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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： A. Danak A.R. Kian Control and Intelligent Processing Center for Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Game theory deals with decision-making processes involving two or more parties with partly or completely conflicting interests. The players involved in the game usually make their decisions under conditions of risk or uncertainty. In this paper, an idea of nondeterministic payoffs is proposed and optimization is done in a more realistic fuzzy environment, helping each player describe his goal functions by using the linguistic variables. Since fuzzy numbers represent uncertain numeric values, their substitution for traditional crisp payoff values is described and their application is surveyed for a specific sample of contributive games - the game of civic duty. A closed formulation is developed for a vast general class of vague payoffs

关键词： Game theory Decision making Fuzzy sets Process control Intelligent control Uncertainty Cost function Probability distribution Artificial intelligence

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A new approach to H/sub /spl infin// controller design with regional pole assignment

A new approach to H/sub /spl infin// controller design with ...

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International Conference on control and Automation (ICCA)

作者： A. Adhami-Mirhosseini O. Namaki-Shoushtari M.J. Yazdanpanah Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

This paper addresses the design of state feedback H/sub /spl infin//, robust controller that satisfies additional constraints on closed-loop poles location. Desired closed-loop poles location is considered to be a clipped sector, corresponding to some performance specifications such as suitable settling time and overshoot. In order to solve the H/sub /spl infin// optimization problem with two Lyapunov constraints, the Lagrange multiplier is used. It is shown that the appropriate controller is characterized by three coupled algebraic Riccati equations. The validity and applicability of this approach are illustrated by two benchmark examples and the results are compared with those of the conventional H/sub /spl infin// control problem and related works.

关键词： State feedback Riccati equations Constraint optimization Uncertainty Stability Output feedback Attenuation Robust control Lagrangian functions Design optimization

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A fuzzy approach to modeling the knowledge of decision-makers

A fuzzy approach to modeling the knowledge of decision-maker...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： A. Danak F. Rastegar A.R. Kian Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

A game is a decision making situation in which each player attempts to act in such a way that the game's circumstances get close to what desirable for him. To reach this goal, a player needs to have a suitable estimation of the other players' decisions. In this paper, we propose a fuzzy approach by which a player can attain an estimation of the other players' actions and pursue a strategy which maximizes its performance. Finally, the results of applying the proposed approach to the well-known "prisoner's dilemma" problem are brought to show the effectiveness of the method

关键词： Game theory Fuzzy sets Uncertainty Application software Process control Intelligent control Decision making History Books Operations research

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Network routing based on reinforcement learning in dynamically changing networks

Network routing based on reinforcement learning in dynamical...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： S. Khodayari M.J. Yazdanpanah Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper we propose a reinforcement learning (RL) algorithm for packet routing in computer networks with emphasis on different traffic conditions. It is shown that routing with an RL approach, considering the traffic, can result in shorter delivery time and less congestion. A simple, but rational simulation of a computer network has also been tested and the suggested algorithm has been compared with other conventional ones. At the end, it is concluded that the suggested algorithm can perform packet routing efficiently with advantage of considering the dynamics in a real network

关键词： Routing Learning Intelligent networks computer networks Traffic control Communication system traffic control Artificial intelligence Telecommunication traffic Computational modeling computer simulation

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Improved genetic algorithm for integrated steelmaking optimum charge plan

Improved genetic algorithm for integrated steelmaking optimu...

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作者： Xue, Yun-Can Wang, Xin Li, Shao-Yuan College of Computer and Information Engineering Hohai University Changzhou China Institute of Information and Control Technology Center of Electrical and Electronic Technology Shanghai Jiao Tong University Shanghai China Institute of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)008045108X

The shortcoming of the standard genetic algorithm is analysed. an improved genetic algorithm with modified mutation operator and adaptive probabilities of crossover and mutation is proposed. Simulation experiments have been carried and the results show that the modifications are very effective. in this paper, an optimum charge plan for steelmaking continuous casting production scheduling is also studied. The charge plan model is established. The modified genetic algorithm is used to solve the optimum charge plan problem. The computation with practical data shows that the model and the modified genetic algorithm are very effective. Copyright © 2005 IFAC.

关键词： Genetic algorithms

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A NEW ACTIVE QUEUE MANAGEMENT ALGORITHM BASED ON NEURAL NETWORKS PI

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IFAC Proceedings Volumes 2005年第1期38卷 1-6页

作者： M. Yaghoubi Waskasi M.J. Yazdanpanah N. Yazdani Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran P.O. Box: 14395/515 Tehran IRAN

Active Queue Management (AQM) applies a suitable control policy upon detecting congestion in networks. In this paper, an adaptive Proportional-Integral (PI) controller based on Artificial Neural Networks (ANN) is applied to AQM for the objective of congestion avoidance and control in middle nodes. The proposed controller is simple and can be easily implemented in high-speed routers. Neural Network PI (NNPI) dynamically adapts its parameters with respect to changes in the system. It is anticipated that this results in better response compared to linear controllers due to the nonlinear nature of NNPI. We simulated our method in ns2 and compared its performance with the conventional PI controller. The simulation results show NNPI yields better performance.

关键词： Neural Networks Queuing Network Models Nonlinear Systems computer Networks PI controllers

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Feature selection and combination criteria for improving predictive accuracy in protein structure classification

Feature selection and combination criteria for improving pre...

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BIBE 2005: 5th IEEE Symposium on Bioinformatics and Bioengineering

作者： Lin, Chun Yuan Lin, Ken-Li Huang, Chuen-Der Chang, Hsiu-Ming Yang, Chiao Yun Lin, Chin-Teng Tang, Chuan Yi Hsu, D. Frank Institute of Molecular and Cellular Biology National Tsing Hua University Hsinchu Taiwan Brain Research Center National Tsing Hua University Hsinchu Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan Department of Electrical and Control Engineering National Chiao Tung University Hsinchu Taiwan Computer Center Chung Hua University Hsinchu Taiwan Department of Electrical Engineering Hsiuping Institute of Technology Tachung Taiwan Department of Computer and Information Science Fordham University New York NY 10023 United States

ISBN: (纸本)0769524761

The classification of protein structures is essential for their function determination in bioinformatics. The success of the protein structure classification depends on two factors: the computational methods used and the features selected. In this paper, we use a combinatorial fusion analysis technique to facilitate feature selection and combination for improving predictive accuracy in protein structure classification. When applying these criteria to our previous work, the resulting classification has an overall prediction accuracy rate of 87% for four classes and 69.6% for 27 folding categories. These rates are significantly higher than our previous work and demonstrate that combinatorial fusion is a valuable method for protein structure classification. © 2005 IEEE.

关键词： Proteins

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LOCALLY CONSTRAINED OPTIMAL AND GLOBALLY STABLE BACKSTEPPING DESIGN

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IFAC Proceedings Volumes 2005年第1期38卷 925-930页

作者： A. Adhami M.J. Yazdanpanah Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran. P.O.Box:14395/515

Robust nonlinear controller design with constraint on the poles’ location of the linear part of closed-loop system is proposed. The design method is based on the integrator backstepping procedure and linear constrained H ∞ for nonlinear strict-feedback systems with disturbance also in strict-feedback form. The resulted closed-loop system will be globally stable, while both local robustness and desired α- stability are achieved. An analytic example is used to compare the performance of the proposed methodology with that of the locally optimal backstepping design with no closed-loop poles constraint.

关键词： Nonlinear control systems H-infinity control constrained poles disturbance attenuation global stability

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Continuous time system identification of nonparametric models with constraints

Continuous time system identification of nonparametric model...

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作者： Wang, Liuping Gawthrop, Peter J. Young, Peter C. School of Electrical and Computer Engineering RMIT University Melbourne Australia Center for Systems and Control Department of Mechanical Engineering University of Glasgow Glasgow G12 8QQ United Kingdom Centre for Research on Environmental Syst. and Stat. Lancaster University LA1 4 YQ United Kingdom

ISBN: (纸本)008045108X

Although structural constraints such as model order and time delay have been incorporated in the continuous time system identification since its origin, the constraints on the estimated model parameters were rarely enforced. This paper proposes a continuous time system identification approach with constraints. It shows that by incorporating physical parameter information known a priori as hard constraints, the traditional parameter estimation schemes are modified to minimize a quadratic cost function with linear inequality constraints. Using the structure of Frequency Sampling Filters as the vehicle, the paper shows that the constraints can be readily imposed on continuous time frequency response estimation and step response estimation. in particular, a priori knowledge in both time-domain and frequency domain is utilized simultaneously as the constraints for the optimal parameter solution. A Monte-Carlo simulation study with 100 noise realization is used to demonstrate the improvement of the estimation results in terms of continuous time frequency response and continuous time step response. Copyright © 2005 IFAC.

关键词： Frequency response

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Identification of multivariable systems based on finite impulse response models with flexible orders

Identification of multivariable systems based on finite impu...

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IEEE International Conference on Mechatronics and Automation

作者： Feng Ding Tongwen Chen Control Science and Engineering Research Center Southern Yangtze University Wuxi China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

For multi-input, multi-output stochastic systems, by means of auxiliary models - finite impulse response (FIR) models, we develop an identification algorithm to estimate the FIR model parameters of each entry (sub-submodel) of transfer matrices with an increasing order for the FIR model. The basic idea is to use auxiliary models to predict/estimate the outputs of the sub-submodels, and further to use the recursive least squares algorithm or the Pade approximation method to produce the parameter estimates of sub-submodels. Some simulation results are included.

关键词： MIMO Finite impulse response filter Parameter estimation Least squares approximation Predictive models Recursive estimation Stochastic systems Approximation algorithms Approximation methods System identification

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