WorldWideScience

Sample records for artificial intelligence

  1. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

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

  2. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

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

  3. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

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

  4. Artificial intelligence

    International Nuclear Information System (INIS)

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

  5. Artificial Intelligence.

    Science.gov (United States)

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

    2016-04-01

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

  6. Trends in Artificial Intelligence.

    Science.gov (United States)

    Hayes, Patrick

    1978-01-01

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

  7. Artificial intelligence

    OpenAIRE

    Duda, Antonín

    2009-01-01

    Abstract : Issue of this work is to acquaint the reader with the history of artificial inteligence, esspecialy branch of chess computing. Main attention is given to progress from fifties to the present. The work also deals with fighting chess programs against each other, and against human opponents. The greatest attention is focused on 1997 and duel Garry Kasparov against chess program Deep Blue. The work is divided into chapters according to chronological order.

  8. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

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

  9. Artificial intelligence in medicine.

    Science.gov (United States)

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

  10. Artificial intelligence in nanotechnology.

    Science.gov (United States)

    Sacha, G M; Varona, P

    2013-11-15

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

  11. Artificial intelligence in nanotechnology

    International Nuclear Information System (INIS)

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

  12. Artificial intelligence in nanotechnology

    Science.gov (United States)

    Sacha, G. M.; Varona, P.

    2013-11-01

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

  13. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

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

  14. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

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

  15. Artificial intelligence within AFSC

    Science.gov (United States)

    Gersh, Mark A.

    1990-01-01

    Information on artificial intelligence research in the Air Force Systems Command is given in viewgraph form. Specific research that is being conducted at the Rome Air Development Center, the Space Technology Center, the Human Resources Laboratory, the Armstrong Aerospace Medical Research Laboratory, the Armamant Laboratory, and the Wright Research and Development Center is noted.

  16. Instructional Applications of Artificial Intelligence.

    Science.gov (United States)

    Halff, Henry M.

    1986-01-01

    Surveys artificial intelligence and the development of computer-based tutors and speculates on the future of artificial intelligence in education. Includes discussion of the definitions of knowledge, expert systems (computer systems that solve tough technical problems), intelligent tutoring systems (ITS), and specific ITSs such as GUIDON, MYCIN,…

  17. Uncertainty in artificial intelligence

    CERN Document Server

    Kanal, LN

    1986-01-01

    How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.

  18. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2010-01-01

    Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente

  19. Soft computing in artificial intelligence

    CERN Document Server

    Matson, Eric

    2014-01-01

    This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

  20. Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

    NARCIS (Netherlands)

    van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

    2013-01-01

    The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

  1. The handbook of artificial intelligence

    CERN Document Server

    Barr, Avron

    1982-01-01

    The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine

  2. Artificial Intelligence in Civil Engineering

    Directory of Open Access Journals (Sweden)

    Pengzhen Lu

    2012-01-01

    Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

  3. Artificial Intelligence in Canada: A Review

    OpenAIRE

    Mccalla, Gordon; Cercone, Nick

    1984-01-01

    Canadians have made many contributions to artificial intelligence over the years. This article presents a summary of current research in artificial intelligence in Canada and acquaints readers with the Canadian organization for artificial intelligence -- the Canadian Society for the Computational Studies of Intelligence / Societe Canadienne pour l' Etude de l'Intelligence par Ordinateur (CSCSI/ SCEIO).

  4. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

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

  5. Artificial intelligence and intelligent tutoring systems

    Energy Technology Data Exchange (ETDEWEB)

    Livergood, N.D.

    1989-01-01

    As a species we have evolved by increasing our mental and physical powers through the deliberate development and use of instruments that amplify our inherent capabilities. Whereas hereditarily given instincts predetermine the actions of lower animal forms, human existence begins with freedom. As humans we can choose what actions we will perform. We have invented a technology called education to prepare ourselves for life. At present, our educational structures and procedures are failing to prepare us efficiently for the demands of modern life. One of the most important new technologies, in relation to human development, is the digital computer. This dissertation proposes that artificial intelligence maintain a highly critical technological awareness. Artificial intelligence, because of its origin as a politically sponsored field of investigation, must strive for constant awareness of its place within the larger political-economic world and its possible misuse by factions intent on manipulation and control. Computerized models of the human mind could be used in developing progressively more sophisticated brainwashing systems. Intelligent tutoring systems comprise an important new technology within the field of artificial intelligence. This dissertation explores specification and design procedures, functions and issues in developing intelligent tutoring systems.

  6. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

  7. Artificial Intelligence and Its Importance in Education.

    Science.gov (United States)

    Tilmann, Martha J.

    Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

  8. Progress and Challenge of Artificial Intelligence

    Institute of Scientific and Technical Information of China (English)

    Zhong-Zhi Shi; Nan-Ning Zheng

    2006-01-01

    Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

  9. Computational aerodynamics and artificial intelligence

    Science.gov (United States)

    Mehta, U. B.; Kutler, P.

    1984-01-01

    The general principles of artificial intelligence are reviewed and speculations are made concerning how knowledge based systems can accelerate the process of acquiring new knowledge in aerodynamics, how computational fluid dynamics may use expert systems, and how expert systems may speed the design and development process. In addition, the anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements for using artificial intelligence in computational fluid dynamics and aerodynamics are examined. Three main conclusions are presented. First, there are two related aspects of computational aerodynamics: reasoning and calculating. Second, a substantial portion of reasoning can be achieved with artificial intelligence. It offers the opportunity of using computers as reasoning machines to set the stage for efficient calculating. Third, expert systems are likely to be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics.

  10. A Definition of Artificial Intelligence

    OpenAIRE

    Dobrev, Dimiter

    2012-01-01

    In this paper we offer a formal definition of Artificial Intelligence and this directly gives us an algorithm for construction of this object. Really, this algorithm is useless due to the combinatory explosion. The main innovation in our definition is that it does not include the knowledge as a part of the intelligence. So according to our definition a newly born baby also is an Intellect. Here we differs with Turing's definition which suggests that an Intellect is a person with knowledge gai...

  11. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  12. Artificial Intelligence Databases: A Survey and Comparison.

    Science.gov (United States)

    Stern, David

    1990-01-01

    Identifies and describes online databases containing references to materials on artificial intelligence, robotics, and expert systems, and compares them in terms of scope and usage. Recommendations for conducting online searches on artificial intelligence and related fields are offered. (CLB)

  13. Impact of Artificial Intelligence on Economic Theory

    OpenAIRE

    Tshilidzi Marwala

    2015-01-01

    Artificial intelligence has impacted many aspects of human life. This paper studies the impact of artificial intelligence on economic theory. In particular we study the impact of artificial intelligence on the theory of bounded rationality, efficient market hypothesis and prospect theory.

  14. Artificial Intelligence Assists Ultrasonic Inspection

    Science.gov (United States)

    Schaefer, Lloyd A.; Willenberg, James D.

    1992-01-01

    Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

  15. Artificial intelligence and simulation

    Energy Technology Data Exchange (ETDEWEB)

    Holmes, W.M.

    1985-01-01

    The research and development of AI are discussed. Papers are presented on an expert system for chemical process control, an ocean surveillance information fusion expert system, a distributed intelligence system and aircraft pilotage, a procedure for speeding innovation by transferring scientific knowledge more quickly, and syntax programming, expert systems, and real-time fault diagnosis. Consideration is given to an expert system for modeling NASA flight control room usage, simulating aphasia, a method for single neuron recognition of letters, numbers, faces, and certain types of concepts, integrating AI and control system approach, testing an expert system for manufacturing, and the human memory.

  16. Uncertainty in artificial intelligence

    CERN Document Server

    Levitt, TS; Lemmer, JF; Shachter, RD

    1990-01-01

    Clearly illustrated in this volume is the current relationship between Uncertainty and AI.It has been said that research in AI revolves around five basic questions asked relative to some particular domain: What knowledge is required? How can this knowledge be acquired? How can it be represented in a system? How should this knowledge be manipulated in order to provide intelligent behavior? How can the behavior be explained? In this volume, all of these questions are addressed. From the perspective of the relationship of uncertainty to the basic questions of AI, the book divides naturally i

  17. Automated Scheduling Via Artificial Intelligence

    Science.gov (United States)

    Biefeld, Eric W.; Cooper, Lynne P.

    1991-01-01

    Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

  18. Artificial Intelligence--Applications in Education.

    Science.gov (United States)

    Poirot, James L.; Norris, Cathleen A.

    1987-01-01

    This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

  19. Of Artificial Intelligence and Legal Reasoning

    OpenAIRE

    Sunstein, Cass Robert

    2014-01-01

    Can computers, or artificial intelligence, reason by analogy? This essay urges that they cannot, because they are unable to engage in the crucial task of identifying the normative principle that links or separates cases. Current claims, about the ability of artificial intelligence to reason analogically, rest on an inadequate picture of what legal reasoning actually is. For the most part, artificial intelligence now operates as a kind of advanced version of LEXIS, offering research assistance...

  20. Artificial intelligence and science education

    Science.gov (United States)

    Good, Ron

    Artificial intelligence (AI) is defined and related to intelligent computer-assisted instruction (ICAI) and science education. Modeling the student, the teacher, and the natural environment are discussed as important parts of ICAI and the concept of microworlds as a powerful tool for science education is presented. Optimistic predictions about ICAI are tempered with the complex, persistent problems of: 1) teaching and learning as a soft or fuzzy knowledge base, 2) natural language processing, and 3) machine learning. The importance of accurate diagnosis of a student's learning state, including misconceptions and naive theories about nature, is stressed and related to the importance of accurate diagnosis by a physician. Based on the cognitive science/AI paradigm, a revised model of the well-known Karplus/Renner learning cycle is proposed.

  1. Epistasis analysis using artificial intelligence.

    Science.gov (United States)

    Moore, Jason H; Hill, Doug P

    2015-01-01

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

  2. Advanced Artificial Intelligence Technology Testbed

    Science.gov (United States)

    Anken, Craig S.

    1993-01-01

    The Advanced Artificial Intelligence Technology Testbed (AAITT) is a laboratory testbed for the design, analysis, integration, evaluation, and exercising of large-scale, complex, software systems, composed of both knowledge-based and conventional components. The AAITT assists its users in the following ways: configuring various problem-solving application suites; observing and measuring the behavior of these applications and the interactions between their constituent modules; gathering and analyzing statistics about the occurrence of key events; and flexibly and quickly altering the interaction of modules within the applications for further study.

  3. Artificial intelligence methods for diagnostic

    International Nuclear Information System (INIS)

    To assist in diagnosis of its nuclear power plants, the Research and Development Division of Electricite de France has been developing skills in Artificial Intelligence for about a decade. Different diagnostic expert systems have been designed. Among them, SILEX for control rods cabinet troubleshooting, DIVA for turbine generator diagnosis, DIAPO for reactor coolant pump diagnosis. This know how in expert knowledge modeling and acquisition is direct result of experience gained during developments and of a more general reflection on knowledge based system development. We have been able to reuse this results for other developments such as a guide for auxiliary rotating machines diagnosis. (authors)

  4. Improving designer productivity. [artificial intelligence

    Science.gov (United States)

    Hill, Gary C.

    1992-01-01

    Designer and design team productivity improves with skill, experience, and the tools available. The design process involves numerous trials and errors, analyses, refinements, and addition of details. Computerized tools have greatly speeded the analysis, and now new theories and methods, emerging under the label Artificial Intelligence (AI), are being used to automate skill and experience. These tools improve designer productivity by capturing experience, emulating recognized skillful designers, and making the essence of complex programs easier to grasp. This paper outlines the aircraft design process in today's technology and business climate, presenting some of the challenges ahead and some of the promising AI methods for meeting these challenges.

  5. Logical Foundations Of Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-04-01

    Full Text Available The procedures of searching solutions to problems, in Artificial Intelligence, can be brought about, in many occasions, without knowledge of the Domain, and in other situations, with knowledge of it. This last procedure is usually called Heuristic Search. In such methods the matrix techniques reveal themselves as essential. Their introduction can give us an easy and precise way in the search of solution. Our paper explains how the matrix theory appears and fruitfully participates in A I, with feasible applications to Game Theory.

  6. Artificial intelligence a beginner's guide

    CERN Document Server

    Whitby, Blay

    2012-01-01

    Tomorrow begins right here as we embark on an enthralling and jargon-free journey into the world of computers and the inner recesses of the human mind. Readers encounter everything from the nanotechnology used to make insect-like robots, to computers that perform surgery, in addition to discovering the biggest controversies to dog the field of AI. Blay Whitby is a Lecturer on Cognitive Science and Artificial Intelligence at the University of Sussex UK. He is the author of two books and numerous papers.

  7. Economic reasoning and artificial intelligence.

    Science.gov (United States)

    Parkes, David C; Wellman, Michael P

    2015-07-17

    The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people.

  8. Economic reasoning and artificial intelligence.

    Science.gov (United States)

    Parkes, David C; Wellman, Michael P

    2015-07-17

    The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people. PMID:26185245

  9. Artificial Intelligence in Education: An Exploration.

    Science.gov (United States)

    Cumming, Geoff

    1998-01-01

    Gives a brief outline of the development of Artificial Intelligence in Education (AIED) which includes psychology, education, cognitive science, computer science, and artificial intelligence. Highlights include learning environments; learner modeling; a situated approach to learning; and current examples of AIED research. (LRW)

  10. Contribution of artificial intelligence to operation

    International Nuclear Information System (INIS)

    Artificial Intelligence techniques are already used in nuclear plants for assistance to operation: synthesis from numerous information sources may be then derived, based on expert knowledge. Artificial intelligence may be used also for quality and reliability assessment of software-based control-command systems. Various expert systems developed by CEA, EDF and Framatome are presented

  11. A Study on Artificial Intelligence IQ and Standard Intelligent Model

    OpenAIRE

    Liu, Feng; Shi, Yong

    2015-01-01

    Currently, potential threats of artificial intelligence (AI) to human have triggered a large controversy in society, behind which, the nature of the issue is whether the artificial intelligence (AI) system can be evaluated quantitatively. This article analyzes and evaluates the challenges that the AI development level is facing, and proposes that the evaluation methods for the human intelligence test and the AI system are not uniform; and the key reason for which is that none of the models ca...

  12. 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...

  13. Artificial Intelligence Research and Development: Proc. of the 11th International Conference of the Catalan Association for Artificial Intelligence

    OpenAIRE

    Alsinet, Teresa; Puyol-Gruart, Josep; Torras, Carme

    2008-01-01

    Artificial Intelligence Research and Development. Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence. Volume 184 Frontiers in Artificial Intelligence and Applications Peer Reviewed

  14. Artificial intelligence and process management

    International Nuclear Information System (INIS)

    Techniques derived from work in artificial intelligence over the past few decades are beginning to change the approach in applying computers to process management. To explore this new approach and gain real practical experience of its potential a programme of experimental applications was initiated by Sira in collaboration with the process industry. This programme encompassed a family of experimental applications ranging from process monitoring, through supervisory control and troubleshooting to planning and scheduling. The experience gained has led to a number of conclusions regarding the present level of maturity of the technology, the potential for further developments and the measures required to secure the levels of system integrity necessary in on-line applications to critical processes. (author)

  15. Artificial intelligence in medical diagnosis.

    Science.gov (United States)

    Szolovits, P; Patil, R S; Schwartz, W B

    1988-01-01

    In an attempt to overcome limitations inherent in conventional computer-aided diagnosis, investigators have created programs that simulate expert human reasoning. Hopes that such a strategy would lead to clinically useful programs have not been fulfilled, but many of the problems impeding creation of effective artificial intelligence programs have been solved. Strategies have been developed to limit the number of hypotheses that a program must consider and to incorporate pathophysiologic reasoning. The latter innovation permits a program to analyze cases in which one disorder influences the presentation of another. Prototypes embodying such reasoning can explain their conclusions in medical terms that can be reviewed by the user. Despite these advances, further major research and developmental efforts will be necessary before expert performance by the computer becomes a reality.

  16. Text Classification using Artificial Intelligence

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Existing supervised learning algorithms for classifying text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification using artificial intelligence technique that requires fewer documents for training. Instead of using words, word relation i.e. association rules from these words is used to derive feature set from pre-classified text documents. The concept of na\\"ive Bayes classifier is then used on derived features and finally only a single concept of genetic algorithm has been added for final classification. A syste...

  17. Artificial Intelligence and Information Management

    Science.gov (United States)

    Fukumura, Teruo

    After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

  18. 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.

  19. Artificial intelligence: Learning to see and act

    Science.gov (United States)

    Schölkopf, Bernhard

    2015-02-01

    An artificial-intelligence system uses machine learning from massive training sets to teach itself to play 49 classic computer games, demonstrating that it can adapt to a variety of tasks. See Letter p.529

  20. Economic modeling using artificial intelligence methods

    CERN Document Server

    Marwala, Tshilidzi

    2013-01-01

    This book examines the application of artificial intelligence methods to model economic data. It addresses causality and proposes new frameworks for dealing with this issue. It also applies evolutionary computing to model evolving economic environments.

  1. Artificial Intelligence for Controlling Robotic Aircraft

    Science.gov (United States)

    Krishnakumar, Kalmanje

    2005-01-01

    A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

  2. 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.

  3. The Twentieth National Conference on Artificial Intelligence

    OpenAIRE

    Veloso, Manuela M.; Kambhampati, Subbarao

    2005-01-01

    The Twentieth National Conference on Artificial Intelligence was held July 9-13, 2005, in Pittsburgh, Pennsylvania. The conference, which marked the twenty-fifth anniversary of the Association for the Advancement of Artificial Intelligence (AAAI), received 803 submissions to the technical program. All papers were double-blind reviewed, and 150 papers were accepted for oral presentation, while 79 papers were accepted for poster presentation. The keynote address was delivered by Marvin Minsky.

  4. Artificial intelligence techniques for rational decision making

    CERN Document Server

    Marwala, Tshilidzi

    2014-01-01

    Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon's bounded rationality theory are flexible due to advanced signal processing techniques, Moore's Law and artificial intellig

  5. Improving Tools in Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-01-01

    Full Text Available The historical origin of the Artificial Intelligence (AI is usually established in the Dartmouth Conference, of 1956. But we can find many more arcane origins [1]. Also, we can consider, in more recent times, very great thinkers, as Janos Neumann (then, John von Neumann, arrived in USA, Norbert Wiener, Alan Mathison Turing, or Lofti Zadeh, for instance [12, 14]. Frequently AI requires Logic. But its Classical version shows too many insufficiencies. So, it was necessary to introduce more sophisticated tools, as Fuzzy Logic, Modal Logic, Non-Monotonic Logic and so on [1, 2]. Among the things that AI needs to represent are categories, objects, properties, relations between objects, situations, states, time, events, causes and effects, knowledge about knowledge, and so on. The problems in AI can be classified in two general types [3, 5], search problems and representation problems. On this last "peak", there exist different ways to reach their summit. So, we have [4] Logics, Rules, Frames, Associative Nets, Scripts, and so on, many times connected among them. We attempt, in this paper, a panoramic vision of the scope of application of such representation methods in AI. The two more disputable questions of both modern philosophy of mind and AI will be perhaps the Turing Test and the Chinese Room Argument. To elucidate these very difficult questions, see our final note.

  6. One Decade of Universal Artificial Intelligence

    CERN Document Server

    Hutter, Marcus

    2012-01-01

    The first decade of this century has seen the nascency of the first mathematical theory of general artificial intelligence. This theory of Universal Artificial Intelligence (UAI) has made significant contributions to many theoretical, philosophical, and practical AI questions. In a series of papers culminating in book (Hutter, 2005), an exciting sound and complete mathematical model for a super intelligent agent (AIXI) has been developed and rigorously analyzed. While nowadays most AI researchers avoid discussing intelligence, the award-winning PhD thesis (Legg, 2008) provided the philosophical embedding and investigated the UAI-based universal measure of rational intelligence, which is formal, objective and non-anthropocentric. Recently, effective approximations of AIXI have been derived and experimentally investigated in JAIR paper (Veness et al. 2011). This practical breakthrough has resulted in some impressive applications, finally muting earlier critique that UAI is only a theory. For the first time, wit...

  7. Performance support systems and artificial intelligent considerations

    International Nuclear Information System (INIS)

    Intelligent performance support systems (PSS) for reactor operations have been discussed, but none is operating yet. The features desired are human-centred design, intelligent behaviour, and real-time performance. PSS derive their origins from the realization that intelligent open-loop complex plant control involves consideration of the human component as well as the machine part of the system. Also , for the PSS to be effective, real-time operating capability is necessary. In this context, the present paper examines the role of artificial intelligence in PSS. 22 refs., 3 figs

  8. Artificial Intelligence Research at the Artificial Intelligence Laboratory, Massachusetts Institute of Technology

    OpenAIRE

    Winston, Patrick H.

    1983-01-01

    The primary goal of the Artificial Intelligence Laboratory is to understand how computers can be made to exhibit intelligence. Two corollary goals are to make computers more useful and to understand certain aspects of human intelligence. Current research includes work on computer robotics and vision, expert systems, learning and commonsense reasoning, natural language understanding, and computer architecture.

  9. 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.

  10. Artificial Intelligence Techniques for Steam Generator Modelling

    CERN Document Server

    Wright, Sarah

    2008-01-01

    This paper investigates the use of different Artificial Intelligence methods to predict the values of several continuous variables from a Steam Generator. The objective was to determine how the different artificial intelligence methods performed in making predictions on the given dataset. The artificial intelligence methods evaluated were Neural Networks, Support Vector Machines, and Adaptive Neuro-Fuzzy Inference Systems. The types of neural networks investigated were Multi-Layer Perceptions, and Radial Basis Function. Bayesian and committee techniques were applied to these neural networks. Each of the AI methods considered was simulated in Matlab. The results of the simulations showed that all the AI methods were capable of predicting the Steam Generator data reasonably accurately. However, the Adaptive Neuro-Fuzzy Inference system out performed the other methods in terms of accuracy and ease of implementation, while still achieving a fast execution time as well as a reasonable training time.

  11. Artificial Intelligence-The Emerging Technology

    OpenAIRE

    R.P. Shenoy

    1985-01-01

    Artificial Intelligence (AI), once considered as an obscure branch of computer science, is now having a growing number of adherents in a wide variety of fields. AI is particularly useful for combat automation in defence. The combined works of computer scientists and technologists and cognitive scientists have brought out for intelligent information processing knowledge is the key factor. In the last few years, AI has been tried out with a high degree of success in certain areas such as the Ex...

  12. Algorithms and architectures of artificial intelligence

    CERN Document Server

    Tyugu, E

    2007-01-01

    This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorithm, or when a well-defined architecture is known, e.g. in neural nets and intelligent agents. It can be used as a handbook for a wide audience of application developers who are interested in using artificial intelligence methods in their software products. Parts of the text are rather independent, so that one can look into the index and go directly to a description of a method presented in the form of an abstract algorithm or an architectural solution. The book can be used also as a textbook for a course in applied artificial intelligence. Exercises on the subject are added at the end of each chapter. Neither programming skills nor specific knowledge in computer science are expected from the reader. However, some p...

  13. Machine learning an artificial intelligence approach

    CERN Document Server

    Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

    1983-01-01

    Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

  14. Knowledge representation an approach to artificial intelligence

    CERN Document Server

    Bench-Capon, TJM

    1990-01-01

    Although many texts exist offering an introduction to artificial intelligence (AI), this book is unique in that it places an emphasis on knowledge representation (KR) concepts. It includes small-scale implementations in PROLOG to illustrate the major KR paradigms and their developments.****back cover copy:**Knowledge representation is at the heart of the artificial intelligence enterprise: anyone writing a program which seeks to work by encoding and manipulating knowledge needs to pay attention to the scheme whereby he will represent the knowledge, and to be aware of the consequences of the ch

  15. Nature inspired algorithms and artificial intelligence

    Directory of Open Access Journals (Sweden)

    Elisa Valentina Onet

    2008-05-01

    Full Text Available Artificial intelligence has been very muchinterested in studying the characteristics ofintelligent agent, mainly planning, learning,reasoning (making decisions and perception.Biological processes and methods have beeninfluencing science from many decades. Naturalsystems have many properties that inspiredapplications - self-organisation, simplicity of basicelements, dynamics, flexibility. This paper is a surveyof nature inspired algorithms, like Particle SwarmOptimization (PSO, Ant Colony Optimization (ACOand Artificial Bee Colony(ABC.

  16. Report on the 1986 Artificial Intelligence and Simulation Workshop

    OpenAIRE

    Modjeski, Richard B.

    1987-01-01

    The first Artificial Intelligence (AI) and simulation workshop was held during the National Conference on Artificial Intelligence (AAAI-86) on 11 August 1986 at Wharton Hall, the University of Pennsylvania.

  17. Abstraction in artificial intelligence and complex systems

    CERN Document Server

    Saitta, Lorenza

    2013-01-01

    Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the K

  18. Employing Artificial Intelligence To Minimise Internet Fraud

    Directory of Open Access Journals (Sweden)

    Edward Wong Sek Khin

    2009-12-01

    Full Text Available Internet fraud is increasing on a daily basis with new methods for extracting funds from government, corporations, businesses in general, and persons appearing almost hourly. The increases in on-line purchasing and the constant vigilance of both seller and buyer have meant that the criminal seems to be one-step ahead at all times. To pre-empt or to stop fraud before it can happen occurs in the non-computer based daily transactions of today because of the natural intelligence of the players, both seller and buyer. Currently, even with advances in computing techniques, intelligence is not the current strength of any computing system of today, yet techniques are available which may reduce the occurrences of fraud, and are usually referred to as artificial intelligence systems.This paper provides an overview of the use of current artificial intelligence (AI techniques as a means of combating fraud.Initially the paper describes how artificial intelligence techniques are employed in systems for detecting credit card fraud (online and offline fraud and insider trading.Following this, an attempt is made to propose the using of MonITARS (Monitoring Insider Trading and Regulatory Surveillance Systems framework which use a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing. Finally, the paper discusses future research agenda to the role of using MonITARS system.

  19. Dynamic Restructuring Of Problems In Artificial Intelligence

    Science.gov (United States)

    Schwuttke, Ursula M.

    1992-01-01

    "Dynamic tradeoff evaluation" (DTE) denotes proposed method and procedure for restructuring problem-solving strategies in artificial intelligence to satisfy need for timely responses to changing conditions. Detects situations in which optimal problem-solving strategies cannot be pursued because of real-time constraints, and effects tradeoffs among nonoptimal strategies in such way to minimize adverse effects upon performance of system.

  20. Nature inspired algorithms and artificial intelligence

    OpenAIRE

    Elisa Valentina Onet; Ecaterina Vladu

    2008-01-01

    Artificial intelligence has been very muchinterested in studying the characteristics ofintelligent agent, mainly planning, learning,reasoning (making decisions) and perception.Biological processes and methods have beeninfluencing science from many decades. Naturalsystems have many properties that inspiredapplications - self-organisation, simplicity of basicelements, dynamics, flexibility. This paper is a surveyof nature inspired algorithms, like Particle SwarmOptimization (PSO), Ant Colony Op...

  1. Artificial Intelligence Applications to Videodisc Technology

    OpenAIRE

    Vries, John K.; Banks, Gordon; McLinden, Sean; Moossy, John; Brown, Melanie

    1985-01-01

    Much of medical information is visual in nature. Since it is not easy to describe pictorial information in linguistic terms, it has been difficult to store and retrieve this type of information. Coupling videodisc technology with artificial intelligence programming techniques may provide a means for solving this problem.

  2. Algorithmic Game Theory and Artificial Intelligence

    OpenAIRE

    Elkind, Edith; Nanyang Technological University; Leyton-Brown, Kevin; University of British Columbia

    2010-01-01

    We briefly survey the rise of game theory as a topic of study in artificial intelligence, and explain the term algorithmic game theory. We then de- scribe three broad areas of current inquiry by AI researchers in algorithmic game theory: game playing, social choice, and mechanism design. Finally, we give short summaries of each of the six articles appearing in this issue.

  3. Seventh Scandinavian Conference on Artificial Intelligence

    DEFF Research Database (Denmark)

    Lund, Henrik Hautop; Mayoh, Brian Henry; Perram, John

    2001-01-01

    The book covers the seventh Scandinavian Conference on Artificial Intelligence, held at the Maersk Mc-Kinney Moller Institute for Production Technology at the University of Southern Denmark during the period 20-21 February, 2001. It continues the tradition established by SCAI of being one...

  4. The potential of artificial intelligence toys

    DEFF Research Database (Denmark)

    Dai, Zheng

    2008-01-01

    Artificial intelligence is moving to a next step of development and application areas. From electronic games to human-like robots, AI toy is a good choice for next step during this process. Technology-based design is fit to the development of AI toy. It can exert the advantages and explore more...

  5. A Starter's Guide to Artificial Intelligence.

    Science.gov (United States)

    McConnell, Barry A.; McConnell, Nancy J.

    1988-01-01

    Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

  6. Artificial Intelligence A New Synthesis

    CERN Document Server

    Nilsson, Nils J

    1998-01-01

    Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading re

  7. Artificial intelligence and information-control systems of robots - 87

    International Nuclear Information System (INIS)

    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

  8. Introducing artificial intelligence into structural optimization programs

    International Nuclear Information System (INIS)

    Artificial Intelligence /AI/ is defined as the branch of the computer science concerned with the study of the ideas that enable computers to be intelligent. The main purpose of the application of AI in engineering is to develop computer programs which function better as tools for engineers and designers. Many computer programs today have properties which make them inconvenient to their final users and the research carried within the field of AI provides tools and techniques so that these restriction can be removed. The continuous progress in computer technology has lead to developing efficient computer systems which can be applied to more than simple solving sets of equations. (orig.)

  9. Artificial intelligence and CAD/CAM

    Energy Technology Data Exchange (ETDEWEB)

    Iwata, K.

    1983-10-01

    In recent years CAD/CAM technology has improved industrial productivity. It is a significant step towards the design of the factory of the future. CAD/CAM in conjunction with artificial intelligence will become paramount. Workers in this field are attempting to produce systems of ever-increasing intelligence and independence for everyday use in factories, schools and elsewhere. A computer system which could understand natural language in both spoken and handwritten form and communicate in natural language would have considerable advantage in practical situations over one of the present generation of computers and computer programs. 2 references.

  10. Philosophy of Logic and Artificial Intelligence

    OpenAIRE

    Karavasileiadis, Christos; O'Bryan, Stephan

    2009-01-01

    For many years, scientists have been trying to implement human intelligence in machines without being able to make a complete model of human mind. Some people connect this failure to theorems proved by Kurt Gödel in 1931 and they are called Gödel’s Incompleteness Theorems. The results of Gödel’s Incompleteness Theorem caused many philosophical debates between the “believers” of Artificial Intelligence (A.I) and those who find it impossible. The purpose of this project is to examine how Gödel’...

  11. Projective simulation for artificial intelligence

    CERN Document Server

    Briegel, Hans J

    2011-01-01

    We propose a notion of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied-cognitive-science approach to intelligent action and learning. While the scheme works entirely classically, it also provides a natural route for generalization to quantum-mechanical operation.

  12. Projective simulation for artificial intelligence

    Science.gov (United States)

    Briegel, Hans J.; De las Cuevas, Gemma

    2012-01-01

    We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation. PMID:22590690

  13. Artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    The IAEA Specialists' Meeting on Artificial Intelligence in Nuclear Power Plants was arranged in Helsink/Vantaa, Finland, on October 10-12, 1989, under auspices of the International Working Group of Nuclear Power Plant Control and Instrumentation of the International Atomic Energy Agency (IAEA/IWG NPPCI). Technical Research Centre of Finland together with Imatran Voima Oy and Teollisuuden Voima Oy answered for the practical arrangements of the meeting. 105 participants from 17 countries and 2 international organizations took part in the meeting and 58 papers were submitted for presentation. These papers gave a comprehensive picture of the recent status and further trends in applying the rapidly developing techniques of artificial intelligence and expert systems to improve the quality and safety in designing and using of nuclear power worldwide

  14. Parallel processing for artificial intelligence 1

    CERN Document Server

    Kanal, LN; Kumar, V; Suttner, CB

    1994-01-01

    Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discus

  15. Empirical Methods in Artificial Intelligence: A Review

    OpenAIRE

    Langley, Pat

    1996-01-01

    Paul Cohen's book Empirical Methods for Artificial Intelligence aims to encourage this trend by providing AI practitioners with the knowledge and tools needed for careful empirical evaluation. The volume provides broad coverage of experimental design and statistics, ranging from a gentle introduction of basic ideas to a detailed presentation of advanced techniques, often combined with illustrative examples of their application to the empirical study of AI. The book is generally well written, ...

  16. Readings in artificial intelligence and software engineering

    Energy Technology Data Exchange (ETDEWEB)

    Rich, C.; Waters, R.C.

    1986-01-01

    Research at the intersection of artificial intelligence and software engineering is important to both AI researchers and software engineers. For AI, programming is a domain that stimulates research in knowledge representation and automated reasoning. In software engineering, AI techniques are being applied to a new generation of programming tools. This book covers a wide spectrum of work in this area. Some of the topics covered include deductive synthesis, program verification, and transformational approaches.

  17. Applications of artificial intelligence to scientific research

    Science.gov (United States)

    Prince, Mary Ellen

    1986-01-01

    Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

  18. Teachers and artificial intelligence. The Logo connection.

    Science.gov (United States)

    Merbler, J B

    1990-12-01

    This article describes a three-phase program for training special education teachers to teach Logo and artificial intelligence. Logo is derived from the LISP computer language and is relatively simple to learn and use, and it is argued that these factors make it an ideal tool for classroom experimentation in basic artificial intelligence concepts. The program trains teachers to develop simple demonstrations of artificial intelligence using Logo. The material that the teachers learn to teach is suitable as an advanced level topic for intermediate- through secondary-level students enrolled in computer competency or similar courses. The material emphasizes problem-solving and thinking skills using a nonverbal expressive medium (Logo), thus it is deemed especially appropriate for hearing-impaired children. It is also sufficiently challenging for academically talented children, whether hearing or deaf. Although the notion of teachers as programmers is controversial, Logo is relatively easy to learn, has direct implications for education, and has been found to be an excellent tool for empowerment-for both teachers and children.

  19. Artificial intelligence approach to legal reasoning

    International Nuclear Information System (INIS)

    For artificial intelligence, understanding the forms of human reasoning is a central goal. Legal reasoning is a form that makes a new set of demands on artificial intelligence methods. Most importantly, a computer program that reasons about legal problems must be able to distinguish between questions it is competent to answer and questions that human lawyers could seriously argue either way. In addition, a program for analyzing legal problems should be able to use both general legal rules and decisions in past cases; and it should be able to work with technical concepts that are only partly defined and subject to shifts of meaning. Each of these requirements has wider applications in artificial intelligence, beyond the legal domain. This dissertation presents a computational framework for legal reasoning, within which such requirements can be accommodated. The development of the framework draws significantly on the philosophy of law, in which the elucidation of legal reasoning is an important topic. A key element of the framework is the legal distinction between hard cases and clear cases. In legal writing, this distinction has been taken for granted more often than it has been explored. Here, some initial heuristics are proposed by which a program might make the distinction

  20. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

  1. Artificial Intelligence and Computer Assisted Instruction. CITE Report No. 4.

    Science.gov (United States)

    Elsom-Cook, Mark

    The purpose of the paper is to outline some of the major ways in which artificial intelligence research and techniques can affect usage of computers in an educational environment. The role of artificial intelligence is defined, and the difference between Computer Aided Instruction (CAI) and Intelligent Computer Aided Instruction (ICAI) is…

  2. Artificial Intelligence and Robotic From the Past to Present

    Directory of Open Access Journals (Sweden)

    Elnaz Asgarifar

    2013-04-01

    Full Text Available This paper overviews the basic principles and recent advances in the Artificial Intelligent robotics and the utilization of robots in nowadays life and the various compass. The aim of the paper is to introduce the basic concepts of artificial intelligent techniques and present a survey about robots. In first section we have a survey on the concept of artificial intelligence and intelligence life; also we introduce two important factors in artificial intelligence. In the next section, we have overview on the basic elements of artificial intelligence. Then, another important section in this paper is intelligent robots and the behavior based robotics. The use of robots in nowadays life is in the various domains. We introduce one of them that are rehabilitation robots.

  3. Non-Newtonian Aspects of Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2016-05-01

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

  4. The epistemology and information systems based on artificial intelligence

    Directory of Open Access Journals (Sweden)

    Miguel Rendueles Mata

    2011-02-01

    Full Text Available The Epistemology was been a Philosophy discipline, that takes its own autonomy from different XVII century currents. The epistemology action field considers the possibility of human intelligence representation. Because of the born of Information Systems based on Artificial Intelligence, the Epistemology is in front of a new challenge, its seems that a lot of things has to be clarify according with the advances on this area. This article reflects the problem and suggests the idea to conjugate the new advances of the epistemological tradition with the Artificial Intelligence.Key Words: Epistemology, Knowledge Theory, Ontology, Artificial Intelligence, Natural Intelligence.

  5. Artificial Intelligence-The Emerging Technology

    Directory of Open Access Journals (Sweden)

    R. P. Shenoy

    1985-04-01

    Full Text Available Artificial Intelligence (AI, once considered as an obscure branch of computer science, is now having a growing number of adherents in a wide variety of fields. AI is particularly useful for combat automation in defence. The combined works of computer scientists and technologists and cognitive scientists have brought out for intelligent information processing knowledge is the key factor. In the last few years, AI has been tried out with a high degree of success in certain areas such as the Expert Systems and the Computer Vision Systems. Both these have great potential in target classification and identification, information fusion, multiradar Air Defence Network, C2 (Command andControl operations etc. in defence.

  6. Probabilistic machine learning and artificial intelligence.

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-28

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  7. Artificial intelligence applications at the ICPP

    International Nuclear Information System (INIS)

    Westinghouse Idaho Nuclear Company (WINCO) initiated an aggressive program for artificial intelligence (AI) expert system implementations in 1985. The first expert system, Safety Analysis Methods Advisor (SAMA) was completed in 1986 to help operational safety analysts select analysis methodologies for safety analysis reports. The SAMA expert system was implemented as a rule-based system using a commercial expert system shell. The major benefit of the system is for training new safety analysts. The first successful implementation launched three other expert system projects: a process alarm filtering system, a process control advisor, and a mass spectrometer trouble-shooting advisor. This paper describes the current status of these projects

  8. Probabilistic machine learning and artificial intelligence

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-01

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  9. Beyond Artificial Intelligence toward Engineered Psychology

    Science.gov (United States)

    Bozinovski, Stevo; Bozinovska, Liljana

    This paper addresses the field of Artificial Intelligence, road it went so far and possible road it should go. The paper was invited by the Conference of IT Revolutions 2008, and discusses some issues not emphasized in AI trajectory so far. The recommendations are that the main focus should be personalities rather than programs or agents, that genetic environment should be introduced in reasoning about personalities, and that limbic system should be studied and modeled. Engineered Psychology is proposed as a road to go. Need for basic principles in psychology are discussed and a mathematical equation is proposed as fundamental law of engineered and human psychology.

  10. 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

  11. Parallel processing for artificial intelligence 2

    CERN Document Server

    Kumar, V; Suttner, CB

    1994-01-01

    With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy. This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their

  12. A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

    Directory of Open Access Journals (Sweden)

    Jeremy Straub

    2013-05-01

    Full Text Available An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response, this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.

  13. Computer science, artificial intelligence, and cybernetics: Applied artificial intelligence in Japan

    Energy Technology Data Exchange (ETDEWEB)

    Rubinger, B.

    1988-01-01

    This sourcebook provides information on the developments in artificial intelligence originating in Japan. Spanning such innovations as software productivity, natural language processing, CAD, and parallel inference machines, this volume lists leading organizations conducting research or implementing AI systems, describes AI applications being pursued, illustrates current results achieved, and highlights sources reporting progress.

  14. A Progress Report on Artificial Intelligence: Hospital Applications and a Review of the Artificial Intelligence Marketplace

    OpenAIRE

    Brenkus, Lawrence M.

    1984-01-01

    Artificial intelligence applications are finally beginning to move from the university research laboratory into commercial use. Before the end of the century, this new computer technology will have profound effects on our work, economy, and lives. At present, relatively few products have appeared in the hospital, but we can anticipate significant product offerings in instrumentation and affecting hospital administration within 5 years.

  15. Artificial intelligence model for sustain ability measurement

    International Nuclear Information System (INIS)

    The article analyses the main dimensions of organizational sustain ability, their possible integrations into artificial neural network. In this article authors performing analyses of organizational internal and external environments, their possible correlations with 4 components of sustain ability, and the principal determination models for sustain ability of organizations. Based on the general principles of sustainable development organizations, a artificial intelligence model for the determination of organizational sustain ability has been developed. The use of self-organizing neural networks allows the identification of the organizational sustain ability and the endeavour to explore vital, social, antropogenical and economical efficiency. The determination of the forest enterprise sustain ability is expected to help better manage the sustain ability. (Authors)

  16. Artificial Intelligence Research Branch future plans

    Science.gov (United States)

    Stewart, Helen (Editor)

    1992-01-01

    This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems.

  17. Artificial intelligence. Fears of an AI pioneer.

    Science.gov (United States)

    Russell, Stuart; Bohannon, John

    2015-07-17

    From the enraged robots in the 1920 play R.U.R. to the homicidal computer H.A.L. in 2001: A Space Odyssey, science fiction writers have embraced the dark side of artificial intelligence (AI) ever since the concept entered our collective imagination. Sluggish progress in AI research, especially during the “AI winter” of the 1970s and 1980s, made such worries seem far-fetched. But recent breakthroughs in machine learning and vast improvements in computational power have brought a flood of research funding— and fresh concerns about where AI may lead us. One researcher now speaking up is Stuart Russell, a computer scientist at the University of California, Berkeley, who with Peter Norvig, director of research at Google, wrote the premier AI textbook, Artificial Intelligence: A Modern Approach, now in its third edition. Last year, Russell joined the Centre for the Study of Existential Risk at Cambridge University in the United Kingdom as an AI expert focusing on “risks that could lead to human extinction.” Among his chief concerns, which he aired at an April meeting in Geneva, Switzerland, run by the United Nations, is the danger of putting military drones and weaponry under the full control of AI systems. This interview has been edited for clarity and brevity.

  18. Marine litter prediction by artificial intelligence

    International Nuclear Information System (INIS)

    Artificial intelligence techniques of neural network and fuzzy systems were applied as alternative methods to determine beach litter grading, based on litter surveys of the Antalya coastline (the Turkish Riviera). Litter measurements were categorized and assessed by artificial intelligence techniques, which lead to a new litter categorization system. The constructed neural network satisfactorily predicted the grading of the Antalya beaches and litter categories based on the number of litter items in the general litter category. It has been concluded that, neural networks could be used for high-speed predictions of litter items and beach grading, when the characteristics of the main litter category was determined by field studies. This can save on field effort when fast and reliable estimations of litter categories are required for management or research studies of beaches--especially those concerned with health and safety, and it has economic implications. The main advantages in using fuzzy systems are that they consider linguistic adjectival definitions, e.g. many/few, etc. As a result, additional information inherent in linguistic comments/refinements and judgments made during field studies can be incorporated in grading systems

  19. Research in artificial intelligence for nuclear facilities

    International Nuclear Information System (INIS)

    The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, artificial intelligence can increase efficiency and effectiveness in a large number of nonoperating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) and in research facility experiments. Recent work at the University of Tennessee has demonstrated the feasibility of using neural networks to identify six different transients introduced into the simulation of a steam generator of a nuclear power plant. This work is now being extended to utilize data from a nuclear power plant training simulator. In one configuration, the inputs to the neural network are a subset of the quantities that are typical of those available from the safety parameter display system. The outputs of the network represent the various states of the plant (e.g., normal operation, coolant leakage, inadequate core flow, excessive peak fuel temperature, etc.). Training of the neural network is performed by introducing various faults or conditions to be diagnosed into the simulator. The goal of this work is to demonstrate a neural network diagnostic system that could provide advice to the operators in accordance with the emergency operating procedures

  20. Artificial intelligence approaches to software engineering

    Science.gov (United States)

    Johannes, James D.; Macdonald, James R.

    1988-01-01

    Artificial intelligence approaches to software engineering are examined. The software development life cycle is a sequence of not so well-defined phases. Improved techniques for developing systems have been formulated over the past 15 years, but pressure continues to attempt to reduce current costs. Software development technology seems to be standing still. The primary objective of the knowledge-based approach to software development presented in this paper is to avoid problem areas that lead to schedule slippages, cost overruns, or software products that fall short of their desired goals. Identifying and resolving software problems early, often in the phase in which they first occur, has been shown to contribute significantly to reducing risks in software development. Software development is not a mechanical process but a basic human activity. It requires clear thinking, work, and rework to be successful. The artificial intelligence approaches to software engineering presented support the software development life cycle through the use of software development techniques and methodologies in terms of changing current practices and methods. These should be replaced by better techniques that that improve the process of of software development and the quality of the resulting products. The software development process can be structured into well-defined steps, of which the interfaces are standardized, supported and checked by automated procedures that provide error detection, production of the documentation and ultimately support the actual design of complex programs.

  1. New Imaginaries of the Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Stefano Bory

    2016-03-01

    Full Text Available The paper aims to investigate the relationship between the artificial intelligence as narrated by science fiction movies in the late five decades and the socio-technical imaginary related to intelligent systems.The first sci-fi movies in analysis shed away from the idea of a symbiotic interaction between humans and AI as forecast during the 1960s by informatics and AI scientists. Afterwards, from the 1970s to the 1990s, AI systems played mainly the role of mirrors for the crisis of human identity: in these narratives the AI is presented as a risk, a possible enemy for human kind. Finally, during the last twenty years, a new frontier of AI seems to emerge in the imaginary. More recent stories forecast a future in which intelligent systems try to take their own place in the human social environment.All these perspectives emerge in conjunction with innovations and technical experimentations, bringing back up the relationship between “legein” and “teukein” as theorized by Cornelius Castoriadis.

  2. Applications of artificial intelligence, including expert systems

    International Nuclear Information System (INIS)

    When Artificial Intelligence is applied to a complex physical system like a nuclear plant it is useful to distinguish between two rather distinct and different intelligent views of such a plant. The first view may be characterised as ''the designer's view''. This is the view of the plant as it was originally conceived and designed; it is essentially a once-and-for-all static view, corresponding to the implicit assumption of an ''ageless plant'', or at most a plant which ages in a preconceived, preset manner. The second view, which may be characterised as ''the operators view'', has to do more with a real-world, ageing plant. It is a more dynamic view, which sees the ageing process as one in which unforeseen, and possibly unforeseeable events may occur at equally unforeseen, and possibly unforeseeable times. The first view is predominantly a way of thinking about the plant, while the second is very often more a way of feeling about it. It should be emphasized that both ways are ways of intelligence. (author)

  3. The 1993 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1993-01-01

    This publication comprises the papers presented at the 1993 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, MD on May 10-13, 1993. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  4. The 1994 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1994-01-01

    This publication comprises the papers presented at the 1994 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/GSFC, Greenbelt, Maryland, on 10-12 May 1994. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  5. The Potential of Artificial Intelligence in Aids for the Disabled.

    Science.gov (United States)

    Boyer, John J.

    The paper explores the possibilities for applying the knowledge of artificial intelligence (AI) research to aids for the disabled. Following a definition of artificial intelligence, the paper reviews areas of basic AI research, such as computer vision, machine learning, and planning and problem solving. Among application areas relevant to the…

  6. The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

    Science.gov (United States)

    Colombano, Silvano

    2000-01-01

    There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

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

    Science.gov (United States)

    Rash, James L. (Editor)

    1990-01-01

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

  8. Artificial Intelligence – Making an Intelligent personal assistant

    Directory of Open Access Journals (Sweden)

    Mr. Ankush Bhatia

    2015-12-01

    Full Text Available A bot in computing is an autonomous program on a network (especially the Internet which can interact with systems or users.[ Simpson, J., and Weiner, E. (1989] This document gives the description of how memory of an Artificial-Intelligence bot can be stored in an optimized way with a faster searching algorithm and how it can learn new things; the user wants the bot to learn. This paper gives the details of how a bot uses a an ordered tree data structure, called TRIE or a prefix tree to dynamically store the things it learns and what to reply when a person commands asks him something, with a little modification.

  9. Artificial Intelligence In Computational Fluid Dynamics

    Science.gov (United States)

    Vogel, Alison Andrews

    1991-01-01

    Paper compares four first-generation artificial-intelligence (Al) software systems for computational fluid dynamics. Includes: Expert Cooling Fan Design System (EXFAN), PAN AIR Knowledge System (PAKS), grid-adaptation program MITOSIS, and Expert Zonal Grid Generation (EZGrid). Focuses on knowledge-based ("expert") software systems. Analyzes intended tasks, kinds of knowledge possessed, magnitude of effort required to codify knowledge, how quickly constructed, performances, and return on investment. On basis of comparison, concludes Al most successful when applied to well-formulated problems solved by classifying or selecting preenumerated solutions. In contrast, application of Al to poorly understood or poorly formulated problems generally results in long development time and large investment of effort, with no guarantee of success.

  10. Artificial Intelligence Software Engineering (AISE) model

    Science.gov (United States)

    Kiss, Peter A.

    1990-01-01

    The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

  11. Artificial intelligence in the materials processing laboratory

    Science.gov (United States)

    Workman, Gary L.; Kaukler, William F.

    1990-01-01

    Materials science and engineering provides a vast arena for applications of artificial intelligence. Advanced materials research is an area in which challenging requirements confront the researcher, from the drawing board through production and into service. Advanced techniques results in the development of new materials for specialized applications. Hand-in-hand with these new materials are also requirements for state-of-the-art inspection methods to determine the integrity or fitness for service of structures fabricated from these materials. Two problems of current interest to the Materials Processing Laboratory at UAH are an expert system to assist in eddy current inspection of graphite epoxy components for aerospace and an expert system to assist in the design of superalloys for high temperature applications. Each project requires a different approach to reach the defined goals. Results to date are described for the eddy current analysis, but only the original concepts and approaches considered are given for the expert system to design superalloys.

  12. Artificial intelligence in process design and operation

    International Nuclear Information System (INIS)

    Artificial Intelligence (AI) has recently become prominent in the discussion of computer applications in the utility business. In order to assess this technology, a research project was performed to determine whether software development techniques based on AI could be used to facilitate management of information associated with the design of a generating station. The approach taken was the development of an expert system, using a relatively simple set of rules acting on a more complex knowledge base. A successful prototype for the application was developed and its potential extension to a production environment demonstrated. During the course of prototype development, other possible applications of AI in design engineering were discovered, and areas of particular interest selected for further investigation. A plan for AI R and D was formulated. That plan and other possible future work in AI are discussed

  13. Issues and challenges in artificial intelligence

    CERN Document Server

    Kulikowski, Juliusz; Mroczek, Teresa; Wtorek, Jerzy

    2014-01-01

    The importance of human-computer system interaction problems is increasing due to the growing expectations of users on general computer systems capabilities in human work and life facilitation. Users expect system which is not only a passive tool in human hands but rather an active partner equipped with a sort of artificial intelligence, having access to large information resources, being able to adapt its behavior to the human requirements and to collaborate with the human users.   This book collects examples of recent human-computer system solutions. The content of the book is divided into three parts. Part I is devoted to detection, recognition and reasoning in different circumstances and applications. Problems associated with data modeling, acquisition and mining are presented by papers collected in part II and part III is devoted to Optimization.

  14. Amplify scientific discovery with artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Gil, Yolanda; Greaves, Mark T.; Hendler, James; Hirsch, Hyam

    2014-10-10

    Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automated language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.

  15. Virtual Enterprise Risk Management Using Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Hanning Chen

    2010-01-01

    Full Text Available Virtual enterprise (VE has to manage its risk effectively in order to guarantee the profit. However, restricting the risk in a VE to the acceptable level is considered difficult due to the agility and diversity of its distributed characteristics. First, in this paper, an optimization model for VE risk management based on distributed decision making model is introduced. This optimization model has two levels, namely, the top model and the base model, which describe the decision processes of the owner and the partners of the VE, respectively. In order to solve the proposed model effectively, this work then applies two powerful artificial intelligence optimization techniques known as evolutionary algorithms (EA and swarm intelligence (SI. Experiments present comparative studies on the VE risk management problem for one EA and three state-of-the-art SI algorithms. All of the algorithms are evaluated against a test scenario, in which the VE is constructed by one owner and different partners. The simulation results show that the PS2O algorithm, which is a recently developed SI paradigm simulating symbiotic coevolution behavior in nature, obtains the superior solution for VE risk management problem than the other algorithms in terms of optimization accuracy and computation robustness.

  16. WEEDS IDENTIFICATION USING EVOLUTIONARY ARTIFICIAL INTELLIGENCE ALGORITHM

    Directory of Open Access Journals (Sweden)

    Ahmed M. Tobal

    2014-01-01

    Full Text Available In a world reached a population of six billion humans increasingly demand it for food, feed with a water shortage and the decline of agricultural land and the deterioration of the climate needs 1.5 billion hectares of agricultural land and in case of failure to combat pests needs about 4 billion hectares. Weeds represent 34% of the whole pests while insects, diseases and the deterioration of agricultural land present the remaining percentage. Weeds Identification has been one of the most interesting classification problems for Artificial Intelligence (AI and image processing. The most common case is to identify weeds within the field as they reduce the productivity and harm the existing crops. Success in this area results in an increased productivity, profitability and at the same time decreases the cost of operation. On the other hand, when AI algorithms combined with appropriate imagery tools may present the right solution to the weed identification problem. In this study, we introduce an evolutionary artificial neural network to minimize the time of classification training and minimize the error through the optimization of the neuron parameters by means of a genetic algorithm. The genetic algorithm, with its global search capability, finds the optimum histogram vectors used for network training and target testing through a fitness measure that reflects the result accuracy and avoids the trial-and-error process of estimating the network inputs according to the histogram data.

  17. Beyond AI: Interdisciplinary Aspects of Artificial Intelligence

    CERN Document Server

    Romportl, Jan; Zackova, Eva; Beyond Artificial Intelligence : Contemplations, Expectations, Applications

    2013-01-01

    Products of modern artificial intelligence (AI) have mostly been formed by the views, opinions and goals of the “insiders”, i.e. people usually with engineering background who are driven by the force that can be metaphorically described as the pursuit of the craft of Hephaestus. However, since the present-day technology allows for tighter and tighter mergence of the “natural” everyday human life with machines of immense complexity, the responsible reaction of the scientific community should be based on cautious reflection of what really lies beyond AI, i.e. on the frontiers where the tumultuous ever-growing and ever-changing cloud of AI touches the rest of the world.   The chapters of this boo are based on the selected subset of the presentations that were delivered by their respective authors at the conference “Beyond AI: Interdisciplinary Aspects of Artificial Intelligence” held in Pilsen in December 2011.   From its very definition, the reflection of the phenomena that lie beyond AI must be i...

  18. The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

    OpenAIRE

    Augusto, Juan Carlos; Shapiro, Daniel

    2007-01-01

    The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

  19. Use of artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, there are a large number of non-operating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) in which artificial intelligence can increase the efficiency and effectiveness of overall plant and corporate operations. This paper reviews the state-of-the-art of artificial intelligence techniques, specifically, expert systems and neural networks, to nuclear power plants. This paper has reviewed the state-of-the-art of artificial intelligence, specifically expert systems and neural networks that are applied to problems in nuclear power plants

  20. The National Artificial Intelligence Research And Development Strategic Plan

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — Executive Summary: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential...

  1. Researches in Artificial Intelligence in Republic of Moldova

    Directory of Open Access Journals (Sweden)

    Yu. Pechersky

    1994-11-01

    Full Text Available The article presents a review of researches in the field of Artificial Intelligence in Republic of Moldova concerning pattern recognition and also theory and applications of intellectual knowledge based systems.

  2. Artificial Intelligence Research in Engineering at North Carolina State University

    OpenAIRE

    Rasdorf, William J.; Fisher, Edward L.

    1985-01-01

    This article presents a summary of ongoing, funded artificial intelligence research at North Carolina State University. The primary focus of the research is engineering aspects of artificial intelligence. These research efforts can be categorized into four main areas: engineering expert systems, generative database management systems, human-machine communication, and robotics and vision. Involved in the research are investigators from both the School of Engineering and the Department of Compu...

  3. The Role of Artificial Intelligence Technologies in Crisis Response

    CERN Document Server

    Khalil, Khaled M; Nazmy, Taymour T; Salem, Abdel-Badeeh M

    2008-01-01

    Crisis response poses many of the most difficult information technology in crisis management. It requires information and communication-intensive efforts, utilized for reducing uncertainty, calculating and comparing costs and benefits, and managing resources in a fashion beyond those regularly available to handle routine problems. In this paper, we explore the benefits of artificial intelligence technologies in crisis response. This paper discusses the role of artificial intelligence technologies; namely, robotics, ontology and semantic web, and multi-agent systems in crisis response.

  4. Artificial intelligence applications in information and communication technologies

    CERN Document Server

    Bouguila, Nizar

    2015-01-01

    This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

  5. Using artificial intelligence to automate remittance processing.

    Science.gov (United States)

    Adams, W T; Snow, G M; Helmick, P M

    1998-06-01

    The consolidated business office of the Allegheny Health Education Research Foundation (AHERF), a large integrated healthcare system based in Pittsburgh, Pennsylvania, sought to improve its cash-related business office activities by implementing an automated remittance processing system that uses artificial intelligence. The goal was to create a completely automated system whereby all monies it processed would be tracked, automatically posted, analyzed, monitored, controlled, and reconciled through a central database. Using a phased approach, the automated payment system has become the central repository for all of the remittances for seven of the hospitals in the AHERF system and has allowed for the complete integration of these hospitals' existing billing systems, document imaging system, and intranet, as well as the new automated payment posting, and electronic cash tracking and reconciling systems. For such new technology, which is designed to bring about major change, factors contributing to the project's success were adequate planning, clearly articulated objectives, marketing, end-user acceptance, and post-implementation plan revision.

  6. Computational neuroscience for advancing artificial intelligence

    Directory of Open Access Journals (Sweden)

    Fernando P. Ponce

    2011-07-01

    Full Text Available resumen del libro de Alonso, E. y Mondragón, E. (2011. Hershey, NY: Medical Information Science Reference. La neurociencia como disciplinapersigue el entendimiento del cerebro y su relación con el funcionamiento de la mente a través del análisis de la comprensión de la interacción de diversos procesos físicos, químicos y biológicos (Bassett & Gazzaniga, 2011. Por otra parte, numerosas disciplinasprogresivamente han realizado significativas contribuciones en esta empresa tales como la matemática, la psicología o la filosofía, entre otras. Producto de este esfuerzo, es que junto con la neurociencia tradicional han aparecido disciplinas complementarias como la neurociencia cognitiva, la neuropsicología o la neurocienciacomputacional (Bengio, 2007; Dayan & Abbott, 2005. En el contexto de la neurociencia computacional como disciplina complementaria a laneurociencia tradicional. Alonso y Mondragón (2011 editan el libroComputacional Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications.

  7. Using artificial intelligence to automate remittance processing.

    Science.gov (United States)

    Adams, W T; Snow, G M; Helmick, P M

    1998-06-01

    The consolidated business office of the Allegheny Health Education Research Foundation (AHERF), a large integrated healthcare system based in Pittsburgh, Pennsylvania, sought to improve its cash-related business office activities by implementing an automated remittance processing system that uses artificial intelligence. The goal was to create a completely automated system whereby all monies it processed would be tracked, automatically posted, analyzed, monitored, controlled, and reconciled through a central database. Using a phased approach, the automated payment system has become the central repository for all of the remittances for seven of the hospitals in the AHERF system and has allowed for the complete integration of these hospitals' existing billing systems, document imaging system, and intranet, as well as the new automated payment posting, and electronic cash tracking and reconciling systems. For such new technology, which is designed to bring about major change, factors contributing to the project's success were adequate planning, clearly articulated objectives, marketing, end-user acceptance, and post-implementation plan revision. PMID:10179973

  8. Vibration energy harvester optimization using artificial intelligence

    Science.gov (United States)

    Hadas, Z.; Ondrusek, C.; Kurfurst, J.; Singule, V.

    2011-06-01

    This paper deals with an optimization study of a vibration energy harvester. This harvester can be used as autonomous source of electrical energy for remote or wireless applications, which are placed in environment excited by ambient mechanical vibrations. The ambient energy of vibrations is usually on very low level but the harvester can be used as alternative source of energy for electronic devices with an expected low level of power consumption of several mW. The optimized design of the vibration energy harvester was based on previous development and the sensitivity of harvester design was improved for effective harvesting from mechanical vibrations in aeronautic applications. The vibration energy harvester is a mechatronic system which generates electrical energy from ambient vibrations due to precision tuning up generator parameters. The optimization study for maximization of harvested power or minimization of volume and weight are the main goals of our development. The optimization study of such complex device is complicated therefore artificial intelligence methods can be used for tuning up optimal harvester parameters.

  9. Interactive Video and Artificial Intelligence: A Convenient Marriage.

    Science.gov (United States)

    Midoro, V.; And Others

    1988-01-01

    Describes the theoretical framework of a research project aimed at exploring the new potentials for instructional systems offered by videodisc technology and artificial intelligence. A prototype of an intelligent tutoring system, "Earth," is described, and types of interactions in instructional systems are discussed as they relate to the learning…

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

    Science.gov (United States)

    Salem, Abdel-Badeeh M.

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

  11. Applications of Artificial Intelligence in Education--A Personal View.

    Science.gov (United States)

    Richer, Mark H.

    1985-01-01

    Discusses: how artificial intelligence (AI) can advance education; if the future of software lies in AI; the roots of intelligent computer-assisted instruction; protocol analysis; reactive environments; LOGO programming language; student modeling and coaching; and knowledge-based instructional programs. Numerous examples of AI programs are cited.…

  12. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  13. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  14. Artificial intelligence and nuclear power. Report by the Technology Transfer Artificial Intelligence Task Team

    International Nuclear Information System (INIS)

    The Artificial Intelligence Task Team was organized to review the status of Artificial Intelligence (AI) technology, identify guidelines for AI work, and to identify work required to allow the nuclear industry to realize maximum benefit from this technology. The state of the nuclear industry was analyzed to determine where the application of AI technology could be of greatest benefit. Guidelines and criteria were established to focus on those particular problem areas where AI could provide the highest possible payoff to the industry. Information was collected from government, academic, and private organizations. Very little AI work is now being done to specifically support the nuclear industry. The AI Task Team determined that the establishment of a Strategic Automation Initiative (SAI) and the expansion of the DOE Technology Transfer program would ensure that AI technology could be used to develop software for the nuclear industry that would have substantial financial payoff to the industry. The SAI includes both long and short term phases. The short-term phase includes projects which would demonstrate that AI can be applied to the nuclear industry safely, and with substantial financial benefit. The long term phase includes projects which would develop AI technologies with specific applicability to the nuclear industry that would not be developed by people working in any other industry

  15. Artificial intelligence for the CTA Observatory scheduler

    Science.gov (United States)

    Colomé, Josep; Colomer, Pau; Campreciós, Jordi; Coiffard, Thierry; de Oña, Emma; Pedaletti, Giovanna; Torres, Diego F.; Garcia-Piquer, Alvaro

    2014-08-01

    The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint

  16. Artificial intelligence and robot responsibilities: innovating beyond rights.

    Science.gov (United States)

    Ashrafian, Hutan

    2015-04-01

    The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals may be considered. At a practical level, the attainment of responsibilities by artificial intelligence and robots can benefit from the established responsibilities and duties of human society, as their subsistence exists within this domain. These responsibilities can be further interpreted and crystalized through legal principles, many of which have been conserved from ancient Roman law. The ultimate and unified goal of stipulating these responsibilities resides through the advancement of mankind and the enduring preservation of the core tenets of humanity.

  17. A review of European applications of artificial intelligence to space

    Science.gov (United States)

    Drummond, Mark (Editor); Stewart, Helen (Editor)

    1993-01-01

    The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.

  18. Artificial intelligence tool development and applications to nuclear power

    International Nuclear Information System (INIS)

    Two parallel efforts are being performed at the Electric Power Research Institute (EPRI) to help the electric utility industry take advantage of the expert system technology. The first effort is the development of expert system building tools, which are tailored to electric utility industry applications. The second effort is the development of expert system applications. These two efforts complement each other. The application development tests the tools and identifies additional tool capabilities that are required. The tool development helps define the applications that can be successfully developed. Artificial intelligence, as demonstrated by the developments described is being established as a credible technological tool for the electric utility industry. The challenge to transferring artificial intelligence technology and an understanding of its potential to the electric utility industry is to gain an understanding of the problems that reduce power plant performance and identify which can be successfully addressed using artificial intelligence

  19. Distributed computing and artificial intelligence : 10th International Conference

    CERN Document Server

    Neves, José; Rodriguez, Juan; Santana, Juan; Gonzalez, Sara

    2013-01-01

    The International Symposium on Distributed Computing and Artificial Intelligence 2013 (DCAI 2013) is a forum in which applications of innovative techniques for solving complex problems are presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. This conference is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and industry se...

  20. A PHILOSOPHICAL APPROACH TO ARTIFICIAL INTELLIGENCE AND ISLAMIC VALUES

    Directory of Open Access Journals (Sweden)

    Ali Akbar Ziaee

    2012-02-01

    Full Text Available Artificial Intelligence has the potential to empower humans through enhanced learning and performance. But if this potential is to be realized and accepted, the ethical aspects as well as the technical must be addressed. Many engineers claim that AI will be smarter than human brains, including scientific creativity, general wisdom and social skills, so we must consider it an important factor for making decisions in our social life and especially in our Islamic societies. The most important challenges will be the quality of representing the Islamic values like piety, obedience, Halal and Haram, and etc in the form of semantics. In this paper, I want to emphasize on the role of Divine Islamic values in the application of AI and discuss it according to philosophy of AI and Islamic perspective.Keywords- Value, expert, Community Development, Artificial Intelligence, Superintelligence, Friendly Artificial Intelligence

  1. 9th International conference on distributed computing and artificial intelligence

    CERN Document Server

    Santana, Juan; González, Sara; Molina, Jose; Bernardos, Ana; Rodríguez, Juan; DCAI 2012; International Symposium on Distributed Computing and Artificial Intelligence 2012

    2012-01-01

    The International Symposium on Distributed Computing and Artificial Intelligence 2012 (DCAI 2012) is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. This conference is a forum in which  applications of innovative techniques for solving complex problems will be presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and indus...

  2. The Coming of Age of Artificial Intelligence in Medicine*

    Science.gov (United States)

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-01-01

    Summary This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the discussants reflect on medical AI research during the subsequent years and attempt to characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems. PMID:18790621

  3. Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

    OpenAIRE

    Lima, Pedro U.; Custodio, Luis M. M.

    2004-01-01

    This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior T?cnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are test...

  4. Bionics: A Step toward Artificial Intelligence Systems

    Science.gov (United States)

    Dutton, Robert E.

    1970-01-01

    Recent developments and future prospects in the borrowing of biological principles to build problem solving relationships between human intelligence and the information storage and manipulation capacities of computers. Twenty-one references. (LY)

  5. Cryptic Mining in Light of Artificial Intelligence

    OpenAIRE

    Shaligram Prajapat; Aditi Thakur; Kajol Maheshwari; Ramjeevan Singh Thakur

    2015-01-01

    “The analysis of cryptic text is hard problem”, and there is no fixed algorithm for generating plain-text from cipher text. Human brains do this intelligently. The intelligent cryptic analysis process needs learning algorithms, co-operative effort of cryptanalyst and mechanism of knowledge based inference engine. This information of knowledge base will be useful for mining data(plain-text, key or cipher text plain-text relationships), classification of cipher text based on enciphering algorit...

  6. Distributed Computing and Artificial Intelligence, 12th International Conference

    CERN Document Server

    Malluhi, Qutaibah; Gonzalez, Sara; Bocewicz, Grzegorz; Bucciarelli, Edgardo; Giulioni, Gianfranco; Iqba, Farkhund

    2015-01-01

    The 12th International Symposium on Distributed Computing and Artificial Intelligence 2015 (DCAI 2015) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Osaka Institute of Technology, Qatar University and the University of Salamanca.

  7. APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1988-01-01

    A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

  8. A Multidisciplinary Artificial Intelligence Model of an Affective Robot

    OpenAIRE

    Hooman Aghaebrahimi Samani; Elham Saadatian

    2012-01-01

    A multidisciplinary approach to a novel artificial intelligence system for an affective robot is presented in this paper. The general objective of the system is to develop a robotic system which strives to achieve a high level of emotional bond between humans and robot by exploring human love. Such a relationship is a contingent process of attraction, affection and attachment from humans towards robots, and the belief of the vice versa from robots to humans. The advanced artificial intelli...

  9. SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2015-12-01

    Full Text Available The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to prepare investment strategies on the stock exchange market.

  10. Artificial Life of Soybean Plant Growth Modeling Using Intelligence Approaches

    OpenAIRE

    Atris Suyantohadi; Mochamad Hariadi; Mauridhi Hery Purnomo

    2010-01-01

    The natural process on plant growth system has a complex system and it has could be developed on characteristic studied using intelligent approaches conducting with artificial life system. The approaches on examining the natural process on soybean (Glycine Max L.Merr) plant growth have been analyzed and synthesized in these research through modeling using Artificial Neural Network (ANN) and Lindenmayer System (L-System) methods. Research aimed to design and to visualize plant growth modeling...

  11. Solving Complex Logistics Problems with Multi-Artificial Intelligent System

    Directory of Open Access Journals (Sweden)

    Y.K. Tse

    2009-10-01

    Full Text Available The economy, which has become more information intensive, more global and more technologically dependent, is undergoing dramatic changes. The role of logistics is also becoming more and more important. In logistics, the objective of service providers is to fulfill all customers? demands while adapting to the dynamic changes of logistics networks so as to achieve a higher degree of customer satisfaction and therefore a higher return on investment. In order to provide high quality service, knowledge and information sharing among departments becomes a must in this fast changing market environment. In particular, artificial intelligence (AI technologies have achieved significant attention for enhancing the agility of supply chain management, as well as logistics operations. In this research, a multi-artificial intelligence system, named Integrated Intelligent Logistics System (IILS is proposed. The objective of IILS is to provide quality logistics solutions to achieve high levels of service performance in the logistics industry. The new feature of this agile intelligence system is characterized by the incorporation of intelligence modules through the capabilities of the case-based reasoning, multi-agent, fuzzy logic and artificial neural networks, achieving the optimization of the performance of organizations.

  12. Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

    Science.gov (United States)

    Burford, Anna M.; Wilson, Harold O.

    This paper addresses the characteristics and applications of artificial intelligence (AI) as a subsection of computer science, and briefly describes the most common types of AI programs: expert systems, natural language, and neural networks. Following a brief presentation of the historical background, the discussion turns to an explanation of how…

  13. Artificial Intelligence: Is the Future Now for A.I.?

    Science.gov (United States)

    Ramaswami, Rama

    2009-01-01

    In education, artificial intelligence (AI) has not made much headway. In the one area where it would seem poised to lend the most benefit--assessment--the reliance on standardized tests, intensified by the demands of the No Child Left Behind Act of 2001, which holds schools accountable for whether students pass statewide exams, precludes its use.…

  14. An Artificial Intelligence Approach to Transient Stability Assessment

    OpenAIRE

    Akella, Vijay Ahaskar; Khincha, HP; Kumar, Sreerama R

    1991-01-01

    An artificial intelligence approach to online transient stability assessment is briefly discussed, and some crucial requirements for this algorithm are identified. Solutions to these are proposed. Some new attributes are suggested so as to reflect machine dynamics and changes in the network. Also a new representative learning set algorithm has been developed.

  15. Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

    Science.gov (United States)

    Sunal, Cynthia Szymanski; Karr, Charles L.; Smith, Coralee; Sunal, Dennis W.

    2003-01-01

    Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

  16. The 1992 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1992-01-01

    The purpose of this conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers fall into the following areas: planning and scheduling, control, fault monitoring/diagnosis and recovery, information management, tools, neural networks, and miscellaneous applications.

  17. Research Priorities for Robust and Beneficial Artificial Intelligence

    OpenAIRE

    Russell, Stuart; University of California, Berkeley; Dewey, Daniel; Oxford University; Tegmark, Max; Massachusetts Institute of Technology

    2016-01-01

    Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.

  18. Artificial Intelligence: Realizing the Ultimate Promises of Computing

    OpenAIRE

    Waltz, David L.

    1997-01-01

    Artificial intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades.

  19. Magical Stories: Blending Virtual Reality and Artificial Intelligence.

    Science.gov (United States)

    McLellan, Hilary

    Artificial intelligence (AI) techniques and virtual reality (VR) make possible powerful interactive stories, and this paper focuses on examples of virtual characters in three dimensional (3-D) worlds. Waldern, a virtual reality game designer, has theorized about and implemented software design of virtual teammates and opponents that incorporate AI…

  20. Evolution and Revolution in Artificial Intelligence in Education

    Science.gov (United States)

    Roll, Ido; Wylie, Ruth

    2016-01-01

    The field of Artificial Intelligence in Education (AIED) has undergone significant developments over the last twenty-five years. As we reflect on our past and shape our future, we ask two main questions: What are our major strengths? And, what new opportunities lay on the horizon? We analyse 47 papers from three years in the history of the…

  1. Interaction between Software Engineering and Artificial Intelligence- A Review

    Directory of Open Access Journals (Sweden)

    Prince Jain

    2011-12-01

    Full Text Available Software engineering and artificial intelligence is the two field of the computer science. During the last decades, the disciplines of Artificial Intelligence and Software Engineering have developedseparately without the much exchange of research outcomes. However, both fields of computer science have different characteristics, benefits and limitations. This statement opens many possibilities and ideas for research. One idea is that the researcher applies the available methods, tools and techniques of Artificial Intelligence to Software Engineering and Software Engineering to Artificial Intelligence in a manner that good things, feature, characteristic and advantages of the both fields is taken up, and the limitations will reduces. During applicability, an intersection area is found between AI and SE, which forms the relation between AI and SE. The work in this paper discusses the factor that come while communicating between AI and SE such as Communication, objective, Problem and reasons for adopting. This work explores the framework of interaction on which both fields are communicate with each other. This framework has four major classes of interaction such as software support environment, AI tools and techniques in conventional software, Use of conventional software technology and Methodological considerations. This paper introduces the relation between AI and SE, and varioustechniques evolved while merging.

  2. An Artificial Intelligence-Based Distance Education System: Artimat

    Science.gov (United States)

    Nabiyev, Vasif; Karal, Hasan; Arslan, Selahattin; Erumit, Ali Kursat; Cebi, Ayca

    2013-01-01

    The purpose of this study is to evaluate the artificial intelligence-based distance education system called ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed…

  3. Some Notes About Artificial Intelligence as New Mathematical Tool

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-04-01

    Full Text Available Mathematics is a mere instance of First-Order Predicate Calculus. Therefore it belongs to applied Monotonic Logic. So, we found the limitations of classical logic reasoning and the clear advantages of Fuzzy Logic and many other new interesting tools. We present here some of the more usefulness tools of this new field of Mathematics so-called Artificial Intelligence.

  4. Artificial Intelligence and the High School Computer Curriculum.

    Science.gov (United States)

    Dillon, Richard W.

    1993-01-01

    Describes a four-part curriculum that can serve as a model for incorporating artificial intelligence (AI) into the high school computer curriculum. The model includes examining questions fundamental to AI, creating and designing an expert system, language processing, and creating programs that integrate machine vision with robotics and…

  5. Neuroscientific implications for situated and embodied artificial intelligence

    Science.gov (United States)

    Downing, Keith

    2007-03-01

    While classic artificial intelligence systems still struggle to incorporate commonsense knowledge properly, situated and embodied artificial intelligence (SEAI) aims to build animats that acquire a common-sense understanding of the world via interactions between simulated brains, bodies and environments. Neuroscientists believe that much of this common sense involves predictive models for physical activities, but the transfer of sensorimotor skill knowledge to cognition is non-trivial, indicating that SEAI may meet a daunting challenge of its own. This paper considers the neurological bases for implicit procedural and explicit declarative common sense, and the possibilities for its transfer from the former to the latter. This helps assess the prospects for SEAI eventually to surpass GOFAI (good old-fashioned AI) in the quest for generally intelligent systems.

  6. Artificial intelligence in a mission operations and satellite test environment

    Science.gov (United States)

    Busse, Carl

    1988-01-01

    A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.

  7. Managing a High Speed LAN using Distributed Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Ibrahiem M. M-El-Emary

    2006-01-01

    Full Text Available This study is concerned with a practical application of distributed artificial intelligence for managing the high data rate bus structured local area computer network that uses deterministic multiple access protocol. In the selected network that is managed using distributed artificial intelligence, the dynamic sharing of the available bandwidth among stations is achieved by forming "train to which each station may append a packet after issuing a reservation. Reservation and packet transmissions are governed by the reception of control packets (token issued by the network end stations. Managing approach that was suggested depends on using intelligent autonomous agents, which are responsible for various tasks among it: election of the end stations, the recovery from failures, and the insertion of new stations in the network. All these tasks are based on the use of special tokens.

  8. Performance evaluation of artificial intelligence classifiers for the medical domain.

    Science.gov (United States)

    Smith, A E; Nugent, C D; McClean, S I

    2002-01-01

    The application of artificial intelligence systems is still not widespread in the medical field, however there is an increasing necessity for these to handle the surfeit of information available. One drawback to their implementation is the lack of criteria or guidelines for the evaluation of these systems. This is the primary issue in their acceptability to clinicians, who require them for decision support and therefore need evidence that these systems meet the special safety-critical requirements of the domain. This paper shows evidence that the most prevalent form of intelligent system, neural networks, is generally not being evaluated rigorously regarding classification precision. A taxonomy of the types of evaluation tests that can be carried out, to gauge inherent performance of the outputs of intelligent systems has been assembled, and the results of this presented in a clear and concise form, which should be applicable to all intelligent classifiers for medicine.

  9. Autonomous operations through onboard artificial intelligence

    Science.gov (United States)

    Sherwood, R. L.; Chien, S.; Castano, R.; Rabideau, G.

    2002-01-01

    The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

  10. Artificial intelligence in nuclear reactor operation

    International Nuclear Information System (INIS)

    Assessment of four real fuzzy control applications at the MIT research reactor in the US, the FUGEN heavy water reactor in Japan, the BR1 research reactor in Belgium, and a TRIGA Mark III reactor in Mexico will be examined through a SWOT analysis (strengths, weakness, opportunities, and threats). Special attention will be paid to the current cooperation between the Belgian Nuclear Research Centre (SCK·CEN) and the Mexican Nuclear Centre (ININ) on AI-based intelligent control for nuclear reactor operation under the partial support of the National Council for Science and Technology of Mexico (CONACYT). (authors)

  11. Artificial organic networks artificial intelligence based on carbon networks

    CERN Document Server

    Ponce-Espinosa, Hiram; Molina, Arturo

    2014-01-01

    This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: ·        approximation; ·        inference; ·        clustering; ·        control; ·        class...

  12. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  13. Philosophy and Theory of Artificial Intelligence

    CERN Document Server

    2013-01-01

    Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we s...

  14. Learning comunication strategies for distributed artificial intelligence

    Science.gov (United States)

    Kinney, Michael; Tsatsoulis, Costas

    1992-08-01

    We present a methodology that allows collections of intelligent system to automatically learn communication strategies, so that they can exchange information and coordinate their problem solving activity. In our methodology communication between agents is determined by the agents themselves, which consider the progress of their individual problem solving activities compared to the communication needs of their surrounding agents. Through learning, communication lines between agents might be established or disconnected, communication frequencies modified, and the system can also react to dynamic changes in the environment that might force agents to cease to exist or to be added. We have established dynamic, quantitative measures of the usefulness of a fact, the cost of a fact, the work load of an agent, and the selfishness of an agent (a measure indicating an agent's preference between transmitting information versus performing individual problem solving), and use these values to adapt the communication between intelligent agents. In this paper we present the theoretical foundations of our work together with experimental results and performance statistics of networks of agents involved in cooperative problem solving activities.

  15. Cryptic Mining in Light of Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Shaligram Prajapat

    2015-08-01

    Full Text Available “The analysis of cryptic text is hard problem”, and there is no fixed algorithm for generating plain-text from cipher text. Human brains do this intelligently. The intelligent cryptic analysis process needs learning algorithms, co-operative effort of cryptanalyst and mechanism of knowledge based inference engine. This information of knowledge base will be useful for mining data(plain-text, key or cipher text plain-text relationships, classification of cipher text based on enciphering algorithms, key length or any other desirable parameters, clustering of cipher text based on similarity and extracting association rules for identifying weaknesses of cryptic algorithms. This categorization will be useful for placing given cipher text into a specific category or solving difficult level of cipher text-plain text conversion process. This paper elucidates cipher text-plain text process first than utilizes it to create a framework for AI-enabled-Cryptanalysis system. The process demonstrated in this paper attempts to analyze captured cipher from scratch. The system design elements presented in the paper gives all hints and guidelines for development of AI enabled Cryptic analysis tool.

  16. An application of artificial intelligence theory to reconfigurable flight control

    Science.gov (United States)

    Handelman, David A.

    1987-01-01

    Artificial intelligence techniques were used along with statistical hpyothesis testing and modern control theory, to help the pilot cope with the issues of information, knowledge, and capability in the event of a failure. An intelligent flight control system is being developed which utilizes knowledge of cause and effect relationships between all aircraft components. It will screen the information available to the pilots, supplement his knowledge, and most importantly, utilize the remaining flight capability of the aircraft following a failure. The list of failure types the control system will accommodate includes sensor failures, actuator failures, and structural failures.

  17. Application of Artificial Intelligence and Data Mining Techniques to Financial Markets

    OpenAIRE

    Katarína Hilovska; Peter Koncz

    2012-01-01

    The aim of artificial intelligence is to discover mechanisms of adaptation in a changing environment with utilisation of intelligence, for instance in the ability to exclude unlikely solutions. Artificial intelligence methods have extensive application in different fields such as medicine, games, transportation, or heavy industry. This paper deals with interdisciplinary issues – interconnection of artificial intelligence and finance. The paper briefly describes techniques of data mining, expe...

  18. Providing Language Instructor with Artificial Intelligence Assistant

    Directory of Open Access Journals (Sweden)

    K. Pietroszek

    2007-12-01

    Full Text Available Abstract—This paper presents the preliminary results ofdeveloping HAL for CALL, an artificial intelligenceassistant for language instructor. The assistant consists of achatbot, an avatar (a three-dimensional visualization of thechatbot, a voice (text-to-speech engine interface andinterfaces to external sources of language knowledge. Sometechniques used in adapting freely available chatbot for theneed of a language learning system are presented.Integration of HAL with Second Life virtual world isproposed. We will discuss technical challenges and possiblefuture work directions.

  19. Artificial Intelligence based technique for BTS placement

    Science.gov (United States)

    Alenoghena, C. O.; Emagbetere, J. O.; Aibinu, A. M.

    2013-12-01

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out.

  20. Artificial Intelligence based technique for BTS placement

    International Nuclear Information System (INIS)

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out

  1. Dynamic Analysis of Emotions through Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Susana Mejía M.

    2016-04-01

    Full Text Available Emotions have been demonstrated to be an important aspect of human intelligence and to play a significant role in human decision-making processes. Emotions are not only feelings but also processes of establishing, maintaining or disrupting the relation between the organism and the environment. In the present paper, several features of social and developmental Psychology are introduced, especially concepts that are related to Theories of Emotions and the Mathematical Tools applied in psychology (i.e., Dynamic Systems and Fuzzy Logic. Later, five models that infer emotions from a single event, in AV-Space, are presented and discussed along with the finding that fuzzy logic can measure human emotional states

  2. A psychoanalyst artificial intelligence model in a computer game

    OpenAIRE

    Muñoz Fernández, Enrique

    2012-01-01

    Projecte realitzat en el marc d'un programa de mobilitat amb la Vienna University of Technology. [ANGLÈS] Implementation of an artificial intelligence model based on the psychoanalytic theory of the ID-Ego-SuperEgo of Sigmund Freud into the computer game Unreal Tournament 2004. [CASTELLÀ] Implementación de un modelo de inteligencia artificial basado en la teoría psicoanalítica del ID-Ego-SuperEgo de Sigmund Freud en el videojuego Unreal Tournament 2004. [CATALÀ] Implementació d'un mo...

  3. Use of Artificial Intelligence in Real Property Valuation

    Directory of Open Access Journals (Sweden)

    Dr. N. B. Chaphalkar

    2013-06-01

    Full Text Available Real properties possess value which is dependent on numerous factors. Investors and owners of the property are interested in the maximum returns, it would fetch. Considering the amount of money involved in real estate, there is a need of accurate prediction of returns and associated risks. This necessitates use of Artificial Intelligence (AI prediction models. This study attempts to analyze and summarize AI techniques, which gives insight to application of various techniques for prediction related to property valuation. Comparison of various techniques shows that Artificial Neural Network (ANNand fuzzy logic are better suited if attributes and model parameters are appropriately selected.

  4. Brown's transport up to third order aberration by artificial intelligence

    International Nuclear Information System (INIS)

    Brown's TRANSPORT is a first and second order matrix multiplication computer program intended for the design of accelerator beam transport systems, neglecting the third order aberration. Recently a new method was developed to derive analytically any order aberration coefficients of general charged particle optic system, applicable to any practical systems, such as accelerators, electron microscopes, lithographs, including those unknown systems yet to be invented. An artificial intelligence program in Turbo Prolog was implemented on IBM-PC 286 or 386 machine to generate automatically the analytical expression of any order aberration coefficients of general charged particle optic system. Based on this new method and technique, Brown's TRANSPORT is extended beyond the second order aberration effect by artificial intelligence, outputting automatically all the analytical expressions up to the third order aberration coefficients

  5. Research on artificial intelligence systems for nuclear installations

    International Nuclear Information System (INIS)

    The development and utilization of atomic energy in Japan has be advanced in conformity with the long term plan of atomic energy development and utilization decided in 1987. As one of the basic targets, the upbringing of creative and innovative science and technology is put up. Artificial intelligence technology has been positioned as one of the important basic technologies for promoting future atomic energy development. The research and development of artificial intelligence technology have been advanced aiming at making nuclear power stations autonomous, by the guidance of Science and Technology Agency and the cooperation of several research institutes. The upbringing of creative science and technology, the preponderant development of basic technology, the concept of developing the basic technology for atomic energy, the concept of autonomous plants, the standard for autonomy, the approach to autonomous plants, the present state of the researches in respective research institutes on autonomous operation and autonomous maintenance are described. (K.I.)

  6. 11th International Conference on Distributed Computing and Artificial Intelligence

    CERN Document Server

    Bersini, Hugues; Corchado, Juan; Rodríguez, Sara; Pawlewski, Paweł; Bucciarelli, Edgardo

    2014-01-01

    The 11th International Symposium on Distributed Computing and Artificial Intelligence 2014 (DCAI 2014) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This year’s technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research (Algeria, Brazil, China, Croatia, Czech Republic, Denmark, France, Germany, Ireland, Italy, Japan, Malaysia, Mexico, Poland, Portugal, Republic of Korea, Spain, Taiwan, Tunisia, Ukraine, United Kingdom), representing ...

  7. Artificial Intelligence Application in Power Generation Industry: Initial considerations

    Science.gov (United States)

    Ismail, Rahmat Izaizi B.; Ismail Alnaimi, Firas B.; AL-Qrimli, Haidar F.

    2016-03-01

    With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.

  8. Evaluation of Artificial Intelligence Based Models for Chemical Biodegradability Prediction

    Directory of Open Access Journals (Sweden)

    Aleksandar Sabljic

    2004-12-01

    Full Text Available This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.

  9. Future of artificial intelligence -- Art, not Science

    CERN Document Server

    Kupervasser, Oleg

    2011-01-01

    Now in the world the technologies relating to design of systems of artificial intellect (AI) actively develop. In this paper it would be desirable to consider not tactical, but strategic problems of this process. Now not many interesting papers on this topic are available, but they exist [1]. It is relating to a fact that most of serious experts is occupied by a solution of tactical problems and often does not think about farther prospects. However the situation at the beginning of cybernetics origin was not that. Then these problems were actively considered. Therefore we will construct our paper as a review of problems of cybernetics as they saw to participants of the symposium in 1961 [2]. We will try to give the review of these prospects from the point of view of the up-to-date physical and cybernetic science and its last reachings.

  10. Real-Time Connect 4 Game Using Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Ahmad M. Sarhan

    2009-01-01

    Full Text Available Problem statement: The study presented a design that converted connect 4 game into a real-time game by incorporating time restraints. Approach: The design used Artificial Intelligence (AI in implementing the connect 4 game. The AI for this game was based on influence mapping. Results: A waterfall-based AI software was developed for a Connect 4 game. Conclusion: A real time connect 4 game was successfully designed and implanted with GUI using C++ programming language.

  11. [I, Robot: artificial intelligence, uniqueness and self-consciousness].

    Science.gov (United States)

    Agrest, Martín

    2008-01-01

    The cinematographic version of the science fiction classical book by Isaac Asimov (I, Robot) is used as a starting point, from the Artificial Intelligence perspective, in order to analyze what it is to have a self. Uniqueness or the exchange impossibility and the continuity of being one self are put forward to understand the movie's characters as well as the possibilities of feeling self conscious.

  12. Application of artificial intelligence to improve aircraft survivability

    OpenAIRE

    Decker, William Leecraft

    1985-01-01

    Approved for public release; distribution is unlimited The hazards associated with the critical flight phases of civil as well as military flight operations can seriously degrade pilot efficiency, and therefore aircraft survivability, if the number or complexity of tasks that the pilot must manage exceeds his/her capabilities. This thesis explores the feasibility of applying artificial intelligence (AI) research to the construction of a Survivability Manager (SM) knowledge based system (K...

  13. Artificial intelligence techniques for industrial applications in job shop scheduling.

    OpenAIRE

    Townsend, Wade Benton

    1983-01-01

    The application of AI (artificial intelligence) techniques to the scheduling of industrial production operations offers a promising new approach to a scheduling problem of great magnitude and complexity. Foremost among these techniques is a powerful knowledge representation language that is capable of modeling the production environment at all levels of detail. The capturing of such complexity in the data base enables the computer to generate feasible schedules from a very large solution spac...

  14. Meaning of cognitive processes for creating artificial intelligence

    OpenAIRE

    Smutný, Zdeněk

    2009-01-01

    This diploma thesis brings an integral view at cognitive processes connected with artificial intelligence systems, and makes a comparison with the processes observed in nature, including human being. A historical background helps us to look at the whole issue from a certain point of view. The main axis of interest comes after the historical overview and includes the following: environment -- stimulations -- processing -- reflection in the cognitive system -- reaction to stimulation; I balance...

  15. Analysis of dynamic conflicts by techniques of artificial intelligence

    OpenAIRE

    Shinar, Josef

    1989-01-01

    Dynamic conflicts exhibit differentiel game characteristics and their analysis by any method which disregards this feature may be, by definition, futile. Unfortunately, realistic conflicts may have an intricate information structure and a complex hierarchy which don't fit in the classical differential game formulation. Moreover, in many cases even well formulated differential games are not solvable. In the recent years great progress has been made in artificial intelligence techniques, put in...

  16. Artificial intelligence issues related to automated computing operations

    Science.gov (United States)

    Hornfeck, William A.

    1989-01-01

    Large data processing installations represent target systems for effective applications of artificial intelligence (AI) constructs. The system organization of a large data processing facility at the NASA Marshall Space Flight Center is presented. The methodology and the issues which are related to AI application to automated operations within a large-scale computing facility are described. Problems to be addressed and initial goals are outlined.

  17. An Artificial Intelligence Environment for Information Retrieval Research

    OpenAIRE

    France, Robert K.; Edward A Fox

    1988-01-01

    The CODER (COmposite Document Expert/Extended/Effective Retrieval) project is a multi-year effort to investigate how best to apply artificial intelligence methods to increase the effectiveness of information retrieval systems. Particular attention is being given to analysis and representation of heterogeneous documents, such as electronic mail digests or messages, which vary widely in style, length, topic,and structure. In order to ensure system adaptability and to allow reconfiguration for c...

  18. The 1991 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1991-01-01

    The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in this proceeding fall into the following areas: Planning and scheduling, fault monitoring/diagnosis/recovery, machine vision, robotics, system development, information management, knowledge acquisition and representation, distributed systems, tools, neural networks, and miscellaneous applications.

  19. Experiments with microcomputer-based artificial intelligence environments

    Science.gov (United States)

    Summers, E.G.; MacDonald, R.A.

    1988-01-01

    The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

  20. A Survey of Artificial Intelligence Research at the IIIA

    OpenAIRE

    Lopez de Mantaras, Ramon; Spanish Council for Scientific Research (CSIC)

    2014-01-01

    The IIIA is a public research centre, belonging to the Spanish National Research Council (CSIC), dedicated to AI research. We focus our activities on a few well-defined sub-domains of Artificial Intelligence, positively avoiding dispersion and keeping a good balance between basic research and applications, and paying particular attention to training PhD students and technology transfer. In this article, we survey some of the most relevant results we have obtained during the last 12 years.

  1. The Innovative Applications of Artificial Intelligence Conference: Past and Future

    OpenAIRE

    Shrobe, Howard

    1996-01-01

    This article is a reflection on the goals and focus of the Innovative Applications of Artificial Intelligence (IAAI) Conference. The author begins with an historical review of the conference. He then goes on to discuss the role of the IAAI conference, including an examination of the relationship between AI scientific research and the application of AI technology. He concludes with a presentation of the new vision for the IAAI conference.

  2. The Dartmouth College Artificial Intelligence Conference: The Next Fifty Years

    OpenAIRE

    Moor, James

    2006-01-01

    The Dartmouth College Artificial Intelligence Conference: The Next 50 Years (AI@50) took place July 13-15, 2006. The conference had three objectives: to celebrate the Dartmouth Summer Research Project, which occurred in 1956; to assess how far AI has progressed; and to project where AI is going or should be going. AI@50 was generously funded by the office of the Dean of Faculty and the office of the Provost at Dartmouth College, by DARPA, and by some private donors.

  3. Artificial intelligence and virtual environment application for materials design methodology

    OpenAIRE

    L.A. Dobrzański; R. Honysz

    2010-01-01

    Purpose: The purpose of this study is to develop a methodology for material design, enabling the selection of the chemical elements concentration, heat and plastic treatment conditions and geometrical dimensions to ensure the required mechanical properties of structural steels specified by the designer of machinery and equipment as the basis for the design of material components manufactured from these steels, by using a computational model developed with use of artificial intelligence method...

  4. Application of artificial intelligence techniques to TRR operation

    International Nuclear Information System (INIS)

    It has been over ten years since TRR had its initial critical. To collect the experiences of shift operators and technique staffs and transfer these experts' knowledge to a computer and build an expert system is a typical application of artificial intelligence techniques to nuclear business. The system can provide the correct information of TRR operation for shift personnel, new staffs and other technical people

  5. Artificial intelligence, expert systems, computer vision, and natural language processing

    Science.gov (United States)

    Gevarter, W. B.

    1984-01-01

    An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

  6. An Artificial Intelligence-Based Distance Education System: Artimat

    OpenAIRE

    NABIYEV, Vasif; Karal, Hasan; Arslan, Selahattin; ERUMIT, Ali Kürsat; Ayça CEBI

    2013-01-01

    The purpose of this study is to evaluate the artificial intelligence-based distance education system called as ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed with 4 teachers and 59 students in 10th grade in an Anatolian High School in Trabzon. Many institutions and organizations in the world approach...

  7. Experiments with microcomputer-based artificial intelligence environments

    Energy Technology Data Exchange (ETDEWEB)

    Summers, E.G.; MacDonald, R.A.

    1988-11-01

    The US Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the artificial intelligence computer, and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Golf Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming.

  8. Artificial intelligence and dynamic systems for geophysical applications

    CERN Document Server

    Gvishiani, Alexei

    2002-01-01

    The book presents new clustering schemes, dynamical systems and pattern recognition algorithms in geophysical, geodynamical and natural hazard applications. The original mathematical technique is based on both classical and fuzzy sets models. Geophysical and natural hazard applications are mostly original. However, the artificial intelligence technique described in the book can be applied far beyond the limits of Earth science applications. The book is intended for research scientists, tutors, graduate students, scientists in geophysics and engineers

  9. Artificial intelligence programming languages for computer aided manufacturing

    Science.gov (United States)

    Rieger, C.; Samet, H.; Rosenberg, J.

    1979-01-01

    Eight Artificial Intelligence programming languages (SAIL, LISP, MICROPLANNER, CONNIVER, MLISP, POP-2, AL, and QLISP) are presented and surveyed, with examples of their use in an automated shop environment. Control structures are compared, and distinctive features of each language are highlighted. A simple programming task is used to illustrate programs in SAIL, LISP, MICROPLANNER, and CONNIVER. The report assumes reader knowledge of programming concepts, but not necessarily of the languages surveyed.

  10. Artificial Intelligence in Video Games: Towards a Unified Framework

    OpenAIRE

    Safadi, Firas

    2015-01-01

    The work presented in this dissertation revolves around the problem of designing artificial intelligence (AI) for video games. This problem becomes increasingly challenging as video games grow in complexity. With modern video games frequently featuring sophisticated and realistic environments, the need for smart and comprehensive agents that understand the various aspects of these environments is pressing. Although machine learning techniques are being successfully applied in a multitude of d...

  11. Application of artificial intelligence to triple quadrupole mass spectrometry (TQMS)

    International Nuclear Information System (INIS)

    At Lawrence Livermore National Laboratory the authors have designed a totally computerized triple quadrupole mass spectrometer with the ultimate goal of using it as a prototype for ''knowledge-based'' instrument control. As an ''intelligent'' instrument, with its computer-based data acquisition and control system, it has the ability to learn and respond quickly. The intelligence is encoded in the system using the representation and rule-based reasoning heuristic techniques of Artificial Intelligence. These techniques are used to encode heuristic knowledge, or the intuition, formal and informal rules, and experiential knowledge that the human expert normally uses to make decisions and arrive at solutions in a specific domain problem. In this specific case, the knowledge the authors are encoding is a tuning procedure for the spectrometer, including heuristics to describe a self-adaptive, feedback control process for real-time optimization or tuning of the data acquisition procedure throughout the entire data collection process

  12. Distinct Neurocognitive Strategies for Comprehensions of Human and Artificial Intelligence

    Science.gov (United States)

    Ge, Jianqiao; Han, Shihui

    2008-01-01

    Although humans have inevitably interacted with both human and artificial intelligence in real life situations, it is unknown whether the human brain engages homologous neurocognitive strategies to cope with both forms of intelligence. To investigate this, we scanned subjects, using functional MRI, while they inferred the reasoning processes conducted by human agents or by computers. We found that the inference of reasoning processes conducted by human agents but not by computers induced increased activity in the precuneus but decreased activity in the ventral medial prefrontal cortex and enhanced functional connectivity between the two brain areas. The findings provide evidence for distinct neurocognitive strategies of taking others' perspective and inhibiting the process referenced to the self that are specific to the comprehension of human intelligence. PMID:18665211

  13. A REVIEW ON ARTIFICIAL INTELLIGENT SYSTEM FOR BEARING CONDITION MONITORING

    Directory of Open Access Journals (Sweden)

    PIYUSH M. PATEL,

    2011-02-01

    Full Text Available Artificial Intelligence (AI is an emerging technology. Research in AI is focused on developing computational approaches to intelligent behavior. The computer programs with which AI could be associated are primarily processes associated with complexity, ambiguity, ndecisiveness, and uncertainty. This present paper surveys the development of a condition monitoring procedure for different types ofbearings, which involves an artificial intelligence method as well as reviewed in order to examine the capability of AI methods and techniques to effectively address various hard-to-solve design tasks and issues relating different types of bearing fault. Although this review cannot be collectively exhaustive, it may be considered as a valuable guide for researchers who are interested in the domain of AI and wish to explore the opportunities offered by fuzzy logic, artificial neural networks and genetic algorithms for further improvement of conditioning monitoring for different types of bearing under different operating conditioning. Recent trends in research on conditioning monitoring using AI for different bearing have also been included.

  14. Neuro-Based Artificial Intelligence Model for Loan Decisions

    Directory of Open Access Journals (Sweden)

    Shorouq F. Eletter

    2010-01-01

    Full Text Available 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 backpropagation learning algorithm was used to build up the proposed model. Results: Different representative cases of loan applications were considered based on the guidelines of different banks in Jordan, to validate the neural network model. Conclusion: The results indicated that artificial neural networks are a successful technology that can be used in loan application evaluation in the Jordanian commercial banks.

  15. Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

    Science.gov (United States)

    Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

  16. An Artificial Intelligence Approach for Gears Diagnostics in AUVs

    Directory of Open Access Journals (Sweden)

    Graciliano Nicolás Marichal

    2016-04-01

    Full Text Available In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles, where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

  17. An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

    Science.gov (United States)

    Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

    2016-01-01

    In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868

  18. An Artificial Intelligence Approach for Gears Diagnostics in AUVs

    Science.gov (United States)

    Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

    2016-01-01

    In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868

  19. An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

    Science.gov (United States)

    Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

    2016-04-12

    In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

  20. Artificial Intelligence Research Capabilities of the Air Force Institute of Technology

    OpenAIRE

    Milne, Robert; Cross, Stephen

    1985-01-01

    The Air Force Institute of Technology (AFIT) provides master's degree education to Air Force and Army Officers in various engineering fields It is in a unique position to educate and perform research in the area of applications of artificial intelligence to military problems. Its two AI faculty members are the only military officers with PhD's in Artificial Intelligence. In the past two years, the artificial intelligence Laboratory of AFIT has become a major focal point for AI research and ap...

  1. The Artificial Intelligence Course at the Faculty of Computer Science in the Polytechnic University of Madrid

    OpenAIRE

    A. GÓMEZ-PÉREZ; Juristo, N.

    1994-01-01

    This paper presents the experience of teaching an Artificial Intelligence course at the Faculty of Computer Science in the Polytechnic University of Madrid, Spain. The objective of this course is to introduce the students to this field, to prepare them to contribute to the evolution of the technology, and to qualify them to solve problems in the real world using Artificial Intelligence technology. The curriculum of the Artificial Intelligence course, which is integrate...

  2. 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.

  3. Artificial intelligence support for scientific model-building

    Science.gov (United States)

    Keller, Richard M.

    1992-01-01

    Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

  4. XII International Conference of the Italian Association on Artificial Intelligence

    CERN Document Server

    Semeraro, Giovanni; Vargiu, Eloisa; New Challenges in Distributed Information Filtering and Retrieval : DART 2011: Revised and Invited Papers

    2013-01-01

    This volume focuses on new challenges in distributed Information Filtering and Retrieval. It collects invited chapters and extended research contributions from the DART 2011 Workshop, held in Palermo (Italy), on September 2011, and co-located with the XII International Conference of the Italian Association on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world applications. The chapters of this book present a comprehensive review of related works and state of the art. Authors, both practitioners and researchers, shared their results in several topics such as "Multi-Agent Systems", "Natural Language Processing", "Automatic Advertisement", "Customer Interaction Analytics", "Opinion Mining".

  5. Artificial intelligence in sports on the example of weight training.

    Science.gov (United States)

    Novatchkov, Hristo; Baca, Arnold

    2013-01-01

    The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key pointsArtificial intelligence is a promising field for sport-related analysis.Implementations integrating pattern recognition techniques enable the automatic evaluation of data

  6. Artificial Intelligence in Sports on the Example of Weight Training

    Science.gov (United States)

    Novatchkov, Hristo; Baca, Arnold

    2013-01-01

    The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key points Artificial intelligence is a promising field for sport-related analysis. Implementations integrating pattern recognition techniques enable the automatic evaluation of data

  7. A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

    Directory of Open Access Journals (Sweden)

    Gys Albertus Marthinus Meiring

    2015-12-01

    Full Text Available In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

  8. A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

    Science.gov (United States)

    Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

    2015-12-04

    In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

  9. Using artificial intelligence to control fluid flow computations

    Science.gov (United States)

    Gelsey, Andrew

    1992-01-01

    Computational simulation is an essential tool for the prediction of fluid flow. Many powerful simulation programs exist today. However, using these programs to reliably analyze fluid flow and other physical situations requires considerable human effort and expertise to set up a simulation, determine whether the output makes sense, and repeatedly run the simulation with different inputs until a satisfactory result is achieved. Automating this process is not only of considerable practical importance but will also significantly advance basic artificial intelligence (AI) research in reasoning about the physical world.

  10. Artificial intelligence techniques for scheduling Space Shuttle missions

    Science.gov (United States)

    Henke, Andrea L.; Stottler, Richard H.

    1994-01-01

    Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.

  11. Artificial intelligence and expert systems in-flight software testing

    Science.gov (United States)

    Demasie, M. P.; Muratore, J. F.

    1991-01-01

    The authors discuss the introduction of advanced information systems technologies such as artificial intelligence, expert systems, and advanced human-computer interfaces directly into Space Shuttle software engineering. The reconfiguration automation project (RAP) was initiated to coordinate this move towards 1990s software technology. The idea behind RAP is to automate several phases of the flight software testing procedure and to introduce AI and ES into space shuttle flight software testing. In the first phase of RAP, conventional tools to automate regression testing have already been developed or acquired. There are currently three tools in use.

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

    Institute of Scientific and Technical Information of China (English)

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

    2003-01-01

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

  13. The role of artificial intelligence techniques in scheduling systems

    Science.gov (United States)

    Geoffroy, Amy L.; Britt, Daniel L.; Gohring, John R.

    1990-01-01

    Artificial Intelligence (AI) techniques provide good solutions for many of the problems which are characteristic of scheduling applications. However, scheduling is a large, complex heterogeneous problem. Different applications will require different solutions. Any individual application will require the use of a variety of techniques, including both AI and conventional software methods. The operational context of the scheduling system will also play a large role in design considerations. The key is to identify those places where a specific AI technique is in fact the preferable solution, and to integrate that technique into the overall architecture.

  14. The application of artificial intelligence technology to aeronautical system design

    Science.gov (United States)

    Bouchard, E. E.; Kidwell, G. H.; Rogan, J. E.

    1988-01-01

    This paper describes the automation of one class of aeronautical design activity using artificial intelligence and advanced software techniques. Its purpose is to suggest concepts, terminology, and approaches that may be useful in enhancing design automation. By understanding the basic concepts and tasks in design, and the technologies that are available, it will be possible to produce, in the future, systems whose capabilities far exceed those of today's methods. Some of the tasks that will be discussed have already been automated and are in production use, resulting in significant productivity benefits. The concepts and techniques discussed are applicable to all design activity, though aeronautical applications are specifically presented.

  15. Westinghouse use of artificial intelligence in signal interpretation

    International Nuclear Information System (INIS)

    This paper discusses Westinghouse's use of artificial intelligence to assist inspectors who routinely monitor the thousands of tubes in nuclear steam generators. Using the AI technology has made the inspection process easier to learn and to apply. The system uses pattern recognition to identify off-normal conditions. As part of the in-service inspection program for nuclear power reactors, utilities make a practice of inspecting the condition of the large heat exchangers that produce the steam that turns the electric turbine generator. The same data are presented for inspection using form, motion, and color to call attention to off-normal signal patterns

  16. ICON: An artificial intelligence approach to radiologic differential diagnosis

    International Nuclear Information System (INIS)

    ICON is a computer system, developed using artificial intelligence techniques, that is designed to help radiologists manage the large body of knowledge needed to perform differential diagnosis in radiology. The system's domain is lung disease in patients with lymphoproliferative disorders. The radiologist proposes a diagnostic hypothesis which he or she thinks explains the known clinical and chest radiographic findings. ICON responds with an English-language prose critique that discusses how and why the proposed diagnosis is or is not supported by the clinical literature and suggests further findings or clinical information that might make the diagnosis more secure

  17. THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN SOUTH AFRICAN MANUFACTURING

    Directory of Open Access Journals (Sweden)

    A.R. Greef

    2012-01-01

    Full Text Available This paper provides an introduction to the most commonly used Knowledge Based Systems (KBS's called Rule Based Systems, presents some benefits of using these systems if the application warrants their attention and provides an over-view of current R&D as well as industrial systems already implemented. Areas of manUfacturing that could use KES's within the South African context are suggested. A research programme investigating the use of KBS's in robotics in progress at the University of Stellenbosch demonstrating a number of useful properties associated with programming Artificial Intelligence (AI techniques using logic programming, is discussed.

  18. Simulation of Artificial Intelligence for Automotive Air-conditioning System

    Institute of Scientific and Technical Information of China (English)

    YUAN Xiao-mei; CHEN You-hua; CHEN Zhi-jiu

    2002-01-01

    The artificial intelligence is applied to the simulation of the automotive air-conditioning system ( AACS )According to the system's characteristics a model of AACS, based on neural network, is developed. Different control methods of AACS are discussed through simulation based on this model. The result shows that the neural- fuzzy control is the best one compared with the on-off control and conventional fuzzy control method.It can make the compartment's temperature descend rapidly to the designed temperature and the fluctuation is small.

  19. Artificial Intelligence in the service of system administrators

    CERN Document Server

    CERN. Geneva

    2012-01-01

    Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way  Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with a "object oriented paradigm" architecture should increase a lot our learning speed, and highlight relations between probl...

  20. Teaching Artificial Intelligence and Logic Programming in a Competitive Environment

    Directory of Open Access Journals (Sweden)

    Pedro RIBEIRO

    2009-04-01

    Full Text Available Motivation plays a key role in the learning process. This paper describes an experience in the context of undergraduate teaching of Artificial Intelligence at the Computer Science Department of the Faculty of Sciences in the University of Porto. A sophisticated competition framework, which involved Prolog programmed contenders and game servers, including an appealing GUI, was developed to motivate students on the deepening of the topics covered in class. We report on the impact that such a competitive setup caused on students' commitment, which surpassed our most optimistic expectations.

  1. PRONET: Basic concepts of a system of Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    S. Lasai

    1999-12-01

    Full Text Available In the work are expounded the principles and basic elements of a system of artificial intelligence. Knowledge representation develops according to the method settled for processing. A thing, a phenomenon can be determined or established by more modules subject to their state as well as the links and relations between them. The system creates a set of blocks (modules for which the concurrent work is pre- established. The volume of knowledge can be also increased without increasing the number of blocks.

  2. Artificial intelligence in medicine: humans need not apply?

    Science.gov (United States)

    Diprose, William; Buist, Nicholas

    2016-05-06

    Artificial intelligence (AI) is a rapidly growing field with a wide range of applications. Driven by economic constraints and the potential to reduce human error, we believe that over the coming years AI will perform a significant amount of the diagnostic and treatment decision-making traditionally performed by the doctor. Humans would continue to be an important part of healthcare delivery, but in many situations, less expensive fit-for-purpose healthcare workers could be trained to 'fill the gaps' where AI are less capable. As a result, the role of the doctor as an expensive problem-solver would become redundant.

  3. Artificial Intelligence as a Business Forecasting and Error Handling Tool

    Directory of Open Access Journals (Sweden)

    Md. Tabrez Quasim

    2015-10-01

    Full Text Available  Any business enterprise must rely a lot on how well it can predict the future happenings. To cope up with the modern global customer demand, technological challenges, market competitions etc., any organization is compelled to foresee the future having maximum impact and least chances of errors. The traditional forecasting approaches have some limitations. That is why the business world is adopting the modern Artificial Intelligence based forecasting techniques. This paper has tried to present different types of forecasting and AI techniques that are useful in business forecasting. At the later stage we have also discussed the forecasting errors and the steps involved in planning the AI support system.

  4. Chips challenging champions games, computers and artificial intelligence

    CERN Document Server

    Schaeffer, J

    2002-01-01

    One of the earliest dreams of the fledgling field of artificial intelligence (AI) was to build computer programs that could play games as well as or better than the best human players. Despite early optimism in the field, the challenge proved to be surprisingly difficult. However, the 1990s saw amazing progress. Computers are now better than humans in checkers, Othello and Scrabble; are at least as good as the best humans in backgammon and chess; and are rapidly improving at hex, go, poker, and shogi. This book documents the progress made in computers playing games and puzzles. The book is the

  5. Artificial intelligence in medicine: humans need not apply?

    Science.gov (United States)

    Diprose, William; Buist, Nicholas

    2016-01-01

    Artificial intelligence (AI) is a rapidly growing field with a wide range of applications. Driven by economic constraints and the potential to reduce human error, we believe that over the coming years AI will perform a significant amount of the diagnostic and treatment decision-making traditionally performed by the doctor. Humans would continue to be an important part of healthcare delivery, but in many situations, less expensive fit-for-purpose healthcare workers could be trained to 'fill the gaps' where AI are less capable. As a result, the role of the doctor as an expensive problem-solver would become redundant. PMID:27349266

  6. Artificial intelligence program in a computer application supporting reactor operations

    International Nuclear Information System (INIS)

    Improving nuclear reactor power plant operability is an ever-present concern for the nuclear industry. The definition of plant operability involves a complex interaction of the ideas of reliability, safety, and efficiency. This paper presents observations concerning the issues involved and the benefits derived from the implementation of a computer application which combines traditional computer applications with artificial intelligence (AI) methodologies. A system, the Component Configuration Control System (CCCS), is being installed to support nuclear reactor operations at the Experimental Breeder Reactor II

  7. The Use of Artificial Intelligence on Finacial Market

    OpenAIRE

    Surynek, Jiří

    2013-01-01

    Diplomová práce se zabývá problematikou a následnou aplikací metod umělé inteligence na finančních trzích. Konkrétně se jedná o využití umělých neuronových sítí za účelem predikce hodnoty a určení trendu vývoje vybraného investičního nástroje. Vlastní řešení je vytvořeno ve vývojovém prostředí Matlab. This thesis focuses on the problem and application of artificial intelligence on the financial market. Especially, the use of artificial neural networks to forecast values and determine the t...

  8. A genetic-neural artificial intelligence approach to resins optimization

    International Nuclear Information System (INIS)

    This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

  9. Artificial intelligence methods in deregulated power systems operations

    Science.gov (United States)

    Ilic, Jovan

    With the introduction of the power systems deregulation, many classical power transmission and distribution optimization tools became inadequate. Optimal Power Flow and Unit Commitment are common computer programs used in the regulated power industry. This work is addressing the Optimal Power Flow and Unit Commitment in the new deregulated environment. Optimal Power Flow is a high dimensional, non-linear, and non-convex optimization problem. As such, it is even now, after forty years since its introduction, a research topic without a widely accepted solution able to encompass all areas of interest. Unit Commitment is a high dimensional, combinatorial problem which should ideally include the Optimal Power Flow in its solution. The dimensionality of a typical Unit Commitment problem is so great that even the enumeration of all the combinations would take too much time for any practical purposes. This dissertation attacks the Optimal Power Flow problem using non-traditional tools from the Artificial Intelligence arena. Artificial Intelligence optimization methods are based on stochastic principles. Usually, stochastic optimization methods are successful where all other classical approaches fail. We will use Genetic Programming optimization for both Optimal Power Flow and Unit Commitment. Long processing times will also be addressed through supervised machine learning.

  10. Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

    Science.gov (United States)

    Abbasi, Maryam; El Hanandeh, Ali

    2016-10-01

    Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. PMID:27297046

  11. AN ARTIFICIAL INTELLIGENCE-BASED DISTANCE EDUCATION SYSTEM: Artimat

    Directory of Open Access Journals (Sweden)

    Vasif NABIYEV

    2013-04-01

    Full Text Available The purpose of this study is to evaluate the artificial intelligence-based distance education system called as ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed with 4 teachers and 59 students in 10th grade in an Anatolian High School in Trabzon. Many institutions and organizations in the world approach seriously to distance education besides traditional education. It is inevitable to use the distance education in teaching the problem solving skills in this different dimension of the education. In the studies in Turkey and abroad in the field of mathematics teaching, problem solving skills are generally stated not to be at the desired level and often expressed to have difficulty in teaching. For this reason, difficulties of the students in problem solving have initially been evaluated and the system has been prepared utilizing artificial intelligence algorithms according to the obtained results. In the evaluation of the findings obtained from the application, it has been concluded that the system is responsive to the needs of the students and is successful in general, but that conceptual changes should be made in order that students adapt to the system quickly.

  12. Artificial intelligence applications in offshore oil and gas production

    International Nuclear Information System (INIS)

    The field of Artificial Intelligence (AI) has gained considerable acceptance in virtually all fields, of engineering applications. Artificial intelligence is now being applied in several areas of offshore oil and gas operations, such as drilling, well testing, well logging and interpretation, reservoir engineering, planning and economic evaluation, process control, and risk analysis. Current AI techniques offer a new and exciting technology for solving problems in the oil and gas industry. Expert systems, fuzzy logic systems, neural networks and genetic algorithms are major AI technologies which have made an impact on the petroleum industry. Presently, these technologies are at different stages of maturity with expert systems being the most mature and genetic algorithms the least. However, all four technologies have evolved such that practical applications were produced. This paper describes the four major Al techniques and their many applications in offshore oil and gas production operations. A summary description of future developments in Al technology that will affect the execution and productivity of offshore operations will be also provided

  13. Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

    Science.gov (United States)

    Abbasi, Maryam; El Hanandeh, Ali

    2016-10-01

    Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg.

  14. Artificial Intelligence Techniques for Automatic Screening of Amblyogenic Factors

    Science.gov (United States)

    Van Eenwyk, Jonathan; Agah, Arvin; Giangiacomo, Joseph; Cibis, Gerhard

    2008-01-01

    Purpose To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. Methods In 1994 one of the authors (G.C.) described video vision development assessment, a digitizable analog video-based system combining Brückner pupil red reflex imaging and eccentric photorefraction to screen young children for amblyogenic factors. The images were analyzed manually with this system. We automated the capture of digital video frames and pupil images and applied computer vision and artificial intelligence to analyze and interpret results. The artificial intelligence systems were evaluated by a tenfold testing method. Results The best system was the decision tree learning approach, which had an accuracy of 77%, compared to the “gold standard” specialist examination with a “refer/do not refer” decision. Criteria for referral were strabismus, including microtropia, and refractive errors and anisometropia considered to be amblyogenic. Eighty-two percent of strabismic individuals were correctly identified. High refractive errors were also correctly identified and referred 90% of the time, as well as significant anisometropia. The program was less correct in identifying more moderate refractive errors, below +5 and less than −7. Conclusions Although we are pursuing a variety of avenues to improve the accuracy of the automated analysis, the program in its present form provides acceptable cost benefits for detecting ambylogenic factors in children aged 6 months to 6 years. PMID:19277222

  15. Artificial intelligence applied to fuel management in BWR type reactors

    International Nuclear Information System (INIS)

    In this work two techniques of artificial intelligence, neural networks and genetic algorithms were applied to a practical problem of nuclear fuel management; the determination of the optimal fuel reload for a BWR type reactor. This is an important problem in the design of the operation cycle of the reactor. As a result of the application of these techniques, comparable or even better reloads proposals than those given by expert companies in the subject were obtained. Additionally, two other simpler problems in reactor physics were solved: the determination of the axial power profile and the prediction of the value of some variables of interest at the end of the operation cycle of the reactor. Neural networks and genetic algorithms have been applied to solve many problems of engineering because of their versatility but they have been rarely used in the area of fuel management. The results obtained in this thesis indicates the convenience of undertaking further work on this area and suggest the application of these techniques of artificial intelligence to the solution of other problems in nuclear reactor physics. (Author)

  16. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  17. Proceedings of the 18th Irish Conference on Artificial Intelligence and Cognitive Science

    OpenAIRE

    Delany, Sarah Jane; Madden, Michael

    2009-01-01

    These proceedings contain the papers that were accepted for publication at AICS-2007, the 18th Annual Conference on Artificial Intelligence and Cognitive Science, which was held in the Dublin Institute of Technology; Dublin, Ireland; on the 29th to the 31st August 2007. AICS is the annual conference of the Artificial Intelligence Association of Ireland (AIAI).

  18. Where Artificial Intelligence and Neuroscience Meet: The Search for Grounded Architectures of Cognition

    Directory of Open Access Journals (Sweden)

    Frank van der Velde

    2010-01-01

    Full Text Available The collaboration between artificial intelligence and neuroscience can produce an understanding of the mechanisms in the brain that generate human cognition. This article reviews multidisciplinary research lines that could achieve this understanding. Artificial intelligence has an important role to play in research, because artificial intelligence focuses on the mechanisms that generate intelligence and cognition. Artificial intelligence can also benefit from studying the neural mechanisms of cognition, because this research can reveal important information about the nature of intelligence and cognition itself. I will illustrate this aspect by discussing the grounded nature of human cognition. Human cognition is perhaps unique because it combines grounded representations with computational productivity. I will illustrate that this combination requires specific neural architectures. Investigating and simulating these architectures can reveal how they are instantiated in the brain. The way these architectures implement cognitive processes could also provide answers to fundamental problems facing the study of cognition.

  19. Artificial Life of Soybean Plant Growth Modeling Using Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Atris Suyantohadi

    2010-03-01

    Full Text Available The natural process on plant growth system has a complex system and it has could be developed on characteristic studied using intelligent approaches conducting with artificial life system. The approaches on examining the natural process on soybean (Glycine Max L.Merr plant growth have been analyzed and synthesized in these research through modeling using Artificial Neural Network (ANN and Lindenmayer System (L-System methods. Research aimed to design and to visualize plant growth modeling on the soybean varieties which these could help for studying botany of plant based on fertilizer compositions on plant growth with Nitrogen (N, Phosphor (P and Potassium (K. The soybean plant growth has been analyzed based on the treatments of plant fertilizer compositions in the experimental research to develop plant growth modeling. By using N, P, K fertilizer compositions, its capable result on the highest production 2.074 tons/hectares. Using these models, the simulation on artificial life for describing identification and visualization on the characteristic of soybean plant growth could be demonstrated and applied.

  20. A Multilayered Model for Artificial Intelligence of Game Character as Agent Architecture

    OpenAIRE

    Miyake, Youichiro; Miyake, Yoichiro

    2015-01-01

    As all mathematics have a beautiful structure, an inner mind model of Artificial Intelligence has a grand architecture. It consists of information flow and software modules. In this twenty years, an agent's inner intelligence model has been researched and developed by many game AI programmers in game titles. A whole image of an agent's intelligent model is explained.

  1. E-LEARNING EXPERIENCE WITH ARTIFICIAL INTELLIGENCE SUPPORTED SOFTWARE: An International Application on English Language Courses

    OpenAIRE

    Kose, Utku; Arslan, Ahmet

    2015-01-01

    Nowadays, artificial intelligence supported e-learning scenarios are widely employed by educational institutions in order to ensure better teaching and learning experiences along educational activities. In the context of performed scientific studies, positive results often encourage such institutions to apply their intelligent e-learning systems on different types of courses and report advantages of artificial intelligent in especially education field. It seems that the future of education w...

  2. Evolvable mathematical models: A new artificial Intelligence paradigm

    Science.gov (United States)

    Grouchy, Paul

    We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

  3. AIonAI: a humanitarian law of artificial intelligence and robotics.

    Science.gov (United States)

    Ashrafian, Hutan

    2015-02-01

    The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation.

  4. Implementing Human-like Intuition Mechanism in Artificial Intelligence

    CERN Document Server

    Dundas, Jitesh

    2011-01-01

    Human intuition has been simulated by several research projects using artificial intelligence techniques. Most of these algorithms or models lack the ability to handle complications or diversions. Moreover, they also do not explain the factors influencing intuition and the accuracy of the results from this process. In this paper, we present a simple series based model for implementation of human-like intuition using the principles of connectivity and unknown entities. By using Poker hand datasets and Car evaluation datasets, we compare the performance of some well-known models with our intuition model. The aim of the experiment was to predict the maximum accurate answers using intuition based models. We found that the presence of unknown entities, diversion from the current problem scenario, and identifying weakness without the normal logic based execution, greatly affects the reliability of the answers. Generally, the intuition based models cannot be a substitute for the logic based mechanisms in handling su...

  5. The implementation of artificial intelligence in control systems

    Energy Technology Data Exchange (ETDEWEB)

    Koul, R.; Weygand, D.P.

    1987-01-01

    Some concepts of artificial intelligence are reviewed, particularly as they apply to control systems of accelerators. Logical representation and formal reasoning are discussed briefly, as well as production systems, which describe various systems based on the idea of condition-action pairs (productions). Procedural knowledge, which deals with routine activities that rarely require change, is described. Frames are defined, which provide a convenient structure for representing knowledge. Frames consist of information about objects. For a given frame there are various slots, and for each slot there are various facets, each containing various data. Direct analogical representation is defined as a class of representation which represents knowledge in a natural analog manner, allowing observation of facts in many cases to be achieved quickly and easily compared to deduction. Architecture of systems applied to accelerator control is then described. (LEW)

  6. SWARM INTELLIGENCE FROM NATURAL TO ARTIFICIAL SYSTEMS: ANT COLONY OPTIMIZATION

    Directory of Open Access Journals (Sweden)

    O. Deepa

    2016-03-01

    Full Text Available Successful applications coming from biologically inspired algorithm like Ant Colony Optimization (ACO based on artificial swarm intelligence which is inspired by the collective behavior of social insects. ACO has been inspired from natural ants system, their behavior, team coordination, synchronization for the searching of optimal solution and also maintains information of each ant. At present, ACO has emerged as a leading metaheuristic technique for the solution of combinatorial optimization problems which can be used to find shortest path through construction graph. This paper describe about various behavior of ants, successfully used ACO algorithms, applications and current trends. In recent years, some researchers have also focused on the application of ACO algorithms to design of wireless communication network, bioinformatics problem, dynamic problem and multi-objective problem.

  7. Artificial intelligence for multi-mission planetary operations

    Science.gov (United States)

    Atkinson, David J.; Lawson, Denise L.; James, Mark L.

    1990-01-01

    A brief introduction is given to an automated system called the Spacecraft Health Automated Reasoning Prototype (SHARP). SHARP is designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for evaluation of the prototype in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The preliminary results of the SHARP project and plans for future application of the technology are discussed.

  8. Application of Artificial Intelligence for Bridge Deterioration Model.

    Science.gov (United States)

    Chen, Zhang; Wu, Yangyang; Li, Li; Sun, Lijun

    2015-01-01

    The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention.

  9. Quantum Interaction Approach in Cognition, Artificial Intelligence and Robotics

    CERN Document Server

    Aerts, Diederik; Sozzo, Sandro

    2011-01-01

    The mathematical formalism of quantum mechanics has been successfully employed in the last years to model situations in which the use of classical structures gives rise to problematical situations, and where typically quantum effects, such as 'contextuality' and 'entanglement', have been recognized. This 'Quantum Interaction Approach' is briefly reviewed in this paper focusing, in particular, on the quantum models that have been elaborated to describe how concepts combine in cognitive science, and on the ensuing identification of a quantum structure in human thought. We point out that these results provide interesting insights toward the development of a unified theory for meaning and knowledge formalization and representation. Then, we analyze the technological aspects and implications of our approach, and a particular attention is devoted to the connections with symbolic artificial intelligence, quantum computation and robotics.

  10. 13th International Conference on Distributed Computing and Artificial Intelligence

    CERN Document Server

    Silvestri, Marcello; González, Sara

    2016-01-01

    The special session Decision Economics (DECON) 2016 is a scientific forum by which to share ideas, projects, researches results, models and experiences associated with the complexity of behavioral decision processes aiming at explaining socio-economic phenomena. DECON 2016 held in the University of Seville, Spain, as part of the 13th International Conference on Distributed Computing and Artificial Intelligence (DCAI) 2016. In the tradition of Herbert A. Simon’s interdisciplinary legacy, this book dedicates itself to the interdisciplinary study of decision-making in the recognition that relevant decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, small and international business, management, operations, and production. Decision-making issues are of crucial importance in economics. Not surprisingly, the study of decision-making has received a growing empirical research efforts in the applied economic literature over the last ...

  11. Artificial Intelligence Based Three-Phase Unified Power Quality Conditioner

    Directory of Open Access Journals (Sweden)

    Moleykutty George

    2007-01-01

    Full Text Available Power quality is an important measure of the performance of an electrical power system. This paper discusses the topology, control strategies using artificial intelligent (AI based controllers and the performance of a unified power quality conditioner (UPQC for power quality improvement. UPQC is an integration of shunt and series compensation to limit the harmonic contamination within 5 %, the limit imposed by IEEE-519 standard. The novelty of this paper lies in the application of neural network control (NNC algorithms such as model reference control (MRC, and nonlinear autoregressive-moving average (NARMA–L2 control to generate switching signals for the series compensator of the UPQC system. The entire system has been modeled using MATLAB 7.0 toolbox. Simulation results demonstrate the applicability of MRC and NARMA-L2 controllers for the control of UPQC.

  12. An intercomparison of artificial intelligence approaches for polar scene identification

    Science.gov (United States)

    Tovinkere, V. R.; Penaloza, M.; Logar, A.; Lee, J.; Weger, R. C.; Berendes, T. A.; Welch, R. M.

    1993-01-01

    The following six different artificial-intelligence (AI) approaches to polar scene identification are examined: (1) a feed forward back propagation neural network, (2) a probabilistic neural network, (3) a hybrid neural network, (4) a 'don't care' feed forward perception model, (5) a 'don't care' feed forward back propagation neural network, and (6) a fuzzy logic based expert system. The ten classes into which six AVHRR local-coverage arctic scenes were classified were: water, solid sea ice, broken sea ice, snow-covered mountains, land, stratus over ice, stratus over water, cirrus over water, cumulus over water, and multilayer cloudiness. It was found that 'don't care' back propagation neural network produced the highest accuracies. This approach has also low CPU requirement.

  13. Application of Artificial Intelligence for Optimization in Pavement Management

    Directory of Open Access Journals (Sweden)

    Reus Salini

    2015-07-01

    Full Text Available Artificial intelligence (AI is a group of techniques that have quite a potential to be applied to pavement engineering and management. In this study, we developed a practical, flexible and out of the box approach to apply genetic algorithms to optimizing the budget allocation and the road maintenance strategy selection for a road network. The aim is to provide an alternative to existing software and better fit the requirements of an important number of pavement managers. To meet the objectives, a new indicator, named Road Global Value Index (RGVI, was created to contemplate the pavement condition, the traffic and the economic and political importance for each and every road section. This paper describes the approach and its components by an example confirming that genetic algorithms are very effective for the intended purpose.

  14. The implementation of artificial intelligence in control systems

    International Nuclear Information System (INIS)

    Some concepts of artificial intelligence are reviewed, particularly as they apply to control systems of accelerators. Logical representation and formal reasoning are discussed briefly, as well as production systems, which describe various systems based on the idea of condition-action pairs (productions). Procedural knowledge, which deals with routine activities that rarely require change, is described. Frames are defined, which provide a convenient structure for representing knowledge. Frames consist of information about objects. For a given frame there are various slots, and for each slot there are various facets, each containing various data. Direct analogical representation is defined as a class of representation which represents knowledge in a natural analog manner, allowing observation of facts in many cases to be achieved quickly and easily compared to deduction. Architecture of systems applied to accelerator control is then described

  15. Medical image diagnosis of liver cancer using artificial intelligence

    International Nuclear Information System (INIS)

    A revised Group Method of Data Handling (GMDH)-type neural network algorithm using artificial intelligence technology for medical image diagnosis is proposed and is applied to medical image diagnosis of liver cancer. In this algorithm, the knowledge base for medical image diagnosis are used for organizing the neural network architecture for medical image diagnosis. Furthermore, the revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares (PSS). It is shown that the revised GMDH-type neural network can be easily applied to the medical image diagnosis. (author)

  16. Artificial intelligence in nuclear power plants. Vol. 2

    International Nuclear Information System (INIS)

    The IAEA Specialists' Meeting on Artificial Intelligence in Nuclear Power Plants was arranged in Helsinki/Vantaa, Finland, on October 10-12, 1989, under auspices of the International Working Group of Nuclear Power Plant Control and Instrumentation of the International Atomic Energy Agency (IAEA/IWG NPPCI). Technical Research Centre of Finland together with Imatran Voima Oy and Teollisuuden Voima Oy answered for the practical arrangements of the meeting. 105 participants from 17 countries and 2 international organizations took part in the meeting and 58 papers were submitted for presentation. These papers gave a comprehensive picture of the recent status and further trends in applying the rapidly developing techniques of and safety in designing and using of nuclear power worldwide

  17. Classification of artificial intelligence ids for smurf attack

    CERN Document Server

    Ugtakhbayar, N; Sodbileg, Sh

    2012-01-01

    Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf attack with much reliable accuracy.

  18. Application of Artificial Intelligence to Reservoir Characterization - An Interdisciplinary Approach

    Energy Technology Data Exchange (ETDEWEB)

    Kelkar, B.G.; Gamble, R.F.; Kerr, D.R.; Thompson, L.G.; Shenoi, S.

    2000-01-12

    The primary goal of this project is to develop a user-friendly computer program to integrate geological and engineering information using Artificial Intelligence (AI) methodology. The project is restricted to fluvially dominated deltaic environments. The static information used in constructing the reservoir description includes well core and log data. Using the well core and the log data, the program identifies the marker beds, and the type of sand facies, and in turn, develops correlation's between wells. Using the correlation's and sand facies, the program is able to generate multiple realizations of sand facies and petrophysical properties at interwell locations using geostatistical techniques. The generated petrophysical properties are used as input in the next step where the production data are honored. By adjusting the petrophysical properties, the match between the simulated and the observed production rates is obtained.

  19. Artificial Intelligence techniques for mission planning for mobile robots

    International Nuclear Information System (INIS)

    This work focuses on Spatial Modelization Techniques and on Control Software Architectures, in order to deal efficiently with the Navigation and Perception problems encountered in Mobile Autonomous Robotics. After a brief survey of the current various approaches for these techniques, we expose ongoing simulation works for a specific mission in robotics. Studies in progress used for Spatial Reasoning are based on new approaches combining Artificial Intelligence and Geometrical techniques. These methods deal with the problem of environment modelization using three types of models: geometrical topological and semantic models at different levels. The decision making processes of control are presented as the result of cooperation between a group of decentralized agents that communicate by sending messages. (author)

  20. Implementing Artificial Intelligence Behaviors in a Virtual World

    Science.gov (United States)

    Krisler, Brian; Thome, Michael

    2012-01-01

    In this paper, we will present a look at the current state of the art in human-computer interface technologies, including intelligent interactive agents, natural speech interaction and gestural based interfaces. We describe our use of these technologies to implement a cost effective, immersive experience on a public region in Second Life. We provision our Artificial Agents as a German Shepherd Dog avatar with an external rules engine controlling the behavior and movement. To interact with the avatar, we implemented a natural language and gesture system allowing the human avatars to use speech and physical gestures rather than interacting via a keyboard and mouse. The result is a system that allows multiple humans to interact naturally with AI avatars by playing games such as fetch with a flying disk and even practicing obedience exercises using voice and gesture, a natural seeming day in the park.

  1. Artificial intelligence in the service of system administrators

    CERN Document Server

    Haen, Christophe; Bonaccorsi, E; Neufeld, N

    2012-01-01

    The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called self objectives supposed to lead to autonomic computing. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an object oriented paradigm architecture should increase our learning speed a lot and highlight relations between problems.

  2. Estimation of mechanical properties of nanomaterials using artificial intelligence methods

    Science.gov (United States)

    Vijayaraghavan, V.; Garg, A.; Wong, C. H.; Tai, K.

    2014-09-01

    Computational modeling tools such as molecular dynamics (MD), ab initio, finite element modeling or continuum mechanics models have been extensively applied to study the properties of carbon nanotubes (CNTs) based on given input variables such as temperature, geometry and defects. Artificial intelligence techniques can be used to further complement the application of numerical methods in characterizing the properties of CNTs. In this paper, we have introduced the application of multi-gene genetic programming (MGGP) and support vector regression to formulate the mathematical relationship between the compressive strength of CNTs and input variables such as temperature and diameter. The predictions of compressive strength of CNTs made by these models are compared to those generated using MD simulations. The results indicate that MGGP method can be deployed as a powerful method for predicting the compressive strength of the carbon nanotubes.

  3. Application of Artificial Intelligence for Bridge Deterioration Model

    Directory of Open Access Journals (Sweden)

    Zhang Chen

    2015-01-01

    Full Text Available The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention.

  4. Training Software in Artificial-Intelligence Computing Techniques

    Science.gov (United States)

    Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

    2005-01-01

    The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

  5. Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

    Directory of Open Access Journals (Sweden)

    Pedro U. Lima

    2008-11-01

    Full Text Available This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior T?cnico (ISR/IST in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots and dynamic (moving robots obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams.

  6. Implementation and Validation of Artificial Intelligence Techniques for Robotic Surgery

    Directory of Open Access Journals (Sweden)

    Aarshay Jain

    2014-03-01

    Full Text Available The primary focus of this study is implementation of Artificial Intelligence (AI technique for developing an inverse kinematics solution for the Raven-IITM surgical research robot [1]. First, the kinematic model of the Raven-IITM robot was analysed along with the proposed analytical solution [2] for inverse kinematics problem. Next, The Artificial Neural Network (ANN techniques was implemented. The training data for the same was careful selected by keeping manipulability constraints in mind. Finally, the results were verified using elliptical trajectories. The originally proposed analytical solution was found to be computationally inefficient, gave multiple solutions and its existence necessitates the use of the Standard Raven-IITM Tool [2]. The solution devised using ANN technique gave a single solution which was thirteen times faster than the original solution. Moreover, it is generic in nature and can be used for any type of tool. Thus, a novel solution for solving the inverse kinematics problem of the Raven-II surgical robot was formulated and confirmed.

  7. [Artificial intelligence to assist clinical diagnosis in medicine].

    Science.gov (United States)

    Lugo-Reyes, Saúl Oswaldo; Maldonado-Colín, Guadalupe; Murata, Chiharu

    2014-01-01

    Medicine is one of the fields of knowledge that would most benefit from a closer interaction with Computer studies and Mathematics by optimizing complex, imperfect processes such as differential diagnosis; this is the domain of Machine Learning, a branch of Artificial Intelligence that builds and studies systems capable of learning from a set of training data, in order to optimize classification and prediction processes. In Mexico during the last few years, progress has been made on the implementation of electronic clinical records, so that the National Institutes of Health already have accumulated a wealth of stored data. For those data to become knowledge, they need to be processed and analyzed through complex statistical methods, as it is already being done in other countries, employing: case-based reasoning, artificial neural networks, Bayesian classifiers, multivariate logistic regression, or support vector machines, among other methodologies; to assist the clinical diagnosis of acute appendicitis, breast cancer and chronic liver disease, among a wide array of maladies. In this review we shift through concepts, antecedents, current examples and methodologies of machine learning-assisted clinical diagnosis.

  8. An application of artificial intelligence for rainfall–runoff modeling

    Indian Academy of Sciences (India)

    Ali Aytek; M Asce; Murat Alp

    2008-04-01

    This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two different ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods are compared with one EC method, Gene Expression Programming (GEP) which is a new evolutionary algorithm that evolves computer programs. The daily hydrometeorological data of three rainfall stations and one streamflow station for Juniata River Basin in Pennsylvania state of USA are taken into consideration in the model development. Statistical parameters such as average, standard deviation, coefficient of variation, skewness, minimum and maximum values, as well as criteria such as mean square error (MSE) and determination coefficient (2) are used to measure the performance of the models. The results indicate that the proposed genetic programming (GP) formulation performs quite well compared to results obtained by ANNs and is quite practical for use. It is concluded from the results that GEP can be proposed as an alternative to ANN models.

  9. ARTIFICIAL INTELLIGENCE IN SPORTS BIOMECHANICS: NEW DAWN OR FALSE HOPE?

    Directory of Open Access Journals (Sweden)

    Roger Bartlett

    2006-12-01

    Full Text Available This article reviews developments in the use of Artificial Intelligence (AI in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements ('techniques' and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics.

  10. Improved RMR Rock Mass Classification Using Artificial Intelligence Algorithms

    Science.gov (United States)

    Gholami, Raoof; Rasouli, Vamegh; Alimoradi, Andisheh

    2013-09-01

    Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide information about the quality of rocks surrounding a structure as well as to propose suitable support systems for unstable regions. Many correlations have been proposed to relate measured quantities such as wave velocity to rock mass classification systems to limit the associated time and cost of conducting the sampling and mechanical tests conventionally used to calculate RMR values. However, these empirical correlations have been found to be unreliable, as they usually overestimate or underestimate the RMR value. The aim of this paper is to compare the results of RMR classification obtained from the use of empirical correlations versus machine-learning methodologies based on artificial intelligence algorithms. The proposed methods were verified based on two case studies located in northern Iran. Relevance vector regression (RVR) and support vector regression (SVR), as two robust machine-learning methodologies, were used to predict the RMR for tunnel host rocks. RMR values already obtained by sampling and site investigation at one tunnel were taken into account as the output of the artificial networks during training and testing phases. The results reveal that use of empirical correlations overestimates the predicted RMR values. RVR and SVR, however, showed more reliable results, and are therefore suggested for use in RMR classification for design purposes of rock structures.

  11. Predicting chick body mass by artificial intelligence-based models

    Directory of Open Access Journals (Sweden)

    Patricia Ferreira Ponciano Ferraz

    2014-07-01

    Full Text Available The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks - with the variables dry-bulb air temperature, duration of thermal stress (days, chick age (days, and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs and neuro-fuzzy networks (NFNs. The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

  12. Artificial intelligence and Internet of Things in a “smart home” context

    DEFF Research Database (Denmark)

    Lynggaard, Per

    with autonomous behavior, parallel processing, context awareness, and node communication. In particular, it introduces a novel approach to adapt and distribute the artificial intelligence to match the distributed system architecture in the smart home. The proposed solution addresses important issues such as real......-assisted living, intelligent transportation systems, and many other sustainable solutions based on ICT.......We are currently witnessing an evolution from building and home automation to smart homes, driven by progressing maturity of the Internet of Things and the use of artificial intelligence. However, significant technological challenges such as immature home intelligence, huge network and central...

  13. Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

    Science.gov (United States)

    Cipresso, Pietro; Riva, Giuseppe

    2015-01-01

    There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

  14. Computer-aided diagnosis and artificial intelligence in clinical imaging.

    Science.gov (United States)

    Shiraishi, Junji; Li, Qiang; Appelbaum, Daniel; Doi, Kunio

    2011-11-01

    Computer-aided diagnosis (CAD) is rapidly entering the radiology mainstream. It has already become a part of the routine clinical work for the detection of breast cancer with mammograms. The computer output is used as a "second opinion" in assisting radiologists' image interpretations. The computer algorithm generally consists of several steps that may include image processing, image feature analysis, and data classification via the use of tools such as artificial neural networks (ANN). In this article, we will explore these and other current processes that have come to be referred to as "artificial intelligence." One element of CAD, temporal subtraction, has been applied for enhancing interval changes and for suppressing unchanged structures (eg, normal structures) between 2 successive radiologic images. To reduce misregistration artifacts on the temporal subtraction images, a nonlinear image warping technique for matching the previous image to the current one has been developed. Development of the temporal subtraction method originated with chest radiographs, with the method subsequently being applied to chest computed tomography (CT) and nuclear medicine bone scans. The usefulness of the temporal subtraction method for bone scans was demonstrated by an observer study in which reading times and diagnostic accuracy improved significantly. An additional prospective clinical study verified that the temporal subtraction image could be used as a "second opinion" by radiologists with negligible detrimental effects. ANN was first used in 1990 for computerized differential diagnosis of interstitial lung diseases in CAD. Since then, ANN has been widely used in CAD schemes for the detection and diagnosis of various diseases in different imaging modalities, including the differential diagnosis of lung nodules and interstitial lung diseases in chest radiography, CT, and position emission tomography/CT. It is likely that CAD will be integrated into picture archiving and

  15. A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

    Science.gov (United States)

    Hancock, Thomas M., III

    1994-01-01

    This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

  16. Promising synergies of simulation model management, software engineering, artificial intelligence, and general system theories

    Energy Technology Data Exchange (ETDEWEB)

    Oren, T.I.

    1982-01-01

    Simulation is viewed within the model management paradigm. Major components of simulation systems as well as elements of model management are outlined. Possible synergies of simulation model management, software engineering, artificial intelligence, and general system theories are systematized. 21 references.

  17. Analysis of artificial intelligence application%人工智能应用分析

    Institute of Scientific and Technical Information of China (English)

    韦燕

    2013-01-01

    With the rapid development of computer technology, artificial intelligence is applied more and more widely.This paper analyzes the specific application of the artificial intelligence from several aspects.%  随着计算机技术的快速发展,人工智能的应用越来越广泛。本文分别从几个方面对人工智能的具体应用进行分析。

  18. The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1995-01-01

    This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  19. On the Future Possibilities of Artificial Intelligence Based M-Learning Content Development

    OpenAIRE

    KÖSE, Utku; TÜFEKÇİ, Aslıhan

    2015-01-01

    Abstract—Artificial Intelligence is widely used in almost every field of the modern life; in order to provide effective solutions for real-world problems. It can be definitely said that this research field has a remarkable power on shaping the future of the humankind. When we take today's technologies into consideration, it is also seen that usage of Artificial Intelligence and mobile applications together is a key element for many future applications. At this point, main objective of this st...

  20. Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program

    OpenAIRE

    Achtner, Wolfgang; Aimeur , Esma; Anand, Sarabjot Singh; Appelt, Doug; Ashish, Naveen; Barnes, Tiffany; Beck, Joseph E.; Dias, M. Bernardine; Doshi, Prashant; Drummond, Chris; Elazmeh, William; Felner, Ariel; Freitag, Dayne; Geffner, Hector; Geib, Christopher W.

    2006-01-01

    The Workshop program of the Twenty-First Conference on Artificial Intelligence was held July 16-17, 2006 in Boston, Massachusetts. The program was chaired by Joyce Chai and Keith Decker. The titles of the 17 workshops were AIDriven Technologies for Service-Oriented Computing; Auction Mechanisms for Robot Coordination; Cognitive Modeling and Agent-Based Social Simulations, Cognitive Robotics; Computational Aesthetics: Artificial Intelligence Approaches to Beauty and Happiness; Educational Data...

  1. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  2. Cognitive communications distributed artificial intelligence (DAI), regulatory policy and economics, implementation

    CERN Document Server

    Grace, David

    2012-01-01

    This book discusses in-depth the concept of distributed artificial intelligence (DAI) and its application to cognitive communications In this book, the authors present an overview of cognitive communications, encompassing both cognitive radio and cognitive networks, and also other application areas such as cognitive acoustics. The book also explains the specific rationale for the integration of different forms of distributed artificial intelligence into cognitive communications, something which is often neglected in many forms of technical contributions available today. Furthermore, t

  3. Enhancing nuclear power plant performance through the use of artificial intelligence

    International Nuclear Information System (INIS)

    The objective of this research was to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important objective, was to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants

  4. Applying artificial intelligence to clinical guidelines: the GLARE approach.

    Science.gov (United States)

    Terenziani, Paolo; Montani, Stefania; Bottrighi, Alessio; Molino, Gianpaolo; Torchio, Mauro

    2008-01-01

    We present GLARE, a domain-independent system for acquiring, representing and executing clinical guidelines (GL). GLARE is characterized by the adoption of Artificial Intelligence (AI) techniques in the definition and implementation of the system. First of all, a high-level and user-friendly knowledge representation language has been designed. Second, a user-friendly acquisition tool, which provides expert physicians with various forms of help, has been implemented. Third, a tool for executing GL on a specific patient has been made available. At all the levels above, advanced AI techniques have been exploited, in order to enhance flexibility and user-friendliness and to provide decision support. Specifically, this chapter focuses on the methods we have developed in order to cope with (i) automatic resource-based adaptation of GL, (ii) representation and reasoning about temporal constraints in GL, (iii) decision making support, and (iv) model-based verification. We stress that, although we have devised such techniques within the GLARE project, they are mostly system-independent, so that they might be applied to other guideline management systems.

  5. Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    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 the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

  6. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Science.gov (United States)

    Wali, W. A.; Hassan, K. H.; Cullen, J. D.; Al-Shamma'a, A. I.; Shaw, A.; Wylie, S. R.

    2011-08-01

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  7. Artificial intelligence in the service of system administrators

    International Nuclear Information System (INIS)

    The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an “object oriented paradigm” architecture should increase our learning speed a lot and highlight relations between problems.

  8. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    International Nuclear Information System (INIS)

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  9. Spike: Artificial intelligence scheduling for Hubble space telescope

    Science.gov (United States)

    Johnston, Mark; Miller, Glenn; Sponsler, Jeff; Vick, Shon; Jackson, Robert

    1990-01-01

    Efficient utilization of spacecraft resources is essential, but the accompanying scheduling problems are often computationally intractable and are difficult to approximate because of the presence of numerous interacting constraints. Artificial intelligence techniques were applied to the scheduling of the NASA/ESA Hubble Space Telescope (HST). This presents a particularly challenging problem since a yearlong observing program can contain some tens of thousands of exposures which are subject to a large number of scientific, operational, spacecraft, and environmental constraints. New techniques were developed for machine reasoning about scheduling constraints and goals, especially in cases where uncertainty is an important scheduling consideration and where resolving conflicts among conflicting preferences is essential. These technique were utilized in a set of workstation based scheduling tools (Spike) for HST. Graphical displays of activities, constraints, and schedules are an important feature of the system. High level scheduling strategies using both rule based and neural network approaches were developed. While the specific constraints implemented are those most relevant to HST, the framework developed is far more general and could easily handle other kinds of scheduling problems. The concept and implementation of the Spike system are described along with some experiments in adapting Spike to other spacecraft scheduling domains.

  10. An artificial intelligence system for computer-assisted menu planning.

    Science.gov (United States)

    Petot, G J; Marling, C; Sterling, L

    1998-09-01

    Planning nutritious and appetizing menus is a complex task that researchers have tried to computerize since the early 1960s. We have attempted to facilitate computer-assisted menu planning by modeling the reasoning an expert dietitian uses to plan menus. Two independent expert systems were built, each designed to plan a daily menu meeting the nutrition needs and personal preferences of an individual client. One system modeled rule-based, or logical, reasoning, whereas the other modeled case-based, or experiential, reasoning. The 2 systems were evaluated and their strengths and weaknesses identified. A hybrid system was built, combining the best of both systems. The hybrid system represents an important step forward because it plans daily menus in accordance with a person's needs and preferences; the Reference Daily Intakes; the Dietary Guidelines for Americans; and accepted aesthetic standards for color, texture, temperature, taste, and variety. Additional work to expand the system's scope and to enhance the user interface will be needed to make it a practical tool. Our system framework could be applied to special-purpose menu planning for patients in medical settings or adapted for institutional use. We conclude that an artificial intelligence approach has practical use for computer-assisted menu planning. PMID:9739801

  11. Artificial intelligence in the service of system administrators

    Science.gov (United States)

    Haen, C.; Barra, V.; Bonaccorsi, E.; Neufeld, N.

    2012-12-01

    The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an “object oriented paradigm” architecture should increase our learning speed a lot and highlight relations between problems.

  12. Macrocell path loss prediction using artificial intelligence techniques

    Science.gov (United States)

    Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

    2014-04-01

    The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

  13. Using artificial intelligence methods to design new conducting polymers

    Directory of Open Access Journals (Sweden)

    Ronaldo Giro

    2003-12-01

    Full Text Available In the last years the possibility of creating new conducting polymers exploring the concept of copolymerization (different structural monomeric units has attracted much attention from experimental and theoretical points of view. Due to the rich carbon reactivity an almost infinite number of new structures is possible and the procedure of trial and error has been the rule. In this work we have used a methodology able of generating new structures with pre-specified properties. It combines the use of negative factor counting (NFC technique with artificial intelligence methods (genetic algorithms - GAs. We present the results for a case study for poly(phenylenesulfide phenyleneamine (PPSA, a copolymer formed by combination of homopolymers: polyaniline (PANI and polyphenylenesulfide (PPS. The methodology was successfully applied to the problem of obtaining binary up to quinternary disordered polymeric alloys with a pre-specific gap value or exhibiting metallic properties. It is completely general and can be in principle adapted to the design of new classes of materials with pre-specified properties.

  14. Parameter tuning of PVD process based on artificial intelligence technique

    Science.gov (United States)

    Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.

    2016-07-01

    In this study, an artificial intelligence technique is proposed to be implemented in the parameter tuning of a PVD process. Due to its previous adaptation in similar optimization problems, genetic algorithm (GA) is selected to optimize the parameter tuning of the RF magnetron sputtering process. The most optimized parameter combination obtained from GA's optimization result is expected to produce the desirable zinc oxide (ZnO) thin film from the sputtering process. The parameters involved in this study were RF power, deposition time and substrate temperature. The algorithm was tested to optimize the 25 datasets of parameter combinations. The results from the computational experiment were then compared with the actual result from the laboratory experiment. Based on the comparison, GA had shown that the algorithm was reliable to optimize the parameter combination before the parameter tuning could be done to the RF magnetron sputtering machine. In order to verify the result of GA, the algorithm was also been compared to other well known optimization algorithms, which were, particle swarm optimization (PSO) and gravitational search algorithm (GSA). The results had shown that GA was reliable in solving this RF magnetron sputtering process parameter tuning problem. GA had shown better accuracy in the optimization based on the fitness evaluation.

  15. Text Analytics: the convergence of Big Data and Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Antonio Moreno

    2016-03-01

    Full Text Available The analysis of the text content in emails, blogs, tweets, forums and other forms of textual communication constitutes what we call text analytics. Text analytics is applicable to most industries: it can help analyze millions of emails; you can analyze customers’ comments and questions in forums; you can perform sentiment analysis using text analytics by measuring positive or negative perceptions of a company, brand, or product. Text Analytics has also been called text mining, and is a subcategory of the Natural Language Processing (NLP field, which is one of the founding branches of Artificial Intelligence, back in the 1950s, when an interest in understanding text originally developed. Currently Text Analytics is often considered as the next step in Big Data analysis. Text Analytics has a number of subdivisions: Information Extraction, Named Entity Recognition, Semantic Web annotated domain’s representation, and many more. Several techniques are currently used and some of them have gained a lot of attention, such as Machine Learning, to show a semisupervised enhancement of systems, but they also present a number of limitations which make them not always the only or the best choice. We conclude with current and near future applications of Text Analytics.

  16. Artificial Intelligence SVC Based Control of Two Machine Transmission System

    Directory of Open Access Journals (Sweden)

    Reza Bayat

    2013-07-01

    Full Text Available The main target in this paper is to present, design fuzzy logic controller (FLC applied to static var compensator (SVC on two machine transmission system to improve transient stability and rapid damping oscillations of synchronous generators, when power generators sudden changes occur.stability that also played important role in power systems. static var compensator with fuzzy logic controller (SVCFLC is a new control strategy can help improve transient stability.The effect of three phase fault causes instability on power system. By and large, it is very difficult to control machine speeds ,rotor angle and voltage during three-phase fault.SVCFLC is a voltage stablizer using three static var compensator which are controlled by SVC with fuzzy logic controller(FLC.The FLC is an effective device for transient stability of two-mashine transmission system. The nonlinear model dynamic formulation problem in unstable system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to improve the system stability . simulation results of three-phase fault in power system show that SVCFLC caused to increase the stability and damp out the oscillation of machine, compared with effective of SVC in the presence of power system stabilizer(PSS.

  17. Crack identification based on synthetic artificial intelligent technique

    Energy Technology Data Exchange (ETDEWEB)

    Shim, Mun Bo; Suh, Myung Won [Sungkyunkwan Univ., Suwon (Korea, Republic of)

    2001-07-01

    It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

  18. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Wali, W A; Hassan, K H; Cullen, J D; Al-Shamma' a, A I; Shaw, A; Wylie, S R, E-mail: w.wali@2009.ljmu.ac.uk [Built Environment and Sustainable Technologies Institute (BEST), School of the Built Environment, Faculty of Technology and Environment Liverpool John Moores University, Byrom Street, Liverpool L3 3AF (United Kingdom)

    2011-08-17

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  19. Implementing embedded artificial intelligence rules within algorithmic programming languages

    Science.gov (United States)

    Feyock, Stefan

    1988-01-01

    Most integrations of artificial intelligence (AI) capabilities with non-AI (usually FORTRAN-based) application programs require the latter to execute separately to run as a subprogram or, at best, as a coroutine, of the AI system. In many cases, this organization is unacceptable; instead, the requirement is for an AI facility that runs in embedded mode; i.e., is called as subprogram by the application program. The design and implementation of a Prolog-based AI capability that can be invoked in embedded mode are described. The significance of this system is twofold: Provision of Prolog-based symbol-manipulation and deduction facilities makes a powerful symbolic reasoning mechanism available to applications programs written in non-AI languages. The power of the deductive and non-procedural descriptive capabilities of Prolog, which allow the user to describe the problem to be solved, rather than the solution, is to a large extent vitiated by the absence of the standard control structures provided by other languages. Embedding invocations of Prolog rule bases in programs written in non-AI languages makes it possible to put Prolog calls inside DO loops and similar control constructs. The resulting merger of non-AI and AI languages thus results in a symbiotic system in which the advantages of both programming systems are retained, and their deficiencies largely remedied.

  20. On the track of Artificial Intelligence: Learning with Intelligent Personal Assistants

    Directory of Open Access Journals (Sweden)

    Nil Goksel Canbek

    2016-01-01

    Full Text Available In a technology dominated world, useful and timely information can be accessed quickly via Intelligent Personal Assistants (IPAs.  By the use of these assistants built into mobile operating systems, daily electronic tasks of a user can be accomplished 24/7. Such tasks like taking dictation, getting turn-by-turn directions, vocalizing email messages, reminding daily appointments, setting reminders, responding any factual questions and invoking apps can be completed by  IPAs such as Apple’s Siri, Google Now and Microsoft Cortana. The mentioned assistants programmed within Artificial Intelligence (AI do create an interaction between human and computer through a natural language used in digital communication. In this regard, the overall purpose of this study is to examine the potential use of IPAs that use advanced cognitive computing technologies and Natural Language Processing (NLP for learning. To achieve this purpose, the working system of IPAs is reviewed briefly within the scope of AI that has recently become smarter to predict, comprehend and carry out multi-step and complex requests of users.

  1. Artificial intelligence and virtual environment application for materials design methodology

    Directory of Open Access Journals (Sweden)

    L.A. Dobrzański

    2010-10-01

    Full Text Available Purpose: The purpose of this study is to develop a methodology for material design, enabling the selection of the chemical elements concentration, heat and plastic treatment conditions and geometrical dimensions to ensure the required mechanical properties of structural steels specified by the designer of machinery and equipment as the basis for the design of material components manufactured from these steels, by using a computational model developed with use of artificial intelligence methods and virtual environment. The model is designed to provide impact examinations of these factors on the mechanical properties of steel only in the computing environment.Design/methodology/approach: A virtual research environment built with use of computational model describing relationships between chemical composition, heat and plastic treatment conditions and product geometric dimensions and mechanical properties of the examined group of steel was developed and practical applied. This model enables the design of new structural steel by setting the values of mechanical properties based on material production descriptors and allows the selection of production descriptors on the basis of the mechanical properties without the need for additional tests or experimental studies in reality.Findings: Virtual computing environment allows full usage of the developed intelligent model of non-alloy and alloy structural steel properties and provides an easy, intuitive and user-friendly way to designate manufacturing descriptors and mechanical properties for products.Research limitations/implications:The proposed solutions allow the usage of developed virtual environment as a new medium in both, the scientific work performed remotely, as well as in education during classes.Practical implications: The new material design methodology has practical application in the development of materials and modelling of steel descriptors in aim to improve the mechanical properties and

  2. 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

  3. Artificial Intelligence and the Brave New World of Eclipsing Binaries

    Science.gov (United States)

    Devinney, E.; Guinan, E.; Bradstreet, D.; DeGeorge, M.; Giammarco, J.; Alcock, C.; Engle, S.

    2005-12-01

    The explosive growth of observational capabilities and information technology over the past decade has brought astronomy to a tipping point - we are going to be deluged by a virtual fire hose (more like Niagara Falls!) of data. An important component of this deluge will be newly discovered eclipsing binary stars (EBs) and other valuable variable stars. As exploration of the Local Group Galaxies grows via current and new ground-based and satellite programs, the number of EBs is expected to grow explosively from some 10,000 today to 8 million as GAIA comes online. These observational advances will present a unique opportunity to study the properties of EBs formed in galaxies with vastly different dynamical, star formation, and chemical histories than our home Galaxy. Thus the study of these binaries (e.g., from light curve analyses) is expected to provide clues about the star formation rates and dynamics of their host galaxies as well as the possible effects of varying chemical abundance on stellar evolution and structure. Additionally, minimal-assumption-based distances to Local Group objects (and possibly 3-D mapping within these objects) shall be returned. These huge datasets of binary stars will provide tests of current theories (or suggest new theories) regarding binary star formation and evolution. However, these enormous data will far exceed the capabilities of analysis via human examination. To meet the daunting challenge of successfully mining this vast potential of EBs and variable stars for astrophysical results with minimum human intervention, we are developing new data processing techniques and methodologies. Faced with an overwhelming volume of data, our goal is to integrate technologies of Machine Learning and Pattern Processing (Artificial Intelligence [AI]) into the data processing pipelines of the major current and future ground- and space-based observational programs. Data pipelines of the future will have to carry us from observations to

  4. Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks

    OpenAIRE

    Nabil Ali Alrajeh; Lloret, J

    2013-01-01

    Intrusion detection system (IDS) is regarded as the second line of defense against network anomalies and threats. IDS plays an important role in network security. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are widely used for threats detection. This paper presents a critical study on genetic algorithm, artificial immune, and artificial neural network (ANN) based IDSs techniques used in wireless sensor netw...

  5. Investment Process in China's Mutual Funds and Application of Artificial Intelligence

    OpenAIRE

    Xie, Ningjia

    2008-01-01

    This paper explored the process of investment management in both theory and practice in China's mutual fund industry and reviewed the applications of artificial intelligence including Rule-based Expert Systems, Genetic Algorithms, Artificial Neural Network, and Support Vector Machines in financial forecasting, asset allocation and stocks selection. This study proposed the use of artificial neural network for stock selection which classifies stocks into undervalued stocks (+1), neutral st...

  6. Evaluation of an artificial intelligence program for estimating occupational exposures.

    Science.gov (United States)

    Johnston, Karen L; Phillips, Margaret L; Esmen, Nurtan A; Hall, Thomas A

    2005-03-01

    Estimation and Assessment of Substance Exposure (EASE) is an artificial intelligence program developed by UK's Health and Safety Executive to assess exposure. EASE computes estimated airborne concentrations based on a substance's vapor pressure and the types of controls in the work area. Though EASE is intended only to make broad predictions of exposure from occupational environments, some occupational hygienists might attempt to use EASE for individual exposure characterizations. This study investigated whether EASE would accurately predict actual sampling results from a chemical manufacturing process. Personal breathing zone time-weighted average (TWA) monitoring data for two volatile organic chemicals--a common solvent (toluene) and a specialty monomer (chloroprene)--present in this manufacturing process were compared to EASE-generated estimates. EASE-estimated concentrations for specific tasks were weighted by task durations reported in the monitoring record to yield TWA estimates from EASE that could be directly compared to the measured TWA data. Two hundred and six chloroprene and toluene full-shift personal samples were selected from eight areas of this manufacturing process. The Spearman correlation between EASE TWA estimates and measured TWA values was 0.55 for chloroprene and 0.44 for toluene, indicating moderate predictive values for both compounds. For toluene, the interquartile range of EASE estimates at least partially overlapped the interquartile range of the measured data distributions in all process areas. The interquartile range of EASE estimates for chloroprene fell above the interquartile range of the measured data distributions in one process area, partially overlapped the third quartile of the measured data in five process areas and fell within the interquartile range in two process areas. EASE is not a substitute for actual exposure monitoring. However, EASE can be used in conditions that cannot otherwise be sampled and in preliminary

  7. Importance of nonverbal expression to the emergence of emotive artificial intelligence systems

    Science.gov (United States)

    Pioggia, Giovanni; Hanson, David; Dinelli, Serena; Di Francesco, Fabio; Francesconi, R.; De Rossi, Danilo

    2002-07-01

    The nonverbal expression of the emotions, especially in the human face, has rapidly become an area of intense interest in computer science and robotics. Exploring the emotions as a link between external events and behavioural responses, artificial intelligence designers and psychologists are approaching a theoretical understanding of foundational principles which will be key to the physical embodiment of artificial intelligence. In fact, it has been well demonstrated that many important aspects of intelligence are grounded in intimate communication with the physical world- so-called embodied intelligence . It follows naturally, then, that recent advances in emotive artificial intelligence show clear and undeniable broadening in the capacities of biologically-inspired robots to survive and thrive in a social environment. The means by which AI may express its foundling emotions are clearly integral to such capacities. In effect: powerful facial expressions are critical to the development of intelligent, sociable robots. Following discussion the importance of the nonverbal expression of emotions in humans and robots, this paper describes methods used in robotically emulating nonverbal expressions using human-like robotic faces. Furthermore, it describes the potentially revolutionary impact of electroactive polymer (EAP) actuators as artificial muscles for such robotic devices.

  8. Cognitive Connected Vehicle Information System Design Requirement for Safety: Role of Bayesian Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Ata Khan

    2013-04-01

    Full Text Available Intelligent transportation systems (ITS are gaining acceptance around the world and the connected vehicle component of ITS is recognized as a high priority research and development area in many technologically advanced countries. Connected vehicles are expected to have the capability of safe, efficient and eco-driving operations whether these are under human control or in the adaptive machine control mode of operations. The race is on to design the capability to operate in connected traffic environment. The operational requirements can be met with cognitive vehicle design features made possible by advances in artificial intelligence-supported methodology, improved understanding of human factors, and advances in communication technology. This paper describes cognitive features and their information system requirements. The architecture of an information system is presented that supports the features of the cognitive connected vehicle. For better focus, information processing capabilities are specified and the role of Bayesian artificial intelligence is defined for data fusion. Example applications illustrate the role of information systems in integrating intelligent technology, Bayesian artificial intelligence, and abstracted human factors. Concluding remarks highlight the role of the information system and Bayesian artificial intelligence in the design of a new generation of cognitive connected vehicle.

  9. Artificial intelligence and design: Opportunities, research problems and directions

    Science.gov (United States)

    Amarel, Saul

    1990-01-01

    The issues of industrial productivity and economic competitiveness are of major significance in the U.S. at present. By advancing the science of design, and by creating a broad computer-based methodology for automating the design of artifacts and of industrial processes, we can attain dramatic improvements in productivity. It is our thesis that developments in computer science, especially in Artificial Intelligence (AI) and in related areas of advanced computing, provide us with a unique opportunity to push beyond the present level of computer aided automation technology and to attain substantial advances in the understanding and mechanization of design processes. To attain these goals, we need to build on top of the present state of AI, and to accelerate research and development in areas that are especially relevant to design problems of realistic complexity. We propose an approach to the special challenges in this area, which combines 'core work' in AI with the development of systems for handling significant design tasks. We discuss the general nature of design problems, the scientific issues involved in studying them with the help of AI approaches, and the methodological/technical issues that one must face in developing AI systems for handling advanced design tasks. Looking at basic work in AI from the perspective of design automation, we identify a number of research problems that need special attention. These include finding solution methods for handling multiple interacting goals, formation problems, problem decompositions, and redesign problems; choosing representations for design problems with emphasis on the concept of a design record; and developing approaches for the acquisition and structuring of domain knowledge with emphasis on finding useful approximations to domain theories. Progress in handling these research problems will have major impact both on our understanding of design processes and their automation, and also on several fundamental questions

  10. Artificial Intelligence, Evolutionary Computing and Metaheuristics In the Footsteps of Alan Turing

    CERN Document Server

    2013-01-01

    Alan Turing pioneered many research areas such as artificial intelligence, computability, heuristics and pattern formation.  Nowadays at the information age, it is hard to imagine how the world would be without computers and the Internet. Without Turing's work, especially the core concept of Turing Machine at the heart of every computer, mobile phone and microchip today, so many things on which we are so dependent would be impossible. 2012 is the Alan Turing year -- a centenary celebration of the life and work of Alan Turing. To celebrate Turing's legacy and follow the footsteps of this brilliant mind, we take this golden opportunity to review the latest developments in areas of artificial intelligence, evolutionary computation and metaheuristics, and all these areas can be traced back to Turing's pioneer work. Topics include Turing test, Turing machine, artificial intelligence, cryptography, software testing, image processing, neural networks, nature-inspired algorithms such as bat algorithm and cuckoo sear...

  11. Proceedings of intelligent engineering systems through artificial neural networks

    International Nuclear Information System (INIS)

    This book contains the edited versions of the technical presentation of ANNIE '91, the first international meeting on Artificial Neural Networks in Engineering. The conference covered the theory of Artificial Neural Networks and its contributions in the engineering domain and attracted researchers from twelve countries. The papers in this edited book are grouped into four categories: Artificial Neural Network Architectures; Pattern Recognition; Adaptive Control, Diagnosis and Process Monitoring; and Neuro-Engineering Systems

  12. The Essential Turing Seminal Writings in Computing, Logic, Philosophy, Artificial Intelligence, and Artificial Life Plus the Secrets of Enigma

    CERN Document Server

    2004-01-01

    The ideas that gave birth to the computer age. Alan Turing, pioneer of computing and WWII codebreaker, was one of the most important and influential thinkers of the twentieth century. In this volume for the first time his key writings are made available to a broad, non-specialist readership. They make fascinating reading both in their own right and for their historic significance: contemporary computational theory, cognitive science, artificial intelligence, and artificial life all spring from this ground-breaking work, which is also rich. in philosophical and logical insight. An introduction

  13. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    International Nuclear Information System (INIS)

    A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

  14. Artificial intelligence applications in the nuclear field: Achievements and prospects: The new challenge

    International Nuclear Information System (INIS)

    The first applications of Artificial Intelligence in the nuclear field were expert systems dedicated to off-line problems of diagnosis and maintenance. A second step aimed at solving more ambitious problems related to plant design and operation, which improved methodologies and tools. By the end of this period, new limits appeared. To solve the problems faced in the late eighties, powerful principles and methods became available. These require extensive sources. The present book describes examples of large-scale applications of Artificial Intelligence in the nuclear field

  15. ARTIFICIAL INTELLIGENCE SELECTION WITH CAPABILITY OF EDITING A NEW PARAMETER FOR EOR SCREENING CRITERIA

    Directory of Open Access Journals (Sweden)

    ELRADI ABASS

    2011-10-01

    Full Text Available This paper describes the application of an Artificial Intelligence (AI technique to assist in the selection of an Enhanced Oil Recovery method (EOR. The structure of an expert systems selection based on a new formulated screening criteria, Artificial Intelligence selection developed by a computer software called (EKORA, with an easily and friendly user interface by using visual Basic-6 environment tools is presented. An additional capability provided by this software is the ability of changing and editing the parameters of EOR methods which emerged or tested in current implementation projects. Other commercial expert systems either offer limited or no capabilities for changing and editing the EOR parameters of screening rule.

  16. International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems

    CERN Document Server

    Dash, Subhransu; Panigrahi, Bijaya

    2015-01-01

      The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

  17. Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

    Science.gov (United States)

    Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

    2010-01-01

    This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…

  18. Inteligência biológica versus inteligência artificial: uma abordagem crítica Biologic intelligence versus artificial intelligence: a critical approach

    Directory of Open Access Journals (Sweden)

    Wilson Luiz Sanvito

    1995-09-01

    Full Text Available Após considerações iniciais sobre inteligência, um estudo comparativo entre inteligência biológica e inteligência artificial é feito. Os especialistas em Inteligência Artificial são de opinião que inteligência é simplesmente uma matéria de manipulação de símbolos físicos. Neste sentido, o objetivo da Inteligência Artificial é entender como a inteligência cerebral funciona em termos de conceitos e técnicas de engenharia. De modo diverso os filósofos da ciência acreditam que os computadores podem ter uma sintaxe, porém não têm uma semântica. No presente trabalho é ressaltado que o complexo cérebro/mente constitui um sistema monolítico, que funciona com funções emergentes em vários níveis de organização hierárquica. Esses níveis hierárquicos não são redutíveis um ao outro. Eles são, no mínimo, três (neuronal, funcional e semântico e funcionam dentro de um plano interacional. Do ponto de vista epistemológico, o complexo cérebro/mente se utiliza de mecanismos lógicos e não-lógicos para lidar com os problemas do dia-a-dia. A lógica é necessária para o processo do pensamento, porém não é suficiente. Ênfase é dada aos mecanismos não-lógicos (lógica nebulosa, heurística, raciocínio intuitivo, os quais permitem à mente desenvolver estratégias para encontrar soluções.After brief considerations about intelligence, a comparative study between biologic and artificial intelligence is made. The specialists in Artificial Intelligence found that intelligence is purely a matter of physical symbol manipulation. The enterprise of Artificial Intelligence aims to understand what we might call Brain Intelligence in terms of concepts and techniques of engineering. However the philosophers believed that computer-machine can have syntax, but can never have semantics. In other words, that they can follow rules, such as those of arithmetic or grammar, but not understand what to us are meanings of symbols

  19. An Analysis of Artificial Intelligence in Machines & Chinese Room Problem

    Directory of Open Access Journals (Sweden)

    Priyanka Yedluri

    2013-12-01

    Full Text Available The success of machines over the last few decades inperforming tasks that were seeming impossible for humans toperform led to the discussion that can machines be madeintelligent. The argument was based on the fact that there was nounderstanding and the computer merely followed human etc. isnot a new one. The question evokes deep programmed ruleswithout any consciousness. The other side countered that anargument like that was arguable, since the results were as ifproduced by an intelligent being and had meaning, the computerhas produced proof of intelligence. In this paper, we wouldanalyze the arguments of both the sides and present a clearerpicture of the capabilities of machine. We'll begin by explainingthe Turing test, a criteria to test the intelligence of a machine andthen move to discuss Chinese room problem and its implications.I will be highlighting the objections raised against these problemsand my own answers to these arguments.

  20. Guidance for human interface with artificial intelligence systems

    Science.gov (United States)

    Potter, Scott S.; Woods, David D.

    1991-01-01

    The beginning of a research effort to collect and integrate existing research findings about how to combine computer power and people is discussed, including problems and pitfalls as well as desirable features. The goal of the research is to develop guidance for the design of human interfaces with intelligent systems. Fault management tasks in NASA domains are the focus of the investigation. Research is being conducted to support the development of guidance for designers that will enable them to make human interface considerations into account during the creation of intelligent systems.

  1. Artificial Intelligence Tools for Grammar and Spelling Instruction.

    Science.gov (United States)

    Pijls, Fieny; And Others

    1987-01-01

    Discusses grammar and spelling instruction in The Netherlands for students aged 10-15 and describes an intelligent computer-assisted instructional environment consisting of a linguistic expert system, a didactic module, and a student interface. Three prototypes are described: BOUWSTEEN and COGO for analyzing sentences, and TDTDT for conjugating…

  2. Synthesis and Analysis in Artificial Intelligence: The Role of Theory in Agent Implementation

    NARCIS (Netherlands)

    Raine, Roxanne B.; Akker, op den Rieks; Cai, Zhiqiang; Graesser, Arthur C.; McNamara, Danielle S.

    2009-01-01

    The domain of artificial intelligence (AI) progresses with extraordinary vicissitude. Whereas prior authors have divided AI into the two categories of analysis and synthesis, Raine and op den Akker distinguish between four types of AI: that of appearance, function, simulation and interpretation. The

  3. ICCE/ICCAI 2000 Full & Short Papers (Artificial Intelligence in Education).

    Science.gov (United States)

    2000

    This document contains the full and short papers on artificial intelligence in education from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction) covering the following topics: a computational model for learners' motivation states in individualized tutoring system; a…

  4. Artificial Intelligence in Education--State of the Art and Perspectives. ZIFF Papiere 111.

    Science.gov (United States)

    Buiu, Catalin

    This review contains an overview of past and present trends in the application of what is called "artificial intelligence" in traditional face-to-face education and in distance education. The reviewed trends are illustrated with examples of research projects and results throughout the world. The first section of the review discusses intelligence…

  5. The Roles of Artificial Intelligence in Education: Current Progress and Future Prospects

    Science.gov (United States)

    McArthur, David; Lewis, Matthew; Bishary, Miriam

    2005-01-01

    This report begins by summarizing current applications of ideas from artificial intelligence (Al) to education. It then uses that summary to project various future applications of Al--and advanced technology in general--to education, as well as highlighting problems that will confront the wide­ scale implementation of these technologies in the…

  6. Artificial intelligence in process control: Knowledge base for the shuttle ECS model

    Science.gov (United States)

    Stiffler, A. Kent

    1989-01-01

    The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

  7. The application and developments for the artificial intelligence in the nuclear engineering

    International Nuclear Information System (INIS)

    The general situations of the research developing artificial intelligence in the nuclear engineering are introduced, and the expert systems and its developing direction which include the failure diagnosis, control and operation, maintenance, alarm and display, accident management for nuclear reactors and the robots are briefly discussed

  8. Artificial intelligence to maximise contributions of nondestructive evaluation to materials science and technology

    International Nuclear Information System (INIS)

    The paper reviews the current status of Nondestructive Testing and Evaluation (NDT and E), in relation to materials science and technology. It suggests a path of growth for Nondestructive Testing and Evaluation, taking into account the increase in data and knowledge. We recommend Artificial Intelligence (AI) concepts for maximising the contributions of and benefits from, Nondestructive Testing and Evaluation. (author)

  9. The application of artificial intelligence chemistry diagnostic system to nuclear power plants

    International Nuclear Information System (INIS)

    By processing water chemistry data to diagnose sensor and equipment malfunctions in realtime, artificial intelligence chemistry diagnostic system helps to reduce the plant downtime due to steam generator tubing failures and other accidents. A typical processing system of water chemistry data is presented

  10. Keeping Pace with New Technology: An Introduction to Robotics, FORTH, and Artificial Intelligence.

    Science.gov (United States)

    Reck, Gene

    A course was developed to introduce students at a community college to four major areas of emphasis in emerging technologies: FORTH programming language, elementary electronic theory, robotics, and artificial intelligence. After a needs assessment indicated the importance of such a course, a pretest focusing on the four areas was given to students…

  11. Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

    Science.gov (United States)

    Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

    1995-01-01

    This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system.

  12. Recap of the Seventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE)

    OpenAIRE

    Bulitko, Vadim; University of Alberta; Riedl, Mark; Georgia Institute of Technology; Jhala, Arnav; University of California, Santa Cruz; Buro, Michael; University of Alberta; Sturtevant, Nathan; University of Denver

    2012-01-01

    The Seventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment was held from October 11–14, 2011, on the campus of Stanford University near Palo Alto, California. The conference featured a research track, an industry track, a demo program, and three one-day workshops. This report summarizes the conference and related activities.

  13. Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

    Science.gov (United States)

    Swanson, David J.

    1990-01-01

    The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

  14. Research in Progress at the Massachusetts Institute of Technology Artificial Intelligence Laboratory

    OpenAIRE

    Horn, Berthold K. P.; Marr, David; Hollerbach, John; Sussman, Gerald J.; Winston, Patrick H.; Davis, Randall; Minsky, Marvin L.

    1980-01-01

    The MIT AI Laboratory has a long tradition of research in most aspects of Artificial Intelligence. Currently, the major foci include computer vision, manipulation, learning, English-language understanding, VLSI design, expert engineering problem solving, common-sense reasoning, computer architecture, distributed problem solving, models of human memory, programmer apprentices, and human education.

  15. Installation and evaluation of a nuclear power plant operator advisor based on artificial intelligence technology

    International Nuclear Information System (INIS)

    This report discusses the following topics on a Nuclear Power Plant operator advisor based on artificial Intelligence Technology; Workstation conversion; Software Conversion; V ampersand V Program Development Development; Simulator Interface Development; Knowledge Base Expansion; Dynamic Testing; Database Conversion; Installation at the Perry Simulator; Evaluation of Operator Interaction; Design of Man-Machine Interface; and Design of Maintenance Facility

  16. Artificial Intelligence and Language Development and Language Usage with the Deaf.

    Science.gov (United States)

    Leach, John Mark

    The paper reviews research on the application of artificial intelligence (AI) in language development and/or instruction with the deaf. Contributions of computer assisted instruction are noted, as are the problems resulting from over-dependence on a drill and practice format and from deaf students' difficulties in receiving and understanding new…

  17. RESEARCH AREA -- ARTIFICIAL INTELLIGENCE CONTROL (AIR POLLUTION TECHNOLOGY BRANCH, AIR POLLUTION PREVENTION AND CONTROL DIVISION, NRMRL)

    Science.gov (United States)

    The Air Pollution Technology Branch (APTB) of NRMRL's Air Pollution Prevention and Control Division in Research Triangle Park, NC, has conducted several research projects for evaluating the use of artificial intelligence (AI) to improve the control of pollution control systems an...

  18. Strategy and Business Planning for Artificial Intelligence Companies: A Guide for Entrepreneurs

    OpenAIRE

    Friedenberg, Robert A.; Hensler, Ralph L.

    1986-01-01

    This article provides some basic assistance to entrepreneurs involved in artificial intelligence, offering a synthesis of standard business-planning and capital-raising practices. Three main areas are discussed: (1) developing a corporate strategy, (2) developing a business plan that works, and (3) approaching sources of capital.

  19. An Artificial Intelligence Tutor: A Supplementary Tool for Teaching and Practicing Braille

    Science.gov (United States)

    McCarthy, Tessa; Rosenblum, L. Penny; Johnson, Benny G.; Dittel, Jeffrey; Kearns, Devin M.

    2016-01-01

    Introduction: This study evaluated the usability and effectiveness of an artificial intelligence Braille Tutor designed to supplement the instruction of students with visual impairments as they learned to write braille contractions. Methods: A mixed-methods design was used, which incorporated a single-subject, adapted alternating treatments design…

  20. Artificial intelligence and finite element modelling for monitoring flood defence structures

    NARCIS (Netherlands)

    Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

    2011-01-01

    We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the Urba

  1. Scientific approaches and techniques for negotiation : a game theoretic and artificial intelligence perspective

    NARCIS (Netherlands)

    Gerding, E.H.; Bragt, D.D.B. van; La Poutré, J.A.

    2000-01-01

    Due to the rapid growth of electronic environments (such as the Internet) much research is currently being performed on autonomous trading mechanisms. This report contains an overview of the current literature on negotiations in the fields of game theory and artificial intelligence (AI). Game theori

  2. A 3D visible evaluation of landslide risk degree under integration of GIS and artificial intelligence

    Institute of Scientific and Technical Information of China (English)

    QIAO; Jianping; ZHU; Axing; CHEN; Yongbo; WANG; Rongxun

    2003-01-01

    Artificial intelligence has been used to obtain background factors (basic environmental factors) from landslide specialists. A 3D visible evaluation map may be charted by fuzzy evaluation, and the traditional plane map may be decoded into a 3D map by using factor weight from specialists system and technology of RS and GIS for quantitative sampling of these factors.

  3. Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

    Science.gov (United States)

    Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

    Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

  4. Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network.

    Science.gov (United States)

    Jahidin, A H; Megat Ali, M S A; Taib, M N; Tahir, N Md; Yassin, I M; Lias, S

    2014-04-01

    This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies.

  5. Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

    Science.gov (United States)

    1994-01-01

    The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments.

  6. Optimal fuel loading pattern design using artificial intelligence techniques

    International Nuclear Information System (INIS)

    The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (Author)

  7. A comparative study of artificial intelligent-based maximum power point tracking for photovoltaic systems

    Science.gov (United States)

    Hussain Mutlag, Ammar; Mohamed, Azah; Shareef, Hussain

    2016-03-01

    Maximum power point tracking (MPPT) is normally required to improve the performance of photovoltaic (PV) systems. This paper presents artificial intelligent-based maximum power point tracking (AI-MPPT) by considering three artificial intelligent techniques, namely, artificial neural network (ANN), adaptive neuro fuzzy inference system with seven triangular fuzzy sets (7-tri), and adaptive neuro fuzzy inference system with seven gbell fuzzy sets. The AI-MPPT is designed for the 25 SolarTIFSTF-120P6 PV panels, with the capacity of 3 kW peak. A complete PV system is modelled using 300,000 data samples and simulated in the MATLAB/SIMULINK. The AI-MPPT has been tested under real environmental conditions for two days from 8 am to 18 pm. The results showed that the ANN based MPPT gives the most accurate performance and then followed by the 7-tri-based MPPT.

  8. On introduction of artificial intelligence elements to heat power engineering

    Science.gov (United States)

    Dregalin, A. F.; Nazyrova, R. R.

    1993-10-01

    The basic problems of 'the thermodynamic intelligence' of personal computers have been outlined. The thermodynamic intellect of personal computers as a concept has been introduced to heat processes occurring in engines of flying vehicles. In particular, the thermodynamic intellect of computers is determined by the possibility of deriving formal relationships between thermodynamic functions. In chemical thermodynamics, a concept of a characteristic function has been introduced.

  9. Hybrid Systems for Knowledge Representation in Artificial Intelligence

    OpenAIRE

    Rajeswari P.V N; Prasad, Dr. T. V

    2012-01-01

    There are few knowledge representation (KR) techniques available for efficiently representing knowledge. However, with the increase in complexity, better methods are needed. Some researchers came up with hybrid mechanisms by combining two or more methods. In an effort to construct an intelligent computer system, a primary consideration is to represent large amounts of knowledge in a way that allows effective use and efficiently organizing information to facilitate making the recommended infer...

  10. An Artificial Intelligence Approach for Gears Diagnostics in AUVs

    OpenAIRE

    Graciliano Nicolás Marichal; María Lourdes Del Castillo; Jesús López; Isidro Padrón; Mariano Artés

    2016-01-01

    In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few st...

  11. Hybrid Systems for Knowledge Representation in Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Rajeswari P.V N

    2012-11-01

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

  12. An Integrated Conceptual Environment based on Collective Intelligence and Distributed Artificial Intelligence for Connecting People on Problem Solving

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2012-12-01

    Full Text Available This paper aims to analyze the different forms of intelligence within organizations in a systemic and inclusive vision, in order to conceptualize an integrated environment based on Distributed Artificial Intelligence (DAI and Collective Intelligence (CI. In this way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. The best way to use collective intelligence is based on knowledge mobilization and semantic technologies. We must not let computers to imitate people but to support people think and develop their ideas within a group. CI helps people to think together, while DAI tries to support people so as to limit human error. Within an organization, to manage CI is to combine instruments like Semantic Technologies (STs, knowledge mobilization methods for developing Knowledge Management (KM strategies, and the processes that promote connection and collaboration between individual minds in order to achieve collective objectives, to perform a task or to solve increasingly economic complex problems.

  13. A genetic-neural artificial intelligence approach to resins optimization; Uma metodologia baseada em inteligencia artificial para otimizacao de resinas

    Energy Technology Data Exchange (ETDEWEB)

    Cabral, Denise C.; Barros, Marcio P.; Lapa, Celso M.F.; Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]. E-mail: lapa@ien.gov.br; mbarros@ien.gov.br

    2005-07-01

    This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

  14. Continuous surveillance of transformers using artificial intelligence methods; Surveillance continue des transformateurs: application des methodes d'intelligence artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Schenk, A.; Germond, A. [Ecole Polytechnique Federale de Lausanne, Lausanne (Switzerland); Boss, P.; Lorin, P. [ABB Secheron SA, Geneve (Switzerland)

    2000-07-01

    The article describes a new method for the continuous surveillance of power transformers based on the application of artificial intelligence (AI) techniques. An experimental pilot project on a specially equipped, strategically important power transformer is described. Traditional surveillance methods and the use of mathematical models for the prediction of faults are described. The article describes the monitoring equipment used in the pilot project and the AI principles such as self-organising maps that are applied. The results obtained from the pilot project and methods for their graphical representation are discussed.

  15. Applicability of artificial intelligence to reservoir induced earthquakes

    Science.gov (United States)

    Samui, Pijush; Kim, Dookie

    2014-06-01

    This paper proposes to use least square support vector machine (LSSVM) and relevance vector machine (RVM) for prediction of the magnitude (M) of induced earthquakes based on reservoir parameters. Comprehensive parameter (E) and maximum reservoir depth (H) are used as input variables of the LSSVM and RVM. The output of the LSSVM and RVM is M. Equations have been presented based on the developed LSSVM and RVM. The developed RVM also gives variance of the predicted M. A comparative study has been carried out between the developed LSSVM, RVM, artificial neural network (ANN), and linear regression models. Finally, the results demonstrate the effectiveness and efficiency of the LSSVM and RVM models.

  16. Natural and artificial intelligence misconceptions about brains and neural networks

    CERN Document Server

    de Callataÿ, A

    1992-01-01

    How does the mind work? How is data stored in the brain? How does the mental world connect with the physical world? The hybrid system developed in this book shows a radically new view on the brain. Briefly, in this model memory remains permanent by changing the homeostasis rebuilding the neuronal organelles. These transformations are approximately abstracted as all-or-none operations. Thus the computer-like neural systems become plausible biological models. This illustrated book shows how artificial animals with such brains learn invariant methods of behavior control from their repeated action

  17. ARTIFICIAL INTELLIGENCE PLANNING TECHNIQUES FOR ADAPTIVE VIRTUAL COURSE CONSTRUCTION

    Directory of Open Access Journals (Sweden)

    NÉSTOR DARÍO DUQUE

    2011-01-01

    Full Text Available El artículo tiene como objetivo proponer un modelo de planificación para la adaptación de cursos virtuales, basado en técnicas de inteligencia artificial, en particular usando el enfoque de sistema multi-agente (SMA y métodos de planificación en inteligencia artificial. El diseño y la implementación por medio de un SMA pedagógico y la definición de un framework para especificar la estrategia de adaptación permiten incorporar diversos enfoques pedagógicos y tecnológicos, de acuerdo a los puntos de vista del equipo de trabajo, lo cual resulta en una implementación e instalación concreta. Se incorpora un novedoso pre-planificador que permite la transparencia y la neutralidad en el modelo propuesto y también ofrece soporte para traducir los elementos del curso a las especificaciones de un problema de planificación. La última sección muestra la plataforma experimental SICAD + (Sistema Inteligente de Cursos ADaptativos, a través de un enfoque multiagente, que valida el modelo propuesto.

  18. Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2013-08-01

    Full Text Available This research involved developing a surgical robot assistant using an articulated PUMA robot running on a linear or nonlinear axis. The research concentrated on studying the artificial intelligence based switching computed torque controller to localization of an endoscopic tool. Results show that the switching artificial nonlinear control algorithm is capable to design a stable controller. For this system, error was used as the performance metric. Positioning of the endoscopic manipulator relative to the world coordinate frame was possible to within 0.05 inch. Error in maintaining a constant point in space is evident during repositioning however this was caused by limitations in the robot arm.

  19. Artificial intelligence. Application of the Statistical Neural Networks computer program in nuclear medicine

    International Nuclear Information System (INIS)

    Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer application of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. In this paper practical aspects of scientific application of ANN in medicine using the Statistical Neural Networks Computer program, were presented. Several steps of data analysis with the above ANN software package were discussed shortly, from material selection and its dividing into groups to the types of obtained results. The typical problems connected with assessing scintigrams by ANN were also described. (author)

  20. Application of artificial intelligence methods for prediction of steel mechanical properties

    Directory of Open Access Journals (Sweden)

    Z. Jančíková

    2008-10-01

    Full Text Available The target of the contribution is to outline possibilities of applying artificial neural networks for the prediction of mechanical steel properties after heat treatment and to judge their perspective use in this field. The achieved models enable the prediction of final mechanical material properties on the basis of decisive parameters influencing these properties. By applying artificial intelligence methods in combination with mathematic-physical analysis methods it will be possible to create facilities for designing a system of the continuous rationalization of existing and also newly developing industrial technologies.

  1. Reducing Energy Waste in Post-secondary Educational Institutions using Artificial Intelligence

    Science.gov (United States)

    Motta Cabrera, David Francisco

    This thesis focuses on computer-related and lighting energy consumption in post-secondary educational institutions. In this respect, artificial intelligence and data association mining are proposed as tools to identify and reduce energy waste. First, an artificial intelligence-based method for forecasting computer usage is proposed. Based on the models' forecast, workstations can be turned on and off, in order to strike a balance between energy savings and user comfort. The models are evaluated on different datasets and their results compared to commercially available alternatives. Second, a data association mining-based approach is proposed to uncover possible relationships between occupancy patterns and lighting-related energy waste in classrooms. A wireless data collection system is used to log data from both lighting consumption and occupancy states during a year. Next, energy savings results of using the proposed approach are compared to those of an occupancy-activated lighting control system for classrooms.

  2. 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.

  3. 13th International Symposium on Distributed Computing and Artificial Intelligence 2016

    CERN Document Server

    Semalat, Ali; Bocewicz, Grzegorz; Sitek, Paweł; Nielsen, Izabela; García, Julián; Bajo, Javier

    2016-01-01

    The 13th International Symposium on Distributed Computing and Artificial Intelligence 2016 (DCAI 2016) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the University of Sevilla (Spain), Osaka Institute of Technology (Japan), and the Universiti Teknologi Malaysia (Malaysia).

  4. Games and machine learning: a powerful combination in an artificial intelligence course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-03-01

    Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

  5. Enhancing nuclear power plant performance through the use of artificial intelligence

    International Nuclear Information System (INIS)

    The objective of this research is to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important, objective is to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants. This means the production of graduates at the B.S., M.S., and Ph.D. levels in Nuclear Engineering and related fields. The research undertaken for this program is particularly appropriate for the M.S. theses and Ph.D. dissertations. A third objective is to transfer the technology developed to the ''nuclear power community,'' as well as the ''scientific and technological community,'' through publications in appropriate journals and proceedings and through presentations at national and international meetings

  6. Artificial Intelligence in Reverse Supply Chain Management: The State of the Art

    CERN Document Server

    Xing, Bo; Battle, Kimberly; Marwala, Tshildzi; Nelwamondo, Fulufhelo V

    2010-01-01

    Product take-back legislation forces manufacturers to bear the costs of collection and disposal of products that have reached the end of their useful lives. In order to reduce these costs, manufacturers can consider reuse, remanufacturing and/or recycling of components as an alternative to disposal. The implementation of such alternatives usually requires an appropriate reverse supply chain management. With the concepts of reverse supply chain are gaining popularity in practice, the use of artificial intelligence approaches in these areas is also becoming popular. As a result, the purpose of this paper is to give an overview of the recent publications concerning the application of artificial intelligence techniques to reverse supply chain with emphasis on certain types of product returns.

  7. Artificial intelligence and tutoring systems computational and cognitive approaches to the communication of knowledge

    CERN Document Server

    Wenger, Etienne

    2014-01-01

    Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge focuses on the cognitive approaches, methodologies, principles, and concepts involved in the communication of knowledge. The publication first elaborates on knowledge communication systems, basic issues, and tutorial dialogues. Concerns cover natural reasoning and tutorial dialogues, shift from local strategies to multiple mental models, domain knowledge, pedagogical knowledge, implicit versus explicit encoding of knowledge, knowledge communication, and practical and theoretic

  8. Applications of artificial intelligence and expert systems in ANGRA-I emergency preparedness - The Brazilian case

    International Nuclear Information System (INIS)

    This study describes a system to follow a nuclear accident and points the areas where the presence of artificial intelligence could be necessary: diagnostics systems, emergency classification, accident management strategies and protective actions. Logical rules could be combined with deterministic equations to provide an expert system prototype to manage a nuclear emergency preparedness for nuclear reactors (fast or thermal) in the Brazilian Nuclear Energy National Commission. (CNEN). (author)

  9. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

    OpenAIRE

    Gonzalez, Luis F.; Montes, Glen A.; Eduard Puig; Sandra Johnson; Kerrie Mengersen; Gaston, Kevin J

    2016-01-01

    Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized therm...

  10. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    Science.gov (United States)

    Krishnan, G. S.

    1997-01-01

    A cost effective model which uses the artificial intelligence techniques in the selection and approval of parts is presented. The knowledge which is acquired from the specialists for different part types are represented in a knowledge base in the form of rules and objects. The parts information is stored separately in a data base and is isolated from the knowledge base. Validation, verification and performance issues are highlighted.

  11. Innovative Applications of Artificial Intelligence 2011: Introduction to the Special Issue

    OpenAIRE

    Shapiro, Daniel G.; Institute for the Study of Learning and Expertise; Fromherz, Markus; Xerox

    2012-01-01

    Every year, AI Magazine devotes one fourth of its annual production to a special issue based on the Innovative Applications of Artificial Intelligence conference. Because IAAI is the premier venue for documenting the transition of AI technology into application, these special issues provide a snapshot of the state of the art in AI with the practical syllogism in mind; they present work that has value because it delivers value in use.

  12. Making smart cities smarter using artificial intelligence techniques for smarter mobility

    OpenAIRE

    Vázquez Salceda, Javier; Álvarez Napagao, Sergio; Tejeda Gómez, José Arturo; Oliva Felipe, Luis Javier; Garcia Gasulla, Dario; Gómez Sebastià, Ignasi; Codina Busquet, Víctor

    2014-01-01

    The term Smart City is tipically applied to urban and metropolitan areas where Information and Communication Technologies provide ways to enable social, cultural and urban development, improving social and political capacities and/or efficiency. In this paper we will show the potential of Artificial Intelligence techniques for augmenting ICT solutions to both increase the cities competiveness but also the active participation of citizens in those processes, making Smart Cities smarter. As exa...

  13. Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

    Science.gov (United States)

    Wroblewski, David; Katrompas, Alexander M.; Parikh, Neel J.

    2009-09-01

    A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

  14. An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

    OpenAIRE

    Hong-Hai Tran; Nhat-Duc Hoang

    2014-01-01

    Permeation grouting is a commonly used approach for soil improvement in construction engineering. Thus, predicting the results of grouting activities is a crucial task that needs to be carried out in the planning phase of any grouting project. In this research, a novel artificial intelligence approach—autotuning support vector machine—is proposed to forecast the result of grouting activities that employ microfine cement grouts. In the new model, the support vector machine (SVM) algorithm is u...

  15. Control Power Optimization using Artificial Intelligence for Hybrid Wing Body Aircraft

    OpenAIRE

    Chhabra, Rupanshi

    2015-01-01

    Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling a large array of control surfaces. This research investigates the potential of employing artificial intelligence methods like neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts for minimizing control power, hinge moments, and actuator forces, while keeping the system weights within acceptable limits. The main obje...

  16. The use of artificial intelligence techniques to improve the multiple payload integration process

    Science.gov (United States)

    Cutts, Dannie E.; Widgren, Brian K.

    1992-01-01

    A maximum return of science and products with a minimum expenditure of time and resources is a major goal of mission payload integration. A critical component then, in successful mission payload integration is the acquisition and analysis of experiment requirements from the principal investigator and payload element developer teams. One effort to use artificial intelligence techniques to improve the acquisition and analysis of experiment requirements within the payload integration process is described.

  17. Pilot Testing an Artificial Intelligence Algorithm That Selects Homeless Youth Peer Leaders Who Promote HIV Testing

    OpenAIRE

    Rice, Eric; Petering, Robin; Craddock, Jaih; Yoshioka-Maxwell, Amanda; Yadav, Amulya; Tambe, Milind

    2016-01-01

    Objective. To pilot test an artificial intelligence (AI) algorithm that selects peer change agents (PCA) to disseminate HIV testing messaging in a population of homeless youth. Methods. We recruited and assessed 62 youth at baseline, 1 month (n = 48), and 3 months (n = 38). A Facebook app collected preliminary social network data. Eleven PCAs selected by AI attended a 1-day training and 7 weekly booster sessions. Mixed-effects models with random effects were used to assess change over time. R...

  18. The Limitations of Standardized Science Tests as Benchmarks for Artificial Intelligence Research: Position Paper

    OpenAIRE

    Davis, Ernest

    2014-01-01

    In this position paper, I argue that standardized tests for elementary science such as SAT or Regents tests are not very good benchmarks for measuring the progress of artificial intelligence systems in understanding basic science. The primary problem is that these tests are designed to test aspects of knowledge and ability that are challenging for people; the aspects that are challenging for AI systems are very different. In particular, standardized tests do not test knowledge that is obvious...

  19. ON GÖDEL'S INCOMPLETENESS THEOREM(S), ARTIFICIAL INTELLIGENCE/LIFE, AND HUMAN MIND

    OpenAIRE

    CHRISTIANTO, V.; FLORENTIN SMARANDACHE

    2015-01-01

    In the present paper we have discussed concerning Gödel’s incompleteness theorem(s) and plausible implications to artificial intelligence/life and human mind. Perhaps we should agree with Sullins III, that the value of this finding is not to discourage certain types of research in AL, but rather to help move us in a direction where we can more clearly define the results of that research.

  20. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955

    OpenAIRE

    McCarthy, John; Minsky, Marvin L.; Rochester, Nathaniel; Shannon, Claude E.

    2006-01-01

    The 1956 Dartmouth summer research project on artificial intelligence was initiated by this August 31, 1955 proposal, authored by John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon. The original typescript consisted of 17 pages plus a title page. Copies of the typescript are housed in the archives at Dartmouth College and Stanford University. The first 5 papers state the proposal, and the remaining pages give qualifications and interests of the four who proposed the study. ...

  1. Utilizing Artificial Intelligence for Achieving a Robust Architecture for Future Robotic Spacecraft

    OpenAIRE

    Jaekel, Steffen; Scholz, Bastian

    2015-01-01

    This paper presents a novel failure-tolerant architecture for future robotic spacecraft. It is based on the Time and Space Partitioning (TSP) principle as well as a combination of Artificial Intelligence (AI) and traditional concepts for system failure detection, isolation and recovery (FDIR). Contrary to classic payload that is separated from the platform, robotic devices attached onto a satellite become an integral part of the spacecraft itself. Hence, the robot needs to be integrated into ...

  2. Introduction to the Special Issue on Innovative Applications of Artificial Intelligence

    OpenAIRE

    Cheetham, William; General Electric Global Research Center; Goker, Mehmet H.; PricewaterhouseCooper

    2008-01-01

    In this editorial we introduce the articles published in this special AI Magazine issue on innovative applications of artificial intelligence. Discussed are a pick-pack-and-ship warehouse-management system, a neural network in the fishing industry, the use of AI to help mobile phone users, building business rules in the mortgage lending business, automating the processing of immigration forms, and the use of the semantic web to provide access to observational datasets.

  3. Artificial General Intelligence: Concept, State of the Art, and Future Prospects

    Science.gov (United States)

    Goertzel, Ben

    2014-12-01

    In recent years broad community of researchers has emerged, focusing on the original ambitious goals of the AI field - the creation and study of software or hardware systems with general intelligence comparable to, and ultimately perhaps greater than, that of human beings. This paper surveys this diverse community and its progress. Approaches to defining the concept of Artificial General Intelligence (AGI) are reviewed including mathematical formalisms, engineering, and biology inspired perspectives. The spectrum of designs for AGI systems includes systems with symbolic, emergentist, hybrid and universalist characteristics. Metrics for general intelligence are evaluated, with a conclusion that, although metrics for assessing the achievement of human-level AGI may be relatively straightforward (e.g. the Turing Test, or a robot that can graduate from elementary school or university), metrics for assessing partial progress remain more controversial and problematic.

  4. Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

    Directory of Open Access Journals (Sweden)

    Hui Chen

    2014-01-01

    Full Text Available Metabolic syndrome is worldwide public health problem and is a serious threat to people's health and lives. Understanding the relationship between metabolic syndrome and the physical symptoms is a difficult and challenging task, and few studies have been performed in this field. It is important to classify adults who are at high risk of metabolic syndrome without having to use a biochemical index and, likewise, it is important to develop technology that has a high economic rate of return to simplify the complexity of this detection. In this paper, an artificial intelligence model was developed to identify adults at risk of metabolic syndrome based on physical signs; this artificial intelligence model achieved more powerful capacity for classification compared to the PCLR (principal component logistic regression model. A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.

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

    Science.gov (United States)

    Moosavi, Vahid; Malekinezhad, Hossein; Shirmohammadi, Bagher

    2014-04-01

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

  6. Neurolinguistically constrained simulation of sentence comprehension: integrating artificial intelligence and brain theory

    Energy Technology Data Exchange (ETDEWEB)

    Gigley, H.M.

    1982-01-01

    An artificial intelligence approach to the simulation of neurolinguistically constrained processes in sentence comprehension is developed using control strategies for simulation of cooperative computation in associative networks. The desirability of this control strategy in contrast to ATN and production system strategies is explained. A first pass implementation of HOPE, an artificial intelligence simulation model of sentence comprehension, constrained by studies of aphasic performance, psycholinguistics, neurolinguistics, and linguistic theory is described. Claims that the model could serve as a basis for sentence production simulation and for a model of language acquisition as associative learning are discussed. HOPE is a model that performs in a normal state and includes a lesion simulation facility. HOPE is also a research tool. Its modifiability and use as a tool to investigate hypothesized causes of degradation in comprehension performance by aphasic patients are described. Issues of using behavioral constraints in modelling and obtaining appropriate data for simulated process modelling are discussed. Finally, problems of validation of the simulation results are raised; and issues of how to interpret clinical results to define the evolution of the model are discussed. Conclusions with respect to the feasibility of artificial intelligence simulation process modelling are discussed based on the current state of research.

  7. Artificial intelligence approach in analysis of DNA sequences.

    Science.gov (United States)

    Brézillon, P J; Zaraté, P; Saci, F

    1993-01-01

    We present an approach for designing a knowledge-based system, called Sequence Acquisition In Context (SAIC), that will be able to cooperate with a biologist in the analysis of DNA sequences. The main task of the system is the acquisition of the expert knowledge that the biologist uses for solving ambiguities from gel autoradiograms, with the aim of re-using it later for solving similar ambiguities. The various types of expert knowledge constitute what we call the contextual knowledge of the sequence analysis. Contextual knowledge deals with the unavoidable problems that are common in the study of the living material (eg noise on data, difficulties of observations). Indeed, the analysis of DNA sequences from autoradiograms belongs to an emerging and promising area of investigation, namely reasoning with images. The SAIC project is developed in a theoretical framework that is shared with other applications. Not all tasks have the same importance in each application. We use this observation for designing an intelligent assistant system with three applications. In the SAIC project, we focus on knowledge acquisition, human-computer interaction and explanation. The project will benefit research in the two other applications. We also discuss our SAIC project in the context of large international projects that aim to re-use and share knowledge in a repository.

  8. Applications of artificial intelligence in safe human-robot interactions.

    Science.gov (United States)

    Najmaei, Nima; Kermani, Mehrdad R

    2011-04-01

    The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of artificial neural networks, namely, self-organizing maps (SOMs), is employed for obtaining a superquadric-based model of the human. The SOM network receives information of the human's footprints from the sensory system and infers necessary data for rendering the human model. The model is then used in order to assess the danger of the robot operations based on the measured as well as predicted human motions. This is followed by the introduction of a new reactive control scheme that results in the least interferences between the human and robot operations. The approach enables the robot to foresee an upcoming danger and take preventive actions before the danger becomes imminent. Simulation and experimental results are presented in order to validate the effectiveness of the proposed method.

  9. Application of Artificial Intelligence Methods of Tool Path Optimization in CNC Machines: A Review

    Directory of Open Access Journals (Sweden)

    Khashayar Danesh Narooei

    2014-08-01

    Full Text Available Today, in most of metal machining process, Computer Numerical Control (CNC machine tools have been very popular due to their efficiencies and repeatability to achieve high accuracy positioning. One of the factors that govern the productivity is the tool path travel during cutting a work piece. It has been proved that determination of optimal cutting parameters can enhance the machining results to reach high efficiency and minimum the machining cost. In various publication and articles, scientist and researchers adapted several Artificial Intelligence (AI methods or hybrid method for tool path optimization such as Genetic Algorithms (GA, Artificial Neural Network (ANN, Artificial Immune Systems (AIS, Ant Colony Optimization (ACO and Particle Swarm Optimization (PSO. This study presents a review of researches in tool path optimization with different types of AI methods that show the capability of using different types of optimization methods in CNC machining process.

  10. Artificial intelligence methods applied for quantitative analysis of natural radioactive sources

    International Nuclear Information System (INIS)

    Highlights: ► Basic description of artificial neural networks. ► Natural gamma ray sources and problem of detections. ► Application of neural network for peak detection and activity determination. - Abstract: Artificial neural network (ANN) represents one of artificial intelligence methods in the field of modeling and uncertainty in different applications. The objective of the proposed work was focused to apply ANN to identify isotopes and to predict uncertainties of their activities of some natural radioactive sources. The method was tested for analyzing gamma-ray spectra emitted from natural radionuclides in soil samples detected by a high-resolution gamma-ray spectrometry based on HPGe (high purity germanium). The principle of the suggested method is described, including, relevant input parameters definition, input data scaling and networks training. It is clear that there is satisfactory agreement between obtained and predicted results using neural network.

  11. Optimization of well placement geothermal reservoirs using artificial intelligence

    Science.gov (United States)

    Akın, Serhat; Kok, Mustafa V.; Uraz, Irtek

    2010-06-01

    This research proposes a framework for determining the optimum location of an injection well using an inference method, artificial neural networks and a search algorithm to create a search space and locate the global maxima. A complex carbonate geothermal reservoir (Kizildere Geothermal field, Turkey) production history is used to evaluate the proposed framework. Neural networks are used as a tool to replicate the behavior of commercial simulators, by capturing the response of the field given a limited number of parameters such as temperature, pressure, injection location, and injection flow rate. A study on different network designs indicates that a combination of neural network and an optimization algorithm (explicit search with variable stepping) to capture local maxima can be used to locate a region or a location for optimum well placement. Results also indicate shortcomings and possible pitfalls associated with the approach. With the provided flexibility of the proposed workflow, it is possible to incorporate various parameters including injection flow rate, temperature, and location. For the field of study, optimum injection well location is found to be in the southeastern part of the field. Specific locations resulting from the workflow indicated a consistent search space, having higher values in that particular region. When studied with fixed flow rates (2500 and 4911 m 3/day), a search run through the whole field located two locations which are in the very same region resulting in consistent predictions. Further study carried out by incorporating effect of different flow rates indicates that the algorithm can be run in a particular region of interest and different flow rates may yield different locations. This analysis resulted with a new location in the same region and an optimum injection rate of 4000 m 3/day). It is observed that use of neural network, as a proxy to numerical simulator is viable for narrowing down or locating the area of interest for

  12. 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

  13. A multi-assets artificial stock market with zero-intelligence traders

    Science.gov (United States)

    Ponta, L.; Raberto, M.; Cincotti, S.

    2011-01-01

    In this paper, a multi-assets artificial financial market populated by zero-intelligence traders with finite financial resources is presented. The market is characterized by different types of stocks representing firms operating in different sectors of the economy. Zero-intelligence traders follow a random allocation strategy which is constrained by finite resources, past market volatility and allocation universe. Within this framework, stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Moreover, the cross-correlations between returns of different stocks are studied using methods of random matrix theory. The probability distribution of eigenvalues of the cross-correlation matrix shows the presence of outliers, similar to those recently observed on real data for business sectors. It is worth noting that business sectors have been recovered in our framework without dividends as only consequence of random restrictions on the allocation universe of zero-intelligence traders. Furthermore, in the presence of dividend-paying stocks and in the case of cash inflow added to the market, the artificial stock market points out the same structural results obtained in the simulation without dividends. These results suggest a significative structural influence on statistical properties of multi-assets stock market.

  14. River Trip Optimization Scheduling Based on Artificial Intelligence Simulation and the Bee-Swarm Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Zhan Wenting

    2012-09-01

    Full Text Available The study on the impacts of human activities on natural resources is of critical importance in constructing effective management strategies in rafting trips. The Camping Schedule Intelligent Generator (CSIG, the computer program developed in the study, which successfully models the complex, dynamic human-environment interactions in the rafting river. This generator includes two parts: artificial intelligence simulation and BSGA-based Optimization. It employs artificial intelligence in creating an individual-based modeling system. With the help of BSGA, this simulation system successfully models the recreatinal rafting behavior and captures the decision making of rafting trips as they responsively seek to optimize their functions. After modeling, the paper applys CSIG to the Colorado River, which is a famous rafting river and find that: the numbers of short motor-trips (6-8 day and long-oar trips (15-18 day are obviously larger than the other two. Finally, the study analyzes the sensitivity of the model and finds that when the water velocity varies in the actual range.

  15. Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2016-08-01

    In the present research, three artificial intelligence methods including Gene Expression Programming (GEP), Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as, 48 empirical equations (10, 12 and 26 equations were temperature-based, sunshine-based and meteorological parameters-based, respectively) were used to estimate daily solar radiation in Kerman, Iran in the period of 1992-2009. To develop the GEP, ANN and ANFIS models, depending on the used empirical equations, various combinations of minimum air temperature, maximum air temperature, mean air temperature, extraterrestrial radiation, actual sunshine duration, maximum possible sunshine duration, sunshine duration ratio, relative humidity and precipitation were considered as inputs in the mentioned intelligent methods. To compare the accuracy of empirical equations and intelligent models, root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE) and determination coefficient (R2) indices were used. The results showed that in general, sunshine-based and meteorological parameters-based scenarios in ANN and ANFIS models presented high accuracy than mentioned empirical equations. Moreover, the most accurate method in the studied region was ANN11 scenario with five inputs. The values of RMSE, MAE, MARE and R2 indices for the mentioned model were 1.850 MJ m-2 day-1, 1.184 MJ m-2 day-1, 9.58% and 0.935, respectively.

  16. Inteligência artificial aplicada à Zootecnia Artificial intelligence in Animal Science

    OpenAIRE

    Ernane José Xavier Costa

    2009-01-01

    Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja conc...

  17. Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

    CERN Document Server

    Khan, Samee; Burczy´nski, Tadeusz

    2012-01-01

    One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

  18. Demonstrating artificial intelligence for space systems - Integration and project management issues

    Science.gov (United States)

    Hack, Edmund C.; Difilippo, Denise M.

    1990-01-01

    As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

  19. An intelligent power factor corrector for power system using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Bayindir, R.; Colak, I. [Department of Electrical Education, Faculty of Technical Education, Gazi University, Besevler, 06500 Ankara (Turkey); Sagiroglu, S. [Department of Computer Engineering, Faculty of Engineering and Architecture, Celal Bayar Bulvari, Gazi University, Maltepe, 06570 Ankara (Turkey)

    2009-01-15

    An intelligent power factor correction approach based on artificial neural networks (ANN) is introduced. Four learning algorithms, backpropagation (BP), delta-bar-delta (DBD), extended delta-bar-delta (EDBD) and directed random search (DRS), were used to train the ANNs. The best test results obtained from the ANN compensators trained with the four learning algorithms were first achieved. The parameters belonging to each neural compensator obtained from an off-line training were then inserted into a microcontroller for on-line usage. The results have shown that the selected intelligent compensators developed in this work might overcome the problems occurred in the literature providing accurate, simple and low-cost solution for compensation. (author)

  20. APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO COMBATING CYBER CRIMES: A REVIEW

    Directory of Open Access Journals (Sweden)

    Selma Dilek

    2015-01-01

    Full Text Available With the advances in information technology (IT criminals are using cyberspace to commit numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other threats. Physical devices and human intervention are not sufficient for monitoring and protection of these infrastructures; hence, there is a need for more sophisticated cyber defense systems that need to be flexible, adaptable and robust, and able to detect a wide variety of threats and make intelligent real-time decisions. Numerous bio-inspired computing methods of Artificial Intelligence have been increasingly playing an important role in cyber crime detection and prevention. The purpose of this study is to present advances made so far in the field of applying AI techniques for combating cyber crimes, to demonstrate how these techniques can be a

  1. A modern artificial intelligence Playware art tool for psychological testing of group dynamics

    DEFF Research Database (Denmark)

    Pagliarini, Luigi; Lund, Henrik Hautop

    2015-01-01

    We describe an artistic method used for the psychological analysis of group dynamics. The design of the artistic system, which mediates group dynamics, emerges from our studies of modular Playware and remixing Playware. Inspired from remixing modular Playware, where users remix samples in the form...... and the psychological findings. We describe the modern artificial intelligence implementation of this instrument. Between an art piece and a psychological test, at a first cognitive analysis, it seems to be a promising research tool. In the discussion we speculate about potential industrial applications, as well....

  2. Myocardial ischemia detection by artificial intelligence interpretation of Tl-201 tomograms

    International Nuclear Information System (INIS)

    This paper reports on an expert system environment which automatically assigned certainty factors to abnormal regions in stress and delayed myocardial thallium-201 polar bulls-eye plots. MYCIN-type algorithms propagated certainty factors for the presence, location, and character of each coronary lesion. Ninety-four previously validated rules that considered only stress perfusion defects spawned 91 new rules considering tracer redistribution. Fifteen new rules assessed vascular territories for the presence and location of fixed or reversible defects. This artificial intelligence tool can provide novice readers of cardiac T1-201 studies automatic, consistent, objective, and justified interpretations that consider artifacts, coronary territory overlap, and multiple defects

  3. Artificial Intelligence Techniques in Real-Time Strategy Games - Architecture and Combat Behavior

    OpenAIRE

    Stene, Sindre Berg

    2006-01-01

    The general purpose of this research is to investigate the possibilities offered for the use of Artificial Intelligence theory and methods in advanced game environments. The real-time strategy (RTS) game genre is investigated in detail, and an architecture and solutions to some common issues are presented. An RTS AI controlled opponent named KAI is implemented for the TA Spring game engine in order to advance the state of the art in usin AI techniques in games and to gain some insight int...

  4. Enhancement of verification and validation for nuclear reactors through artificial intelligence

    International Nuclear Information System (INIS)

    In parallel with the rapid advancements in computer technology, there is growing concern in application of computer-enhanced methodologies in human-machine integrated complex systems virtually for the same essential goals, namely: safe, reliable and cost effective operation. In this context, the relevant studies may have various focal points such as plant wide monitoring, verification and validation, fault diagnosis and so on. This work highlights the eminent role which artificial intelligence (Al) and Al-based methodologies can play in designing operational enhancement of nuclear power reactors with particular reference to verification and validation. (author). 11 refs, 3 figs

  5. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, F.J.O. [Instituto de Engenharia Nuclear, Cidade Universitaria, Rio de Janeiro, CEP 21945-970, Caixa Postal 68550 (Brazil)], E-mail: fferreira@ien.gov.br; Crispim, V.R.; Silva, A.X. [DNC/Poli, PEN COPPE CT, UFRJ Universidade Federal do Rio de Janeiro, CEP 21941-972, Caixa Postal 68509, Rio de Janeiro (Brazil)

    2010-06-15

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  6. Approximate Matching as a Key Technique in Organization of Natural and Artificial Intelligence

    Science.gov (United States)

    Mack, Marilyn; Lapir, Gennadi M.; Berkovich, Simon

    2000-01-01

    The basic property of an intelligent system, natural or artificial, is "understanding". We consider the following formalization of the idea of "understanding" among information systems. When system I issues a request to system 2, it expects a certain kind of desirable reaction. If such a reaction occurs, system I assumes that its request was "understood". In application to simple, "push-button" systems the situation is trivial because in a small system the required relationship between input requests and desired outputs could be specified exactly. As systems grow, the situation becomes more complex and matching between requests and actions becomes approximate.

  7. Application of Artificial Intelligence technology to the analysis and synthesis of reliable software systems

    Science.gov (United States)

    Wild, Christian; Eckhardt, Dave

    1987-01-01

    The development of a methodology for the production of highly reliable software is one of the greatest challenges facing the computer industry. Meeting this challenge will undoubtably involve the integration of many technologies. This paper describes the use of Artificial Intelligence technologies in the automated analysis of the formal algebraic specifications of abstract data types. These technologies include symbolic execution of specifications using techniques of automated deduction and machine learning through the use of examples. On-going research into the role of knowledge representation and problem solving in the process of developing software is also discussed.

  8. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    International Nuclear Information System (INIS)

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  9. Statistic Approach versus Artificial Intelligence for Rainfall Prediction Based on Data Series

    Directory of Open Access Journals (Sweden)

    Indrabayu

    2013-04-01

    Full Text Available This paper proposed a new idea in comparing two common predictors i.e. the statistic method and artificial intelligence (AI for rainfall prediction using empirical data series. The statistic method uses Auto- Regressive Integrated Moving (ARIMA and Adaptive Splines Threshold Autoregressive (ASTAR, most favorable statistic tools, while in the AI, combination of Genetic Algorithm-Neural Network (GA-NN is chosen. The results show that ASTAR gives best prediction compare to others, in term of root mean square (RMSE and following trend between prediction and actual.

  10. Validating a UAV artificial intelligence control system using an autonomous test case generator

    Science.gov (United States)

    Straub, Jeremy; Huber, Justin

    2013-05-01

    The validation of safety-critical applications, such as autonomous UAV operations in an environment which may include human actors, is an ill posed problem. To confidence in the autonomous control technology, numerous scenarios must be considered. This paper expands upon previous work, related to autonomous testing of robotic control algorithms in a two dimensional plane, to evaluate the suitability of similar techniques for validating artificial intelligence control in three dimensions, where a minimum level of airspeed must be maintained. The results of human-conducted testing are compared to this automated testing, in terms of error detection, speed and testing cost.

  11. Validating an artificial intelligence human proximity operations system with test cases

    Science.gov (United States)

    Huber, Justin; Straub, Jeremy

    2013-05-01

    An artificial intelligence-controlled robot (AICR) operating in close proximity to humans poses risk to these humans. Validating the performance of an AICR is an ill posed problem, due to the complexity introduced by the erratic (noncomputer) actors. In order to prove the AICR's usefulness, test cases must be generated to simulate the actions of these actors. This paper discusses AICR's performance validation in the context of a common human activity, moving through a crowded corridor, using test cases created by an AI use case producer. This test is a two-dimensional simplification relevant to autonomous UAV navigation in the national airspace.

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

    CERN Document Server

    Quiza, Ramón; Davim, J Paulo

    2012-01-01

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

  13. International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems

    CERN Document Server

    Bhaskar, M; Panigrahi, Bijaya; Das, Swagatam

    2016-01-01

    The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES -2015) held at Velammal Engineering College (VEC), Chennai, India during 22 – 23 April 2015. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of Communication, Computing and Power Technologies.

  14. AN ARTIFICIAL INTELLIGENCE APPROACH FOR THE PREDICTION OF SURFACE ROUGHNESS IN CO2 LASER CUTTING

    Directory of Open Access Journals (Sweden)

    MILOŠ MADIĆ

    2012-12-01

    Full Text Available In laser cutting, the cut quality is of great importance. Multiple non-linear effects of process parameters and their interactions make very difficult to predict cut quality. In this paper, artificial intelligence (AI approach was applied to predict the surface roughness in CO2 laser cutting. To this aim, artificial neural network (ANN model of surface roughness was developed in terms of cutting speed, laser power and assist gas pressure. The experimental results obtained from Taguchi’s L25 orthogonal array were used to develop ANN model. The ANN mathematical model of surface roughness was expressed as explicit nonlinear function of the selected input parameters. Statistical results indicate that the ANN model can predict the surface roughness with good accuracy. It was showed that ANNs may be used as a good alternative in analyzing the effects of cutting parameters on the surface roughness.

  15. High voltage transmission lines studies with the use of artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Ekonomou, L. [A.S.PE.T.E. - School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece)

    2009-12-15

    The paper presents an alternative approach for the studies of high voltage transmission lines based on artificial intelligence and more specifically artificial neural networks (ANNs). In contrast to the existing conventional-analytical techniques and simulations which are using in the calculations empirical and/or approximating equations, this approach is based only on actual field data and actual measurements. The proposed approach is applied on high voltage transmission lines in order to calculate the lightning outages, on grounding systems in order to assess the grounding resistance and on high voltage transmission lines' polluted insulators in order to estimate the critical flashover voltage. The obtained results are very close to the actual ones for all three case studies, something which clearly implies that the ANN approach is well working and has an acceptable accuracy, constituting an additional tool of electric engineers. (author)

  16. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NNds) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

  17. Predicting Learners Performance Using Artificial Neural Networks in Linear Programming Intelligent Tutoring System

    Directory of Open Access Journals (Sweden)

    Samy S. Abu Naser

    2012-04-01

    Full Text Available In this paper we present a technique that employ Artificial Neural Networks and expert systems to obtain knowledge for the learner model in the Linear Programming Intelligent Tutoring System(LP-ITS to be able to determine the academic performance level of the learners in order to offer him/her the properdifficulty level of linear programming problems to solve. LP-ITS uses Feed forward Back-propagation algorithm to be trained with a group of learners data to predict their academic performance. Furthermore, LP-ITS uses an Expert System to decide the proper difficulty level that is suitable with the predicted academic performance of the learner. Several tests have been carried out to examine adherence to real time data. The accuracy of predicting the performance of the learners is very high and thus states that the Artificial Neural Network is skilled enough to make suitable predictions.

  18. Predicting Learners Performance Using Artificial Neural Networks in Linear Programming Intelligent Tutoring System

    Directory of Open Access Journals (Sweden)

    Samy S. Abu Naser

    2012-03-01

    Full Text Available In this paper we present a technique that employ Artificial Neural Networks and expert systems to obtain knowledge for the learner model in the Linear Programming Intelligent Tutoring System(LP-ITS to be able to determine the academic performance level of the learners in order to offer him/her the proper difficulty level of linear programming problems to solve. LP-ITS uses Feed forward Back-propagation algorithm to be trained with a group of learners data to predict their academic performance. Furthermore, LP-ITS uses an Expert System to decide the proper difficulty level that is suitable with the predicted academic performance of the learner. Several tests have been carried out to examine adherence to real time data. The accuracy of predicting the performance of the learners is very high and thus states that the Artificial Neural Network is skilled enough to make suitable predictions.

  19. Prediction of Metabolism of Drugs using Artificial Intelligence: How far have we reached?

    Science.gov (United States)

    Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

    2016-01-01

    Information about drug metabolism is an essential component of drug development. Modeling the drug metabolism requires identification of the involved enzymes, rate and extent of metabolism, the sites of metabolism etc. There has been continuous attempts in the prediction of metabolism of drugs using artificial intelligence in effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are number of predictive models available for metabolism using Support vector machines, Artificial neural networks, Bayesian classifiers etc. There is an urgent need to review their progress so far and address the existing challenges in prediction of metabolism. In this attempt, we are presenting the currently available literature models and some of the critical issues regarding prediction of drug metabolism.

  20. Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil.

    Science.gov (United States)

    Nunes, Matheus Henrique; Görgens, Eric Bastos

    2016-01-01

    Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approaches can be useful techniques in minimizing estimation errors within complex variations of vegetation. We evaluated the performance of Random Forest® regression tree and Artificial Neural Network procedures in modelling stem taper. Diameters and volume outside bark were compared to a traditional taper-based equation across a tropical Brazilian savanna, a seasonal semi-deciduous forest and a rainforest. Neural network models were found to be more accurate than the traditional taper equation. Random forest showed trends in the residuals from the diameter prediction and provided the least precise and accurate estimations for all forest types. This study provides insights into the superiority of a neural network, which provided advantages regarding the handling of local effects.

  1. Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil.

    Directory of Open Access Journals (Sweden)

    Matheus Henrique Nunes

    Full Text Available Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approaches can be useful techniques in minimizing estimation errors within complex variations of vegetation. We evaluated the performance of Random Forest® regression tree and Artificial Neural Network procedures in modelling stem taper. Diameters and volume outside bark were compared to a traditional taper-based equation across a tropical Brazilian savanna, a seasonal semi-deciduous forest and a rainforest. Neural network models were found to be more accurate than the traditional taper equation. Random forest showed trends in the residuals from the diameter prediction and provided the least precise and accurate estimations for all forest types. This study provides insights into the superiority of a neural network, which provided advantages regarding the handling of local effects.

  2. OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

    Science.gov (United States)

    Pedrazzoli, Attilio

    2010-06-01

    AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

  3. Identification of Age, Temperature and Radiation Effect on Ferritic Steel Microstructure Based on Artificial Intelligence

    International Nuclear Information System (INIS)

    In the construction of nuclear installation, it is important to know the material condition used on it. Considering mechanical properties of these materials, there are some material change affected by ageing, temperature and radiation. For some years, austenitic stainless steel are used as a fuel cladding in fast breeder reactor. However this material will not sufficiently competitive from economic point of view for the next year. Experiment result on ferritic steel gave information of stronger structural properties compared to austenitic stainless steel. Modeling and simulation will support further identification of this material changing caused by such effects. Pattern recognition of these changes base on artificial intelligence is expected to support the research and development activities on nuclear structure materials. Material structure pattern of these materials, observed by SEM, are converted using image processing system. Its characteristic is then analyzed with principal component using perception method, which usually used on identifying and learning neural network system based on artificial intelligence. Specific design and input are needed to identify the change of material structure pattern before and after any applied effect. In this paper, simulation of changing identification on three types ferritic steel F17(17 Cr), EM 12 (9 CR-2 MoNbV), and EMI 0 (9 Cr-I Mo) were done. The microstructure data before and after effect are taken from some references. The whole pattern recognition process are done using MATLAB software package. (author)

  4. Detection of Heart Diseases by Mathematical Artificial Intelligence Algorithm Using Phonocardiogram Signals

    Directory of Open Access Journals (Sweden)

    D. Prakash

    2013-05-01

    Full Text Available An artificial intelligence (AI algorithm has been developed using Mathematical formula to diagnose heart disease from Phonocardiogram (PCG signals. Auscultation, the technique of listening to heart sounds with a stethoscope can be used as a primary detection technique for detecting heart disorders for the past years. But now the Phonocardiogram, the digital recording of heart sounds is becoming very popular technique as it is relatively inexpensive. Four amplitude parameters of the PCG signal are extracted by using filter technique and are used as input. PCG signals for three types of heart diseases such as Tachycardia, Bradycardia and Atrial fibrillation were used in this paper to test the accuracy. These disease types that affect the electrical system of heart are known as arrhythmias, cause the heart to beat very fast (Tachycardia or very slow (Bradycardia, or unexpectedly (Atrial fibrillation. After the signals are filtered and the parameters are extracted, the parameters are fed to the AI algorithm. Classifications of heart diseases are carried using the AI algorithm by comparing the extracted parameters. Here comparison is done using Min Max method. The developed mathematical artificial intelligence algorithm is implemented in MATLab using Simulink and the simulation results proved that the developed algorithm has been shown to be a powerful technique in detection of heart diseases using PCG signals.

  5. The DelFly design, aerodynamics, and artificial intelligence of a flapping wing robot

    CERN Document Server

    de Croon, G C H E; Remes, B D W; Ruijsink, R; De Wagter, C

    2016-01-01

    This book introduces the topics most relevant to autonomously flying flapping wing robots: flapping-wing design, aerodynamics, and artificial intelligence. Readers can explore these topics in the context of the "Delfly", a flapping wing robot designed at Delft University in The Netherlands. How are tiny fruit flies able to lift their weight, avoid obstacles and predators, and find food or shelter? The first step in emulating this is the creation of a micro flapping wing robot that flies by itself. The challenges are considerable: the design and aerodynamics of flapping wings are still active areas of scientific research, whilst artificial intelligence is subject to extreme limitations deriving from the few sensors and minimal processing onboard. This book conveys the essential insights that lie behind success such as the DelFly Micro and the DelFly Explorer. The DelFly Micro, with its 3.07 grams and 10 cm wing span, is still the smallest flapping wing MAV in the world carrying a camera, whilst the DelFly Expl...

  6. Analysis of Boiler Operational Variables Prior to Tube Leakage Fault by Artificial Intelligent System

    Directory of Open Access Journals (Sweden)

    Al-Kayiem Hussain H.

    2014-07-01

    Full Text Available Steam boilers are considered as a core of any steam power plant. Boilers are subjected to various types of trips leading to shut down of the entire plant. The tube leakage is the worse among the common boiler faults, where the shutdown period lasts for around four to five days. This paper describes the rules of the Artificial Intelligent Systems to diagnosis the boiler variables prior to tube leakage occurrence. An Intelligent system based on Artificial Neural Network was designed and coded in MATLAB environment. The ANN was trained and validated using real site data acquired from coal fired power plant in Malaysia. Ninety three boiler operational variables were identified for the present investigation based on the plant operator experience. Various neural networks topology combinations were investigated. The results showed that the NN with two hidden layers performed better than one hidden layer using Levenberg-Maquardt training algorithm. Moreover, it was noticed that hyperbolic tangent function for input and output nodes performed better than other activation function types.

  7. Artificial intelligence-based control system for the analysis of metal casting properties

    Directory of Open Access Journals (Sweden)

    E. Mares

    2010-06-01

    Full Text Available Purpose: The metal casting process requires testing equipment that along with customized computer software properly supports the analysis of casting component characteristic properties. Due to the fact that this evaluation process involves the control of complex and multi-variable melting, casting and solidification factors, it is necessary to develop dedicated software.Design/methodology/approach: The integration of Statistical Process Control methods and Artificial Intelligence techniques (Case-Based Reasoning into Thermal Analysis Data Acquisition Software (NI LabView was developed to analyze casting component properties. The thermal data was tested in terms of accuracy, reliability and timeliness in order to secure metal casting process effectiveness.Findings: Quantitative values were defined as “Low”, “Medium” and “High” to assess the level of improvement in the metal casting analysis by means of the Artificial Intelligence-Based Control System (AIBCS. The traditional process was used as a reference to measure such improvement. As a result, the accuracy, reliability and timeliness were significantly increased to the “High” level.Research limitations/implications: Presently, the AIBCS predicts a limited number of casting properties. Due to its flexible design more properties could be added.Practical implications: The AIBCS has been successfully used at the Ford/Nemak Windsor Aluminum Plant (WAP to analyze Al casting properties of the engine blocks.Originality/value: The metal casting research community has immensely benefited from these developed information technologies that support the metal casting process.

  8. GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2012-10-01

    Full Text Available Congetive method is used in this research to create portfilo of movement robot manipulator. Gradient descent (GD artificial intelligence based switching feedback linearization controller was used and robot’s postures and trajectory were expected in MATLAB/SIMULINK environment. Feedback linearization controller (CTC is an influential nonlinear controller to certain systems which it is based on feedback linearization and computes the required torques using the nonlinear feedback control law in certain systems. Practically a large amount of systems have uncertainties accordingly this method has a challenge. Switching feedback linearization controller is a significant combination nonlinear stable-robust controller under condition of partly uncertain dynamic parameters of system. This technique is used to control of highly nonlinear systems especially in nonlinear time varient nonlinear dynamic system. To increase the stability and robustness with regards to improve the robustness switching methodology is applied to feedback linearization controller. Lyapunov stability is proved in proposed controller based on switching function. To compensate for the dependence on switching parameters baseline methodology is used.The nonlinear model dynamic formulation problem in uncertain system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to estimate the system dynamic. Forward kinematics implemented the manipulator's movements. Results validated the robot's range of possible postures and trajectories.

  9. Application of an Artificial Intelligence Method for Velocity Calibration and Events Location in Microseismic Monitoring

    Science.gov (United States)

    Yang, Y.; Chen, X.

    2013-12-01

    Good quality hydraulic fracture maps are heavily dependent upon the best possible velocity structure. Particle Swarm Optimization inversion scheme, an artificial intelligence technique for velocity calibration and events location could serve as a viable option, able to produce high quality data. Using perforation data to recalibrate the 1D isotropic velocity model derived from dipole sonic logs (or even without them), we are able to get the initial velocity model used for consequential events location. Velocity parameters can be inverted, as well as the thickness of the layer, through an iterative procedure. Performing inversion without integrating available data is unlikely to produce reliable results; especially if there are only one perforation shot and a single poor-layer-covered array along with low signal/noise ratio signal. The inversion method was validated via simulations and compared to the Fast Simulated Annealing approach and the Conjugate Gradient method. Further velocity model refinement can be accomplished while calculating events location during the iterative procedure minimizing the residuals from both sides. This artificial intelligence technique also displays promising application to the joint inversion of large-scale seismic activities data.

  10. Prediction of shear wave velocity using empirical correlations and artificial intelligence methods

    Science.gov (United States)

    Maleki, Shahoo; Moradzadeh, Ali; Riabi, Reza Ghavami; Gholami, Raoof; Sadeghzadeh, Farhad

    2014-06-01

    Good understanding of mechanical properties of rock formations is essential during the development and production phases of a hydrocarbon reservoir. Conventionally, these properties are estimated from the petrophysical logs with compression and shear sonic data being the main input to the correlations. This is while in many cases the shear sonic data are not acquired during well logging, which may be for cost saving purposes. In this case, shear wave velocity is estimated using available empirical correlations or artificial intelligent methods proposed during the last few decades. In this paper, petrophysical logs corresponding to a well drilled in southern part of Iran were used to estimate the shear wave velocity using empirical correlations as well as two robust artificial intelligence methods knows as Support Vector Regression (SVR) and Back-Propagation Neural Network (BPNN). Although the results obtained by SVR seem to be reliable, the estimated values are not very precise and considering the importance of shear sonic data as the input into different models, this study suggests acquiring shear sonic data during well logging. It is important to note that the benefits of having reliable shear sonic data for estimation of rock formation mechanical properties will compensate the possible additional costs for acquiring a shear log.

  11. Artificial intelligence and Internet of Things in a “smart home” context:A Distributed System Architecture

    OpenAIRE

    Lynggaard, Per

    2014-01-01

    We are currently witnessing an evolution from building and home automation to smart homes, driven by progressing maturity of the Internet of Things and the use of artificial intelligence. However, significant technological challenges such as immature home intelligence, huge network and central server processing load; and embedded resource usage, still need to be addressed. Until now, most of the research in this area has focused on centralized architectures for smart homes. This work contribu...

  12. The role of the artificial intelligence within the context of the human factors in the nuclear safety

    International Nuclear Information System (INIS)

    The effective evaluation of a human-machine system depends heavily on a cognitive model of the human behaviour. The basic question is: How can we model the human cognition? The response should be found in the five disciplines that form the Cognitive Sciences: Artificial Intelligence, Cognitive Psychology, Neurophysiology, Linguistic, and Philosophy. Among them, the Artificial Intelligence appears as the catalyzer of the contributions and discoveries in the other four, trying to realize that cognitive model with the tools of the Computer Science. Sometimes, it seems as if these disciplines spoke different languages to describe the same ideas. It is necessary a holistic treatment of such questions that include the human cognition and its modelling. This becomes more clear when we observe that there are nowadays different methodologies that must be integrated in some way. This is the case of the symbolic approach (artificial intelligence), connectionist approach (neural networks) and the fuzzy logic. This paper makes a review of the available methodologies, showing the problems and the current solutions to answer the following question. How is possible to develop a human-machine system and an intelligent interface based on the Artificial Intelligence that fulfills the following characteristics: human-centered design, cognitive simulation of the human behaviour, and dynamic function allocation. This paper concludes with proposals of national projects to be applied to the Brazilian situation. (author). 28 refs

  13. PID Based on a Single Artificial Neural Network Algorithm for Intelligent Sensors

    Directory of Open Access Journals (Sweden)

    J. Rivera-Mejía

    2012-04-01

    Full Text Available Today control is required in any field or application. Nowadays, classic control is the most used, but it is well-known that users need to know the system’s characteristics to reach optimal control. This paper is focused on designing a proportional integral derivative control, based on a single artificial neural network with the aim to improve its performance and its use with minimal control knowledge from the end user. The proposed control was assessed with simulated and practical physical systems of first and second order. In order to increase the confidence of the intelligent sensor control, the evaluation was made using the classical test of control response of a step as input. The proposed control was implemented on an intelligent sensor with a small microcontroller. Also, the performance was compared between the proposed control and a commercial control. Here, an intelligent sensor is presented with control capability for a wide variety of physical systems. The experiments performed demonstrated the capability of the proposed control, which can be easily used and save time at the initial control set up.

  14. Self-Calibration and Optimal Response in Intelligent Sensors Design Based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Gilberto Bojorquez

    2007-08-01

    Full Text Available The development of smart sensors involves the design of reconfigurable systemscapable of working with different input sensors. Reconfigurable systems ideally shouldspend the least possible amount of time in their calibration. An autocalibration algorithmfor intelligent sensors should be able to fix major problems such as offset, variation of gainand lack of linearity, as accurately as possible. This paper describes a new autocalibrationmethodology for nonlinear intelligent sensors based on artificial neural networks, ANN.The methodology involves analysis of several network topologies and training algorithms.The proposed method was compared against the piecewise and polynomial linearizationmethods. Method comparison was achieved using different number of calibration points,and several nonlinear levels of the input signal. This paper also shows that the proposedmethod turned out to have a better overall accuracy than the other two methods. Besides,experimentation results and analysis of the complete study, the paper describes theimplementation of the ANN in a microcontroller unit, MCU. In order to illustrate themethod capability to build autocalibration and reconfigurable systems, a temperaturemeasurement system was designed and tested. The proposed method is an improvement over the classic autocalibration methodologies, because it impacts on the design process of intelligent sensors, autocalibration methodologies and their associated factors, like time and cost.

  15. Development of an Artificial Intelligence Programming Course and Unity3d Based Framework to Motivate Learning in Artistic Minded Students

    DEFF Research Database (Denmark)

    Reng, Lars

    2012-01-01

    between technical and artistic minded students is, however, increased once the students reach the sixth semester. The complex algorithms of the artificial intelligence course seemed to demotivate the artistic minded students even before the course began. This paper will present the extensive changes made...... to the sixth semester artificial intelligence programming course, in order to provide a highly motivating direct visual feedback, and thereby remove the steep initial learning curve for artistic minded students. The framework was developed with close dialog to both the game industry and experienced master...

  16. Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Santos de Oliveira, Iona Maghali, E-mail: ioliveira@con.ufrj.br [Nuclear Engineering Program, Federal University of Rio de Janeiro, P.O. Box 68509, Zip Code 21945-970, Rio de Janeiro, RJ (Brazil); Schirru, Roberto, E-mail: schirru@lmp.ufrj.br [Nuclear Engineering Program, Federal University of Rio de Janeiro, P.O. Box 68509, Zip Code 21945-970, Rio de Janeiro, RJ (Brazil)

    2011-05-15

    Research highlights: > We present Artificial Bee Colony with Random Keys (ABCRK) for In-Core Fuel Management Optimization. > Its performance is examined through the optimization of a Brazilian '2-loop' PWR. > Feasibility of using ABCRK is shown against some well known population-based algorithms. > Additional advantage includes the utilization of fewer control parameters. - Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian '2-loop' Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.

  17. Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

    Science.gov (United States)

    Pathak, Lakshmi; Singh, Vineeta; Niwas, Ram; Osama, Khwaja; Khan, Saif; Haque, Shafiul; Tripathi, C K M; Mishra, B N

    2015-01-01

    Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500.

  18. Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

    International Nuclear Information System (INIS)

    Research highlights: → We present Artificial Bee Colony with Random Keys (ABCRK) for In-Core Fuel Management Optimization. → Its performance is examined through the optimization of a Brazilian '2-loop' PWR. → Feasibility of using ABCRK is shown against some well known population-based algorithms. → Additional advantage includes the utilization of fewer control parameters. - Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian '2-loop' Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.

  19. Bayesian Model Averaging of Artificial Intelligence Models for Hydraulic Conductivity Estimation

    Science.gov (United States)

    Nadiri, A.; Chitsazan, N.; Tsai, F. T.; Asghari Moghaddam, A.

    2012-12-01

    This research presents a Bayesian artificial intelligence model averaging (BAIMA) method that incorporates multiple artificial intelligence (AI) models to estimate hydraulic conductivity and evaluate estimation uncertainties. Uncertainty in the AI model outputs stems from error in model input as well as non-uniqueness in selecting different AI methods. Using one single AI model tends to bias the estimation and underestimate uncertainty. BAIMA employs Bayesian model averaging (BMA) technique to address the issue of using one single AI model for estimation. BAIMA estimates hydraulic conductivity by averaging the outputs of AI models according to their model weights. In this study, the model weights were determined using the Bayesian information criterion (BIC) that follows the parsimony principle. BAIMA calculates the within-model variances to account for uncertainty propagation from input data to AI model output. Between-model variances are evaluated to account for uncertainty due to model non-uniqueness. We employed Takagi-Sugeno fuzzy logic (TS-FL), artificial neural network (ANN) and neurofuzzy (NF) to estimate hydraulic conductivity for the Tasuj plain aquifer, Iran. BAIMA combined three AI models and produced better fitting than individual models. While NF was expected to be the best AI model owing to its utilization of both TS-FL and ANN models, the NF model is nearly discarded by the parsimony principle. The TS-FL model and the ANN model showed equal importance although their hydraulic conductivity estimates were quite different. This resulted in significant between-model variances that are normally ignored by using one AI model.

  20. Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

    Science.gov (United States)

    Niwas, Ram; Osama, Khwaja; Khan, Saif; Haque, Shafiul; Tripathi, C. K. M.; Mishra, B. N.

    2015-01-01

    Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500. PMID:26368924

  1. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

    OpenAIRE

    Min-Chao He; Yun-Yun Liu,; Wei Qi; Zhen-Hong Yuan; Jing-Liang Xu,; Yu Zhang

    2012-01-01

    Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the centr...

  2. Structural investigation and simulation of acoustic properties of some tellurite glasses using artificial intelligence technique

    International Nuclear Information System (INIS)

    Research highlights: → Simulation the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). → The glass network is strengthened by enhancing the linkage of Te-O chains. The tellurite network will also come to homogenization, because of uniform distribution of Nb5+ ions among the Te-O chains, though some of the tellurium-oxide polyhedra still link each other in edge sharing. → Excellent agreements between the measured values and the predicted values were obtained for over 50 different tellurite glass compositions. → The model we designed gives a better agreement as compared with Makishima and Machenzie model. - Abstract: The developments in the field of industry raise the need for simulating the acoustic properties of glass materials before melting raw material oxides. In this paper, we are trying to simulate the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). The artificial neural network (ANN) technique is introduced in the current study to simulate and predict important parameters such as density, longitudinal and shear ultrasonic velocities and elastic moduli (longitudinal and shear moduli). The ANN results were found to be in successful good agreement with those experimentally measured parameters. Then the presented ANN model is used to predict the acoustic properties of some new tellurite glasses. For this purpose, four glass systems xNb2O5-(1 - x)TeO2, 0.1PbO-xNb2O5-(0.9 - x)TeO2, 0.2PbO-xNb2O5-(0.8 - x)TeO2 and 0.05Bi2O3-xNb2O5-(0.95 - x)TeO2 were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb2O5 as a network modifier provides oxygen ions to change [TeO4] tbps into [TeO3] tps.

  3. Combining Artificial Intelligence and Advanced Techniques in Fault-Tolerant Control

    Directory of Open Access Journals (Sweden)

    A. Vargas-Martínez

    2011-08-01

    Full Text Available We present the integration of artificial intelligence, robust, nonlinear and model reference adaptive control (MRACmethods for fault-tolerant control (FTC. We combine MRAC schemes with classical PID controllers, artificial neuralnetworks (ANNs, genetic algorithms (GAs, H∞ controls and sliding mode controls. Six different schemas areproposed: the first one is an MRAC with an artificial neural network and a PID controller whose parameters weretuned by a GA using Pattern Search Optimization. The second scheme is an MRAC controller with an H∞ control(H∞. The third scheme is an MRAC controller with a sliding mode controller (SMC. The fourth scheme is an MRACcontroller with an ANN. The fifth scheme is an MRAC controller with a PID controller optimized by a GA. Finally, thelast scheme is an MRAC classical control system. The objective of this research is to generate more powerful FTCmethods and compare the performance of above schemes under different fault conditions in sensors and actuators.An industrial heat exchanger process was the test bed for these approaches. Simulation results showed that the useof Pattern Search Optimization and ANNs improved the performance of the FTC scheme because it makes the controlsystem more robust against sensor and actuator faults.

  4. Estimating the Return on Investment Opportunities in Financial Markets and Establishing Optimized Portfolio by Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Farzad Karimi

    2013-07-01

    Full Text Available This project is looking for increasing return on investment, by presenting models based on artificial intelligence. Investment in financial markets could be considered in short-term (daily and middle-term (monthly basis/ hence the daily data in Tehran Stock Exchange and the rates of foreign exchange and gold coins have been extracted for the period Mar. 2010 to Sep. 2012 and recorded as the data into the neural networks and the genetic programming model. Also the monthly rate of return and risk of 20 active companies of the stock exchange, and the monthly risk values of foreign exchange and gold coin, as well as bank deposits were used as genetic algorithms in order to provide optimum investment portfolios for the investors. The results obtained from executing the models indicates the efficiency of both methods of artificial neural network and also genetic programming in the short-term financial markets predictions, but artificial neural networks show a better efficiency. Also the efficiency of geneticalgorithm was approved in improving the rate of return and risks, via identifying the optimum investment portfolios.

  5. Artificial Intelligence Techniques for the Estimation of Direct Methanol Fuel Cell Performance

    Science.gov (United States)

    Hasiloglu, Abdulsamet; Aras, Ömür; Bayramoglu, Mahmut

    2016-04-01

    Artificial neural networks and neuro-fuzzy inference systems are well known artificial intelligence techniques used for black-box modelling of complex systems. In this study, Feed-forward artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used for modelling the performance of direct methanol fuel cell (DMFC). Current density (I), fuel cell temperature (T), methanol concentration (C), liquid flow-rate (q) and air flow-rate (Q) are selected as input variables to predict the cell voltage. Polarization curves are obtained for 35 different operating conditions according to a statistically designed experimental plan. In modelling study, various subsets of input variables and various types of membership function are considered. A feed -forward architecture with one hidden layer is used in ANN modelling. The optimum performance is obtained with the input set (I, T, C, q) using twelve hidden neurons and sigmoidal activation function. On the other hand, first order Sugeno inference system is applied in ANFIS modelling and the optimum performance is obtained with the input set (I, T, C, q) using sixteen fuzzy rules and triangular membership function. The test results show that ANN model estimates the polarization curve of DMFC more accurately than ANFIS model.

  6. Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

    Science.gov (United States)

    Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

    2015-01-01

    Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

  7. The Effects of Textisms on Learning, Study Time, and Instructional Perceptions in an Online Artificial Intelligence Instructional Module

    Science.gov (United States)

    Beasley, Robert; Bryant, Nathan L.; Dodson, Phillip T.; Entwistle, Kevin C.

    2013-01-01

    The purpose of this study was to investigate the effects of textisms (i.e., abbreviated spellings, acronyms, and other shorthand notations) on learning, study time, and instructional perceptions in an online artificial intelligence instructional module. The independent variable in this investigation was experimental condition. For the control…

  8. An Artificial Intelligence Approach to the Symbolic Factorization of Multivariable Polynomials. Technical Report No. CS74019-R.

    Science.gov (United States)

    Claybrook, Billy G.

    A new heuristic factorization scheme uses learning to improve the efficiency of determining the symbolic factorization of multivariable polynomials with interger coefficients and an arbitrary number of variables and terms. The factorization scheme makes extensive use of artificial intelligence techniques (e.g., model-building, learning, and…

  9. Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

    Science.gov (United States)

    Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W.

    2003-01-01

    Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

  10. Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

    Science.gov (United States)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

    This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

  11. Use of artificial intelligence techniques for visual inspection systems prototyping. Application to magnetoscopy

    International Nuclear Information System (INIS)

    The automation of visual inspection is a complex task that requires collaboration between experts, for example inspection specialist, vision specialist. on-line operators. Solving such problems through prototyping promotes this collaboration: the use of a non specific programming environment allows rapid, concrete checking of method validity, thus leading incrementally to the final system. In this context, artificial intelligence techniques permit easy, extensible, and modular design of the prototype, together with heuristic solution building. We define and achieve the SPOR prototyping environment, based on object-oriented programming and rules-basis managing. The feasibility and the validity of an heuristic method for automated visual inspection in fluoroscopy have been proved through prototyping in SPOR. (author)

  12. Evolution of research in the field of artificial intelligence in Ukraine and the World

    Directory of Open Access Journals (Sweden)

    Oleksandr Podgayetsky

    2012-12-01

    Full Text Available The article demonstrates the way artificial intelligence science has passed since the 1950s up to now. The work concerns the important development stages of AI in Ukraine and the world. In particular, the work highlights the history of AI as the history of neurocomputers, heuristic programs and chess programs; history of biological cybernetics and evolution of the theory of pattern recognition and speech recognition. The article illustrates scientific contribution to this problem by native scientists N.M. Amosov, V.A. Kovalevsky, M.I. Schlesinger, T.K. Vintsiuk, M.M. Botvinnik, D.A. Pospelov and T.A. Taran. There are provided materials showing that the domestic reading machine «CHARS» was not inferior to similare of Western standards, while remaining economical. The author examines the development of «softwareinterlocutors » and expert systems.

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

    International Nuclear Information System (INIS)

    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)

  14. 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.

  15. Development of a Car Racing Simulator Game Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Marvin T. Chan

    2015-01-01

    Full Text Available This paper presents a car racing simulator game called Racer, in which the human player races a car against three game-controlled cars in a three-dimensional environment. The objective of the game is not to defeat the human player, but to provide the player with a challenging and enjoyable experience. To ensure that this objective can be accomplished, the game incorporates artificial intelligence (AI techniques, which enable the cars to be controlled in a manner that mimics natural driving. The paper provides a brief history of AI techniques in games, presents the use of AI techniques in contemporary video games, and discusses the AI techniques that were implemented in the development of Racer. A comparison of the AI techniques implemented in the Unity platform with traditional AI search techniques is also included in the discussion.

  16. The Use of Means of Artificial Intelligence for the Decision Making Support on Financial Markets

    OpenAIRE

    Vrba, Patrik

    2013-01-01

    Diplomová práce se zaměřuje na aplikaci nástrojů umělé inteligence pro predikce vývoje finančních trhů. Hlavní důraz je kladen na vyhodnocení využitelnosti neuronových sítí, pro stanovení predikcí na devizových trzích. Zároveň je poskytnut návrh řešení, pro plně automatizované zpracování tržních dat a následné generování obchodních příkazů. This Master's thesis focuses on applying artificial intelligence tools for the prediction of development financial markets. Major emphasis is placed on...

  17. Artificial intelligence search techniques for optimization of the cold source geometry

    International Nuclear Information System (INIS)

    Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness which produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometrical shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape which is the unknown in such a study. We draw an analogy between this problem and a state space search, then we use a simple Artificial Intelligence (AI) search technique to determine the optimum cold source shape based on a two-group, r-z diffusion model. We implemented this AI design concept in the computer program AID which consists of two modules, a physical model module and a search module, which can be independently modified, improved, or made more sophisticated. 7 refs., 1 fig

  18. EXPERIMENTS AND RESULTS ON THE USE OF ONTOLOGIES IN THE ARTIFICIAL INTELLIGENCE DOMAIN

    Directory of Open Access Journals (Sweden)

    Vasile-Daniel Păvăloaia

    2012-10-01

    Full Text Available The field of agent-based systems as part of the Artificial Intelligence domain is, now-a-days, quite popular. There are specialized technologies required for building software agents and it should be communicative, capable, autonomous and adaptive. In fact, these are the key characteristics required to help make the Internet activity more successful. The limiting factors in building such systems are being overcome, and new approaches are emerging from information technology research laboratories around the world. The use of ontology has proven to be essential elements in many applications and thus, they have been successfully applied in agent systems technology, knowledge management systems, and e-commerce platforms. The current research aims to present besides some theoretical aspects and examples of using the web agents for two European cities.

  19. An application of artificial intelligence to the interpretation of mass spectra.

    Science.gov (United States)

    Buchanan, B. G.; Duffield, A. M.; Robertson, A. V.

    1971-01-01

    Description of the DENDRAL (Dendritic Algorithm) project, the objectives of which were to base the computer program on an alogorithm that generates an exhaustive, nonredundant list of all the structural isomers of a given chemical composition, and to devise a computer program that would perform an organic structure determination, given a molecular formula and a mass spectrum. This program is called 'Heuristic DENDRAL' and it operates by using the known structure/spectrum correlations to constrain the DENDRAL isomer generator to produce a single isomer for that composition. The collaboration of chemists and computer scientists has produced a tool of some practical utility from the chemical viewpoint, and an interesting program from the viewpoint of artificial intelligence.

  20. Words: blocks, amoebas, or patches of fog? Artificial intelligence and the conceptual foundations of fuzzy logic

    Science.gov (United States)

    Jaki, Stanley L.

    1996-06-01

    Words are the fundamental carriers of information. Words that refer to numbers stand apart from all other words in one respect: Numbers are concepts that lend themselves to spatial representations with exact contours. Yet the verbal definition of numbers, through which their meaning is defined, shares in a property common to all words: their verbal definition cannot be given a spatial representation with exact contours. In that definitional respect, words are not even comparable to amoebas which, although they constantly change their shapes, have clear boundaries. Words are best to be likened to patches of fog that not only change but have no strict boundaries. While this does not land all discourse in the realm of half-truths, it sets basic limits to what can be achieved by fuzzy logic and programs of artificial intelligence.