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International Joint Conference on Neural Networks (IJCNN)

作者： G.G. Lendaris R.A. Santiago M.S. Carroll Systems Science and of Electrical & Computer Engineering Northwest Computational Intelligence Laboratory Portland State University Portland OR USA Systems Science Program Northwest Computational Intelligence Laboratory Portland State University Portland OR USA

Adaptive critics have shown much promise for designing optimal nonlinear controllers in an off-line context. Still, their greatest potential exists in the context Of reconfigurable control, that is, real time controller redesign in response to (substantial) changes in plant dynamics. To accomplish this, a framework is proposed for the application of adaptive critics in real-time control (for those critic methods requiring a model of the plant). The framework is presented in the context of work being done in reconfigurable flight control by the NW Computational Intelligence Lab (NWCIL) at Portland State University. The proposal incorporates recent work (by others) in fast and efficient on-line plant identification, considerations for bounding the computational costs of converging neural networks, and a novel approach (by us) toward the task of assuring system stability during the adaptation process. The potential and limitations of the proposed framework are discussed. It is suggested that with the recent rapid reduction in computational barriers, only certain theoretical issues remain as the central barriers to successful on-line application of the methods.

关键词： programmable control Adaptive control Optimal control Neural networks Computational intelligence Control systems Stability State-space methods Design methodology Piecewise linear approximation

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Knowledge Acquisition for Adversary Course of Action Prediction Models

Knowledge Acquisition for Adversary Course of Action Predict...

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2002 AAAI Fall Symposium

作者： Brown, Scott M. Santos, Eugene Bell, Benjamin Electronic Systems Center Information Operations Program Office 240 Hall Blvd Suite 105 San AntonioTX78243-7058 United States University of Connecticut Dept of Computer Science & Engineering UTEB 191 Auditorium Rd. U-155 StorrsCT06269-3155 United States CHI Systems Inc. 1035 Virginia Drive Suite 300 Ft. WashingtonPA19034-3107 United States

Intelligence Preparation of the Battlespace (IPB) is a predominantly "gray matter-based" fusion and information synthesis process conducted to predict possible future adversary courses of action. The purpose is to understand where the enemy is in the battlespace, and to infer what we believe he will do next. From that understanding, military commanders plan their own course of action. As the state of the art improves, we are in a position to begin applying technologies to move the labor-intensive parts of IPB to the computer, allowing the planner to perform those tasks that are more suited to human capabilities. This is a primary focus of our research effort. This paper presents the approaches that we are adopting to acquire the knowledge necessary to build models to assist decision makers determine adversary intent. We discuss how the IPB process can assist with knowledge acquisition and we present a detailed discussion of our AII system and the techniques we have developed to collect and process the data necessary to map observations of the adversary into evidence to support reasoning about the adversary’s intent. Copyright © 2002, AAAI (***). All rights reserved.

关键词： Knowledge acquisition

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An efficient heuristic for routing and wavelength assignment in optical WDM networks

An efficient heuristic for routing and wavelength assignment...

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IEEE International Conference on Communications (ICC)

作者： Yongbing Zhang K. Taira H. Takagi S.K. Das Institute of Policy and Planning Sciences University of Tsukuba Tsukuba Ibaraki Japan Doctoral Program in Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan Department of Computer Science and Engineering University of Texas Arlington TX USA

ISBN: (纸本)0780374002

We propose an efficient heuristic algorithm that sets up and releases lightpaths for connection requests dynamically. We partition the routing and wavelength assignment (commonly known as RWA) problem into two subproblems and solves both of them using a well-known shortest path routing algorithm. For solving the routing subproblem, an auxiliary graph is created whereby the nodes and links in the original network are transformed to the edges and vertices, respectively, and the availability of each wavelength on the input and output links of a node as well as the number of available wavelength converters are taken into account in determining the weights of edges. Furthermore, for solving the wavelength assignment subproblem, an auxiliary graph is also utilized and the cost for wavelength conversion is taken into consideration in the edge weight function. A distinguished feature of our algorithm is that it employs more accurate network information on the availability of both the wavelengths and the wavelength converters than the existing algorithms in deciding the routing and the wavelength assignment. Simulation results show that our algorithm performs much better than previously proposed algorithms with comparable computation time, especially when the number of wavelengths is large while the number of converters at each node is limited.

关键词： Wavelength routing Wavelength assignment Optical fiber networks WDM networks Optical wavelength conversion Partitioning algorithms Heuristic algorithms Cost function Availability Computational modeling

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A soft expert system for the creative exploration of first principles of crystal-laser design

A soft expert system for the creative exploration of first p...

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IEEE International Conference on systems, Man and Cybernetics

作者： S.H. Rubin R.J. Rush M.H. Smith S.N. Jayaram Murthy L. Trajkovic SPAWAR Systems Center San Diego CA USA BISC Program University of California Berkeley CA USA Department of Computer Science Central Michigan University Mount Pleasant MI USA School of Engineering Science Simon Fraser University Burnaby BC Canada

A soft expert system is defined to be one that is qualitatively fuzzy. We present such a system known as KASER which stands for Knowledge Amplification by Structural Expert Randomization. KASER facilitates reasoning using domain specific expert and commonsense knowledge. It accomplishes this through object-classed predicates and an associated novel inference engine. It addresses the high cost associated with the knowledge acquisition bottleneck. It also enables the entry of a basis of rules and provides for the automatic extension of that basis through domain symmetries. We demonstrate an application for KASER in the design of an intelligent tutoring system that teaches the basic science of crystal-laser design. It enables the student to experiment with various design concepts and receive feedback on the functionality of the proposed design. This is possible without a need to preprogram all possible scenarios.

关键词： Expert systems Knowledge acquisition Intelligent systems USA Councils Engines Costs Production systems computer errors Hybrid intelligent systems Fuzzy systems

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A freshman engineering course which introduces engineering design and engineering fundamentals in the context of a unifying theme

A freshman engineering course which introduces engineering d...

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2001 ASEE Annual Conference and Exposition: Peppers, Papers, Pueblos and Professors

作者： Wilk, Richard D. Traver, Cherrice LaPlante, Christine Hedrick, James Keat, William D. Wicks, Frank E. Division of Engineering Union College Schenectady NY Computer Systems Engineering Program Department of Civil Engineering Union College Department of Mechanical Engineering Union College

A revision of Union College's Introduction to engineering and computer Science course is presented. The change include the introduction of a design project and competition, the presentation of engineering and computer science concepts under a unifying theme, and the introduction of weekly talks from outside speakers. The course instruction also changed from a series of modules taught by different faculty to a structure in which all the faculty taught all the topics in the course. If this approach is used with a group of cooperative faculty, the benefits of the exposure to different teaching styles and understanding of other disciplines can be positive.

关键词： engineering education

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AUTO WIS ARD: Unsupervised modes for the WISARD

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6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001

作者： Wickert, Iuri Fraņca, Felipe M. G. Computer Systems Engineering Program - COPPE UFRJ Caixa Postal 68511 21945-970 Rio de Janeiro RJ Brazil

ISBN: (纸本)3540422358

This work in traducest wo new unsupervised learning algorithms based on the WISARD weightless neural classifier model. The first one, the standard AUTOWISARD model, is able to perform fast one-shot, learning of unsorted sets of input patterns. The second oik? is a recursive version of AUTOWISARD which not only keeps the good features of the basic model, agility, plasticit v and stability', but also produces hierarc hically structured tree-lik? classifications. Although the standard A UT(WISARD model exhibits good classification skills when exposed to symbolic patterns (by producing only few classes containing patterns of different meanings), its recursive version produces even less confusing classes. The stability of both learning algorithms is also demonstrated. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Learning algorithms

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From standard to non-standard semantics by semantics modifiers

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International Journal of Foundations of computer Science 2001年第2期12卷 171-211页

作者： Abramov, Sergei Glück, Robert Program Systems Institute Russian Academy of Sciences RU-152140 Pereslavl-Zalessky Russian Federation Department of Information and Computer Science School of Science and Engineering Waseda University Shinjuku-ku Tokyo 169-8555 Japan

An approach for systematically modifying the semantics of programming languages by semantics modifiers is described. Semantics modifiers are a class of programs that allow the development of general and reusable semantics components. Language independence is achieved through the interpretive approach: an interpreter serves as a mediator between the new language and the language for which the non-standard semantics was implemented. Inverse computation, equivalence transformation and neighborhood analysis are shown to be semantics modifiers. Experiments with these modifiers show the computational feasibility of this approach. Seven modifier projections are given which allow the efficient implementation of non-standard interpreters and non-standard compilers by program specialization or other powerful program transformation methods. © 2001 World Scientific Publishing Company.

关键词： interpreters non-standard semantics partial evaluation program transformation programming languages supercompilation

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A theoretical model for autism

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Journal of Theoretical Medicine 2001年第4期3卷 271-286页

作者： Vidal De Caralho, Luís Alfred De Carvalho Ferreifa, Níve Fiszman, Adriana Program of Systems Engineering and Computer Science RJ Brazil Institute of Psychiatry Rio de Janeiro Brazil

Autism is a mental disorder characterized by deficits in socialization, communication, and imagination. Along with the deficits, autistic children may show savant skills ("islets of ability") of unknown origin that puzzles their families and the psychologists. Comorbidity with epilepsy and mental retardation has brought the researchers' attention to neurobiological and cognitive theories of the syndrome. The present article proposes a neurobiological model for the autism based on the fundamental biological process of neuronal competition. A neural network capable of defining neural maps-synaptic projections preserving neighborhoods between two neural tissues-simulates the process of neurodevelopment. Experiments were performed reducing the level of neural growth factor released by the neurons, leading to ill-developed maps and suggesting the cause of the aberrant neurogenesis present in autism. The computer simulations hint that brain regions responsible for the formation of higher level representations are impaired in autistic patients. The lack of this integrated representation of the world would result in the peculiar cognitive deficits of socialization, communication, and imagination and could also explain some "islets of abilities", like excellent memory for raw data and stimuli discrimination. The neuronal model is based on plausible biological findings and on recently developed cognitive theories of autism. Close relations are established between the computational properties of the neural network model and the cognitive theory of autism denominated "weak central coherence", bringing some insight to the understanding of the disorder.

关键词： Autism Cortical maps Neural networks Neurodevelopment Plasticity Weak central coherence

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Robust /spl Hscr//sub /spl infin// filtering for uncertain discrete-time state-delayed systems

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IEEE Transactions on Signal Processing 2001年第8期49卷 1696-1703页

作者： R.M. Palhares C.E. de Souza P.L. Dias Peres Graduate Program in Electrical Engineering Pontifical Catholic University of Minas Gerais Belo Horizonte Brazil Department of Systems and Control Brazil School of Electrical and Computer Engineering State University of Campinas-UNICAMP Campinas Brazil

This paper addresses the problem of robust /spl Hscr//sub /spl infin// filtering for linear discrete-time systems subject to parameter uncertainties in the system state-space model and with multiple time delays in the state variables. The uncertain parameters are supposed to belong to a given convex bounded polyhedral domain. A methodology is developed to design a stable linear filter that assures asymptotic stability and a prescribed /spl Hscr//sub /spl infin// performance for the filtering error, irrespective of the uncertainty and the time delays. The proposed design is given in terms of linear matrix inequalities, which has the advantage in that it can be implemented numerically very efficiently.

关键词： Filtering Nonlinear filters Delay effects Uncertainty Noise robustness Uncertain systems Linear matrix inequalities Signal design Riccati equations Context modeling

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Fuzzy Bayes predictor in electric load forecasting

Fuzzy Bayes predictor in electric load forecasting

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International Joint Conference on Neural Networks (IJCNN)

作者： M.A. Teixeira G. Zaverucha V.N.A.L. da Silva G.F. Ribeiro Systems Engineering and Computer Science Program Graduate Programs in Engineering COPPE Federal University of Rio de Janeiro Brazil Electric Power Research Center CEPEL CEPEL Brazil

ISBN: (纸本)0780370449

We present the fuzzy Bayes predictor (FBP), a hybrid system for the task of monthly electric load forecasting. The FBP is a modification we introduce in the naive Bayes classifier in order to enable it to predict numerical values. We consider three versions of the FBP, each one with a different dependence among the input data: independence, first-order and second-order dependence. For verifying the efficiency of the FBP's prediction, we compare it with two fuzzy systems and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.

关键词： Load forecasting Fuzzy systems Power engineering and energy Smoothing methods Testing Niobium compounds systems engineering and theory computer science Predictive models Electric variables measurement

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