, and materials and mechanical engineering. The book is a collection of original papers that have been reviewed by technical editors. These papers were presented at the International Conference on Intelligent Technologies and Engineering Systems, held Dec. 13-15, 2012.

Business-Intelligence-Systeme im Spannungsfeld zwischen Usability und Sicherheit

OpenAIRE

Hinck, Thorsten

2010-01-01

Business-Intelligence-Systeme stehen im Spannungsfeld zwischen Usability und Sicherheit. Die Gefahren und Sicherheitsmaßnahmen für Informationssysteme werden ermittelt und ökonomisch in Bezug zur Gebrauchstauglichkeit gesetzt. Es entsteht ein Sicherheitsprofil für Business-Intelligence-Systeme. Business-Intelligence-Systems are in tension between Usability and IT-Security. Risks and safety measures of informationsystems are defined and set in (economic) regard to Usability. A security prof...

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.

Active and intelligent packaging systems for a modern society.

Science.gov (United States)

Realini, Carolina E; Marcos, Begonya

2014-11-01

Active and intelligent packaging systems are continuously evolving in response to growing challenges from a modern society. This article reviews: (1) the different categories of active and intelligent packaging concepts and currently available commercial applications, (2) latest packaging research trends and innovations, and (3) the growth perspectives of the active and intelligent packaging market. Active packaging aiming at extending shelf life or improving safety while maintaining quality is progressing towards the incorporation of natural active agents into more sustainable packaging materials. Intelligent packaging systems which monitor the condition of the packed food or its environment are progressing towards more cost-effective, convenient and integrated systems to provide innovative packaging solutions. Market growth is expected for active packaging with leading shares for moisture absorbers, oxygen scavengers, microwave susceptors and antimicrobial packaging. The market for intelligent packaging is also promising with strong gains for time-temperature indicator labels and advancements in the integration of intelligent concepts into packaging materials. Copyright © 2014 Elsevier Ltd. All rights reserved.

Artificial Intelligence and Moral intelligence

OpenAIRE

Laura Pana

2008-01-01

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

Space applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 2: Space projects overview

Science.gov (United States)

Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

1982-01-01

Applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities, and their related ground support functions are studied so that informed decisions can be made on which aspects of ARAMIS to develop. The space project breakdowns, which are used to identify tasks ('functional elements'), are described. The study method concentrates on the production of a matrix relating space project tasks to pieces of ARAMIS.

Automated intelligent emergency assesment of GTA pipeline events

Energy Technology Data Exchange (ETDEWEB)

Asgary, Ali; Ghaffari, Alireza; Kong, Albert [University of York, Toronto, (Canada)

2010-07-01

The traditional approach used for risk assessment in pipeline operations is stochastic, using probabilities of events. This paper reports on an investigation into the deployment of an automated intelligence reasoning system used in decision support for risk assessments related to oil and gas emergencies in the Greater Toronto Area (GTA). The study evaluated the use of fuzzy interference rules encoded using JESS and fuzzy J to develop a risk assessment system. Real time data from web services such as weather, Geographic Information Systems (GIS) and Supervisory Control and Data Acquisition (SCADA) systems were used. This study took into consideration the most recent communications infrastructure and technologies, involving the most advanced human machine interface (HMI) access via hypertext transfer protocol (HTTP). This new approach will support decision making in emergency response scenarios. The study showed that the convergence of several technologies may change the automated intelligence system design paradigm.

Requirement analysis for autonomous systems and intelligent ...

African Journals Online (AJOL)

user

Danish Power System and a requirement analysis for the use of intelligent agents and ..... tries to make an optimal islanding plan at this state and tries to blackstart. ... 4 Foundation for Physical Intelligent Agents (FIPA): http://www.fipa.org ...

Active Detection for Exposing Intelligent Attacks in Control Systems

Energy Technology Data Exchange (ETDEWEB)

Weerakkody, Sean [Carnegie Mellon Univ., Pittsburgh, PA (United States); Ozel, Omur [Carnegie Mellon Univ., Pittsburgh, PA (United States); Griffioen, Paul [Carnegie Mellon Univ., Pittsburgh, PA (United States); Sinopoli, Bruno [Carnegie Mellon Univ., Pittsburgh, PA (United States)

2017-07-01

In this paper, we consider approaches for detecting integrity attacks carried out by intelligent and resourceful adversaries in control systems. Passive detection techniques are often incorporated to identify malicious behavior. Here, the defender utilizes finely-tuned algorithms to process information and make a binary decision, whether the system is healthy or under attack. We demonstrate that passive detection can be ineffective against adversaries with model knowledge and access to a set of input/output channels. We then propose active detection as a tool to detect attacks. In active detection, the defender leverages degrees of freedom he has in the system to detect the adversary. Specifically, the defender will introduce a physical secret kept hidden from the adversary, which can be utilized to authenticate the dynamics. In this regard, we carefully review two approaches for active detection: physical watermarking at the control input, and a moving target approach for generating system dynamics. We examine practical considerations for implementing these technologies and discuss future research directions.

Business Intelligence Solutions for Gaining Competitive Advantage

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available Business Intelligence is the process for increasing the competitive advantage of a company by intelligent use of available data in decision-making. Only a revolutionary Business Intelligence solution, like the proposed portal-based, can solve the complex issues faced when evaluating decision support applications and ensures the availability of any business-critical information.

A Concurrent Distributed System for Aircraft Tactical Decision Generation

Science.gov (United States)

McManus, John W.

1990-01-01

A research program investigating the use of artificial intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of a concurrent version of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS) program, a second generation TDG, is presented. Concurrent computing environments and programming approaches are discussed and the design and performance of a prototype concurrent TDG system are presented.

Decision support system for outage management and automated crew dispatch

Science.gov (United States)

Kang, Ning; Mousavi, Mirrasoul

2018-01-23

A decision support system is provided for utility operations to assist with crew dispatch and restoration activities following the occurrence of a disturbance in a multiphase power distribution network, by providing a real-time visualization of possible location(s). The system covers faults that occur on fuse-protected laterals. The system uses real-time data from intelligent electronics devices coupled with other data sources such as static feeder maps to provide a complete picture of the disturbance event, guiding the utility crew to the most probable location(s). This information is provided in real-time, reducing restoration time and avoiding more costly and laborious fault location finding practices.

Granular, soft and fuzzy approaches for intelligent systems dedicated to professor Ronald R. Yager

CERN Document Server

Filev, Dimitar; Beliakov, Gleb

2017-01-01

This book offers a comprehensive report on the state-of-the art in the broadly-intended field of “intelligent systems”. After introducing key theoretical issues, it describes a number of promising models for data and system analysis, decision making, and control. It discusses important theories, including possibility theory, the Dempster-Shafer theory, the theory of approximate reasoning, as well as computing with words, together with novel applications in various areas, such as information aggregation and fusion, linguistic data summarization, participatory learning, systems modeling, and many others. By presenting the methods in their application contexts, the book shows how granular computing, soft computing and fuzzy logic techniques can provide novel, efficient solutions to real-world problems. It is dedicated to Professor Ronald R. Yager for his great scientific and scholarly achievements, and for his long-lasting service to the fuzzy logic, and the artificial and computational intelligence communit...

A novel AIDS/HIV intelligent medical consulting system based on expert systems.

Science.gov (United States)

Ebrahimi, Alireza Pour; Toloui Ashlaghi, Abbas; Mahdavy Rad, Maryam

2013-01-01

The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV. In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stages include: Business understanding, data understanding, data preparation, modelling, evaluation and deployment. C5.0 Tree classification algorithm is used for modelling. Also, rational unified process (RUP) is used to develop the web-based medical consulting software. Stages of RUP are as follows: Inception, elaboration, construction and transition. The intelligent developed model has been used in the infrastructure of the software and based on client's inquiry and keywords related FAQs are displayed to the client, according to the rank. FAQs' ranks are gradually determined considering clients reading it. Based on displayed FAQs, test and entertainment links are also displayed. The accuracy of the AIDS/HIV intelligent web-based medical consulting system is estimated to be 78.76%. AIDS/HIV medical consulting systems have been developed using intelligent infrastructure. Being equipped with an intelligent model, providing consulting services on systematic textual data and providing side services based on client's activities causes the implemented system to be unique. The research has been approved by Iranian Ministry of Health and Medical Education for being practical.

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.

Life system modeling and intelligent computing. Pt. I. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Li, Kang; Irwin, George W. (eds.) [Belfast Queen' s Univ. (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Fei, Minrui; Jia, Li [Shanghai Univ. (China). School of Mechatronical Engineering and Automation

2010-07-01

This book is part I of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 55 papers in this volume are organized in topical sections on intelligent modeling, monitoring, and control of complex nonlinear systems; autonomy-oriented computing and intelligent agents; advanced theory and methodology in fuzzy systems and soft computing; computational intelligence in utilization of clean and renewable energy resources; intelligent modeling, control and supervision for energy saving and pollution reduction; intelligent methods in developing vehicles, engines and equipments; computational methods and intelligence in modeling genetic and biochemical networks and regulation. (orig.)

Como obter vantagem competitiva utilizando business intelligence

Directory of Open Access Journals (Sweden)

Avanilde Kemczinski

2003-06-01

Full Text Available The objective of this paper is to define Business Intelligence and to identify the information and communication technologies that support to this type of information system. A context is made about the concept and typologies of information systems (IS. Data Warehouse, Data Mart and Data Mining are the technological resources of Back-end system, used to store important data and to extract patterns of behavior and tendencies of the organizational processes. DSS (Decision Support Systems, EIS (Executive Information Systems and OLAP (On-Line Analytical Processing tools are Front-end systems for Business Intelligence solutions. Through these systems the user transforms the information in strategic knowledge for the obtaining competitive advantages.

Semantic Business Intelligence - a New Generation of Business Intelligence

Directory of Open Access Journals (Sweden)

Dinu AIRINEI

2012-01-01

Full Text Available Business Intelligence Solutions represents applications used by companies to manage process and analyze data to provide substantiated decision. In the context of Semantic Web develop-ment trend is to integrate semantic unstructured data, making business intelligence solutions to be redesigned in such a manner that can analyze, process and synthesize, in addition to traditional data and data integrated with semantic another form and structure. This invariably leads appearance of new BI solution, called Semantic Business Intelligence.

Knowledge, decision making, and uncertainty

International Nuclear Information System (INIS)

Fox, J.

1986-01-01

Artificial intelligence (AI) systems depend heavily upon the ability to make decisions. Decisions require knowledge, yet there is no knowledge-based theory of decision making. To the extent that AI uses a theory of decision-making it adopts components of the traditional statistical view in which choices are made by maximizing some function of the probabilities of decision options. A knowledge-based scheme for reasoning about uncertainty is proposed, which extends the traditional framework but is compatible with it

Techniques of artificial intelligence applied to the electric power expansion distribution system planning problem; Tecnicas de inteligencia artificial aplicadas ao problema de planejamento da expansao do sistema de distribuicao de energia eletrica

Energy Technology Data Exchange (ETDEWEB)

Froes, Salete Maria

1996-07-01

A tool named Constrained Decision Problem (CDP), which is based on Artificial Intelligence and a specific application to Distribution System Planning is described. The CDP allows multiple objective optimization that does not, necessarily, result in a single optimal solution. First, a literature review covers published works related to Artificial Intelligence applications to Electric Power Distribution Systems, emphasizing feeder restoration and reconfiguration. Some concepts related to Artificial Intelligence are described, with particular attention to Planning and to Constrained Decision Problems. Following, an Electric Power System planning model is addressed by using the CDP tool. Some case studies illustrate the Distribution Planning model, which are compared with standard optimization models. Concluding, some comments establishing the possibilities of CDP applications are followed by a view on future developments. (author)

Personalized E- learning System Based on Intelligent Agent

Science.gov (United States)

Duo, Sun; Ying, Zhou Cai

Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

Hybrid Intelligent Warning System for Boiler tube Leak Trips

Directory of Open Access Journals (Sweden)

Singh Deshvin

2017-01-01

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

Artificial intelligence in cardiology.

Science.gov (United States)

Bonderman, Diana

2017-12-01

Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

Intelligent nesting system

Directory of Open Access Journals (Sweden)

Đuričić Zoran

2003-01-01

Full Text Available The economy of the process for the manufacture of parts from sheet metal plates depends on successful solution of the process of cutting various parts from sheet metal plates. Essentially, the problem is to arrange contours within a defined space so that they take up minimal surface. When taken in this way, the considered problem assumes a more general nature; it refers to the utilization of a flat surface, and it can represent a general principle of arranging 2D contours on a certain surface. The paper presents a conceptual solution and a prototypal intelligent nesting system for optimal cutting. The problem of nesting can generally be divided into two intellectual phases: recognition and classification of shapes, and arrangement of recognized shapes on a given surface. In solving these problems, methods of artificial intelligence are applied. In the paper, trained neural network is used for recognition of shapes; on the basis of raster record of a part's drawing, it recognizes the part's shape and which class it belongs to. By means of the expert system, based on rules defined on the basis of acquisition of knowledge from manufacturing sections, as well as on the basis of certain mathematical algorithms, parts are arranged on the arrangement surface. Both systems can also work independently, having been built on the modular principle. The system uses various product models as elements of integration for the entire system. .

Intelligence systems in environmental management theory and applications

CERN Document Server

Sari, İrem

2017-01-01

This book offers a comprehensive reference guide to intelligence systems in environmental management. It provides readers with all the necessary tools for solving complex environmental problems, where classical techniques cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including ant colony, genetic algorithms, evolutionary algorithms, fuzzy multi-criteria decision making tools, particle swarm optimization, agent-based modelling, artificial neural networks, simulated annealing, Tabu search, fuzzy multi-objective optimization, fuzzy rules, support vector machines, fuzzy cognitive maps, cumulative belief degrees, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on complex environmental problems. Moreover, by extending all the main aspec...

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

2015 International Conference on Information Technology and Intelligent Transportation Systems

CERN Document Server

Jain, Lakhmi; Zhao, Xiangmo

2017-01-01

This volume includes the proceedings of the 2015 International Conference on Information Technology and Intelligent Transportation Systems (ITITS 2015) which was held in Xi’an on December 12-13, 2015. The conference provided a platform for all professionals and researchers from industry and academia to present and discuss recent advances in the field of Information Technology and Intelligent Transportation Systems. The presented information technologies are connected to intelligent transportation systems including wireless communication, computational technologies, floating car data/floating cellular data, sensing technologies, and video vehicle detection. The articles focusing on intelligent transport systems vary in the technologies applied, from basic management systems to more application systems including topics such as emergency vehicle notification systems, automatic road enforcement, collision avoidance systems and some cooperative systems. The conference hosted 12 invited speakers and over 200 part...

i-Car: An Intelligent and Interactive Interface for Driver Assistance ...

African Journals Online (AJOL)

i-Car: An Intelligent and Interactive Interface for Driver Assistance System. ... techniques with pattern recognition, feature extraction, machine learning, object recognition, ... The system uses eye closure based decision algorithm to detect driver ...

An Artificial Intelligence-Based Environment Quality Analysis System

OpenAIRE

Oprea , Mihaela; Iliadis , Lazaros

2011-01-01

Part 20: Informatics and Intelligent Systems Applications for Quality of Life information Services (ISQLIS) Workshop; International audience; The paper describes an environment quality analysis system based on a combination of some artificial intelligence techniques, artificial neural networks and rule-based expert systems. Two case studies of the system use are discussed: air pollution analysis and flood forecasting with their impact on the environment and on the population health. The syste...

Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning

Science.gov (United States)

2015-03-01

ARL-SR-0318 ● MAR 2015 US Army Research Laboratory Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated...Adaptive Intelligent Tutoring Systems for Self-Regulated Learning by Robert A Sottilare Human Research and Engineering Directorate, ARL...TITLE AND SUBTITLE Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Clinical and Business Intelligence: Why It's Important to Your Pharmacy.

Science.gov (United States)

Pinto, Brian; Fox, Brent I

2016-07-01

According to the Healthcare Information Management and Systems Society, "Clinical & Business Intelligence (C&BI) is the use and analysis of data captured in the healthcare setting to directly inform decision-making" (http://www.himss.org/library/clinical-business-intelligence). Some say that it is the right information given to the right person at the right time in the right way. No matter how you define it, the fact remains that timely access, synthesis, and visualization of clinical data have become key to how health professionals make patient care decisions and improve care delivery.

Building Explainable Artificial Intelligence Systems

National Research Council Canada - National Science Library

Core, Mark G; Lane, H. Chad; van Lent, Michael; Gomboc, Dave; Solomon, Steve; Rosenberg, Milton

2006-01-01

As artificial intelligence (AI) systems and behavior models in military simulations become increasingly complex, it has been difficult for users to understand the activities of computer-controlled entities...

Recent Advances in Intelligent Engineering Systems

CERN Document Server

Klempous, Ryszard; Araujo, Carmen

2012-01-01

This volume is a collection of 19 chapters on intelligent engineering systems written by respectable experts of the fields. The book consists of three parts. The first part is devoted to the foundational aspects of computational intelligence. It consists of 8 chapters that include studies in genetic algorithms, fuzzy logic connectives, enhanced intelligence in product models, nature-inspired optimization technologies, particle swarm optimization, evolution algorithms, model complexity of neural networks, and fitness landscape analysis. The second part contains contributions to intelligent computation in networks, presented in 5 chapters. The covered subjects include the application of self-organizing maps for early detection of denial of service attacks, combating security threats via immunity and adaptability in cognitive radio networks, novel modifications in WSN network design for improved SNR and reliability, a conceptual framework for the design of audio based cognitive infocommunication channels, and a ...

Decision making in the context of business intelligence and data quality

Directory of Open Access Journals (Sweden)

L. Marshall

2009-02-01

Full Text Available delaharper@cput.ac.za Making decisions in a business intelligence (BI environment can become extremely challenging and sometimes even impossible if the data on which the decisions are based are of poor quality. It is only possible to utilise data effectively when it is accurate, up-to-date, complete and available when needed. The BI decision makers and users are in the best position to determine the quality of the data available to them. It is important to ask the right questions of them; therefore the issues of information quality in the BI environment were established through a literature study. Information-related problems may cause supplier relationships to deteriorate, reduce internal productivity and the business' confidence in IT. Ultimately it can have implications for an organisation's ability to perform and remain competitive. The purpose of this article is aimed at identifying the underlying factors that prevent information from being easily and effectively utilised and understanding how these factors can influence the decision-making process, particularly within a BI environment. An exploratory investigation was conducted at a large retail organisation in South Africa to collect empirical data from BI users through unstructured interviews. Some of the main findings indicate specific causes that impact the decisions of BI users, including accuracy, inconsistency, understandability and availability of information. Key performance measures that are directly impacted by the quality of data on decision-making include waste, availability, sales and supplier fulfilment. The time spent on investigating and resolving data quality issues has a major impact on productivity. The importance of documentation was highlighted as an important issue that requires further investigation. The initial results indicate the value of

Monitoring and operational support on nuclear power plants using an artificial intelligence system

International Nuclear Information System (INIS)

Bianchi, P.H.; Baptista Filho, B.D.

2009-01-01

The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

Monitoring and operational support on nuclear power plants using an artificial intelligence system

Energy Technology Data Exchange (ETDEWEB)

Bianchi, Paulo H.; Baptista Filho, Benedito D., E-mail: phbianchi@gmail.co, E-mail: bdbfilho@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2009-07-01

The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

Framework for Intelligent Teaching and Training Systems -- A Study of Systems

Science.gov (United States)

Graf von Malotky, Nikolaj Troels; Martens, Alke

2016-01-01

Intelligent Tutoring System are state of the art in eLearning since the late 1980s. The earliest system have been developed in teams of psychologists and computer scientists, with the goal to investigate learning processes and, later on with the goal to intelligently support teaching and training with computers. Over the years, the eLearning hype…

Future and Feature of Intelligent Systems and Their Societies

African Journals Online (AJOL)

2012-12-01

Dec 1, 2012 ... work covered the consequences of having artificial intelligent systems with us in the near future. Keywords: intelligence, systems, artificial ... AI as science and technology to develop computers that can think and function in.

Information Security Intelligence as a Basis for Modern Information Security Management

OpenAIRE

Natalia Georgievna Miloslavskaya; Aleksandr Ivanovich Tolstoy

2013-01-01

There is a transfer from the simple Log Management Systems and SIEM systems to those supporting Information Security Intelligence (ISI). ISIe as Business Intelligence enables companies to make more informed business decisions through more effective processing of great volumes of available information concerning their IT infrastructure. The relevance of such a transition is defined. The main goal and advantage of ISI are highlighted. The basic functionality of computer-based systems for ISI ar...

Fuzzy Reasoning as a Base for Collision Avoidance Decision Support System

Directory of Open Access Journals (Sweden)

tanja brcko

2013-12-01

Full Text Available Despite the generally high qualifications of seafarers, many maritime accidents are caused by human error; such accidents include capsizing, collision, and fire, and often result in pollution. Enough concern has been generated that researchers around the world have developed the study of the human factor into an independent scientific discipline. A great deal of progress has been made, particularly in the area of artificial intelligence. But since total autonomy is not yet expedient, the decision support systems based on soft computing are proposed to support human navigators and VTS operators in times of crisis as well as during the execution of everyday tasks as a means of reducing risk levels.This paper considers a decision support system based on fuzzy logic integrated into an existing bridge collision avoidance system. The main goal is to determine the appropriate course of avoidance, using fuzzy reasoning.

Business Intelligence: Turning Knowledge into Power

Science.gov (United States)

Endsley, Krista

2009-01-01

Today, many school districts are turning to business intelligence tools to retrieve, organize, and share knowledge for faster analysis and more effective, guided decision making. Business intelligence (BI) tools are the technologies and applications that gather and report information to help an organization's leaders make better decisions. BI…

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

Directory of Open Access Journals (Sweden)

Stephen Fox

2017-06-01

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

An intelligent detecting system for permeability prediction of MBR.

Science.gov (United States)

Han, Honggui; Zhang, Shuo; Qiao, Junfei; Wang, Xiaoshuang

2018-01-01

The membrane bioreactor (MBR) has been widely used to purify wastewater in wastewater treatment plants. However, a critical difficulty of the MBR is membrane fouling. To reduce membrane fouling, in this work, an intelligent detecting system is developed to evaluate the performance of MBR by predicting the membrane permeability. This intelligent detecting system consists of two main parts. First, a soft computing method, based on the partial least squares method and the recurrent fuzzy neural network, is designed to find the nonlinear relations between the membrane permeability and the other variables. Second, a complete new platform connecting the sensors and the software is built, in order to enable the intelligent detecting system to handle complex algorithms. Finally, the simulation and experimental results demonstrate the reliability and effectiveness of the proposed intelligent detecting system, underlying the potential of this system for the online membrane permeability for detecting membrane fouling of MBR.

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...

The Intelligent Safety System: could it introduce complex computing into CANDU shutdown systems

International Nuclear Information System (INIS)

Hall, J.A.; Hinds, H.W.; Pensom, C.F.; Barker, C.J.; Jobse, A.H.

1984-07-01

The Intelligent Safety System is a computerized shutdown system being developed at the Chalk River Nuclear Laboratories (CRNL) for future CANDU nuclear reactors. It differs from current CANDU shutdown systems in both the algorithm used and the size and complexity of computers required to implement the concept. This paper provides an overview of the project, with emphasis on the computing aspects. Early in the project several needs leading to an introduction of computing complexity were identified, and a computing system that met these needs was conceived. The current work at CRNL centers on building a laboratory demonstration of the Intelligent Safety System, and evaluating the reliability and testability of the concept. Some fundamental problems must still be addressed for the Intelligent Safety System to be acceptable to a CANDU owner and to the regulatory authorities. These are also discussed along with a description of how the Intelligent Safety System might solve these problems

Cooperation and the evolution of intelligence.

Science.gov (United States)

McNally, Luke; Brown, Sam P; Jackson, Andrew L

2012-08-07

The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the 'social intelligence hypothesis'), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa.

Learning modalities in artificial intelligence systems: a framework and review

Energy Technology Data Exchange (ETDEWEB)

Araya, A A

1982-01-01

Intelligent systems should possess two fundamental capabilities: problem solving and learning. Problem solving capabilities allow an intelligent system to cope with problems in a given domain. Learning capabilities make possible for an intelligent system to improve the solution to the problems within its current reach or to cope with new problems. This paper examines research in artificial intelligence from the perspective of learning with the purpose of: 1) developing and understanding of the problem of learning from the AI point of view, and II) characterizing the current state of the art on learning in AI. 35 references.