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neural networks: advances And Applications edited by E. Gelenbe North-Holland, Amsterdam, 1992, ix + 222 pp., distributed in USA and Canada by Elsevier Science Publishing Co., New York (Hardcover $108;paperback £24.95). - An Introduction To The Modeling Of neural networks, by P. Peretto. Collection Alea-Saclay: Monographs and Texts in Statistical No. 2, Cambridge University Press, 1992, xviii + 473 pp., (£60.00, Hardback);£24.95, Paperback) - neural networks For systems And control, edited by K. Warwick, Irwin G.W. and Hunt K.J. iee control Engineering Series no. 46, Peter Peregrinus, London, on behalf of Institution of Electrical Engineers, London, 1992, xiii + 260pp., (Hardcover, £39.00).

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Robotica 2009年第6期11卷 586-586页

作者： Alex M. Andrew Splatt Mill Chillaton Lifton PL16 OBJ Devon (UK)

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Transient stability control of multimachine power systems using flywheel energy injection

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iee PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION 2005年第5期152卷 589-596页

作者： Wang, MH Chen, HC Natl Chin Yi Univ Technol Inst Informat & Elect Energy Taichung Taiwan

Owing to advances in many technologies, the high-speed flywheel energy storage system (FESS), flywheel battery, has become a viable alternative to electrochemical batteries and attracted much research attention in recent years. A self-organising fuzzy neural network controller is presented for FESS to improve transient stability and increase transfer capability of power systems. The main difference from a traditional control approach ties in the model-free description of the control system and parallel computing capability. Simulation results from the Taiwan power system (Taipower) show that FESS with the proposed controller has produced significant improvement in power system performance.

关键词： neural networks (Computer science) SIMULATION methods & models ELECTRIC batteries PARALLEL computers ELECTRIC controllers

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Electronic nose: Clinical diagnosis based on soft computing methodologies 1

Electronic nose: Clinical diagnosis based on soft computing ...

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1st International ieeE Symposium on Intelligent systems

作者： Kodogiannis, VS Chountas, P Pavlou, A Petrounias, I Chowdrey, HS Temponi, C Univ Westminster Mechatron Grp Dept Comp Sci London HA1 3TP England

ISBN: (纸本)0780376013

Recently, the use of smell in clinical diagnosis has been rediscovered due to major advances in odour sensing technology and artificial intelligence. It was well known in the past that a number of infectious or metabolic diseases could liberate specific odours characteristic of the disease stage and among others, urine volatile compounds have been identified as possible diagnostic markers. A newly developed electronic nose based on chemoresistive sensors has been employed to identify in vitro 13 bacterial clinical isolates, collected from patients diagnosed with urinary tract infections, gastrointestinal and respiratory infections, and in vivo urine samples from patients with suspected uncomplicated UTI who were scheduled for microbiological analysis in a UK Health Laboratory environment. An intelligent model consisting of an odour generation mechanism, rapid volatile delivery and recovery system, and a classifier system based on a neural networks, genetic algorithms, and multivariate techniques such as principal components analysis and discriminant function analysis-cross validation. The experimental results confirm the validity of the presented methods.

关键词： neural networks genetic algorithms electronic noses microbial analysis

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On-line dynamic security contingency screening using artificial neural networks

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iee PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION 2000年第6期147卷 367-372页

作者： Chan, KW Edwards, AR Dunn, RW Daniels, AR Hong Kong Polytech Univ Dept Elect Engn Hong Kong Hong Kong Peoples R China Avantage Syst Ltd Colchester CO4 3FP Essex England Univ Bath Sch Elect & Elect Engn Bath BA2 7AY Avon England

On-line dynamic security analysis has now become realistic due to advances in computer technology and algorithms for security assessment. Details of pattern recognition based electro, mechanical stability screens which have been implemented within a dynamic security assessor are presented. Use of statistical functions of features is shown to overcome the dimensionality problem of applying pattern recognition techniques to large power systems. The low computational cost of this approach coupled with efficient operation has resulted in a significant step towards achieving full online dynamic security assessment.

关键词： power system security on-line dynamic security contingency screening Pattern recognition artificial neural networks online dynamic security assessment neural computing techniques Security aspects low computational cost Power engineering computing electromechanical stability screens neural nets pattern recognition power system analysis computing statistical functions dynamic security assessor Power system control power system stability

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A novel radial basis function neural network for fault section estimation in transmission network

A novel radial basis function neural network for fault secti...

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5th International Conference on advances in Power systems control, Operation and Management

作者： Bi, TS Ni, YX Shen, CM Wu, FF Yang, QX Univ Hong Kong Dept Elect & Elect Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)0852967918

In this paper, the application of Radial Basis Function neural Network (RBF NN) to fault section estimation in power systems is addressed. The orthogonal least square algorithm has been extended to optimize the parameters of RBF NN. In order to assess the effectiveness of RBF NN, a classical Back-Propagation neural Network (BP NN) has been developed to solve the same problem for comparison. Computer test is conducted on a 4-bus test system and the test results show that the RBF NN is quite effective and superior to BP NN in fault section estimation.

关键词： Electric power transmission networks

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Intelligent PID controllers for non-linear dynamic systems

Intelligent PID controllers for non-linear dynamic systems

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作者： Zhu, Q.M. Faculty of Engineering University of the West of England Frenchay Campus Coldharbor Lane Bristol BS16 1QY United Kingdom

The author attended the IFAC Workshop on Digital control - past, present, and future of PID control, Teresa, Spain, 5-7 April, 2000 and presented a joint paper. This presentation reports back the development on intelligent PID controller design in the workshop. At present structure of PID controllers is quite different of the original analogue PID controllers, the PID controller design combining with neural networks, fuzzy logic, auto-tuning, and inductive learning mechanisms is one of the key sessions during the workshop, which has attracted scientific specialists in control methodology and users with industrial control applications to work together for the exploitation of these new capabilities.

关键词： Three term control systems

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Genetic learning for direct inverse neural network control

Genetic learning for direct inverse neural network control

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作者： Sharma, S.K. Tokhi, M.O. Department of Automatic Control University of Sheffield United Kingdom

The application of neural networks (NNs) as a direct inverse controller for general nonlinear systems is considered Since little knowledge of the nonlinear plant is normally available, it is difficult to obtain an analytical expression for the plant Jacobian. Thus, an emulator is required as a channel to compute the derivative of the system output with respect to its input for NN training. neural network training using genetic algorithms (GAs) offer several advantages. No understanding of the plant model is required. Also, since no derivative computations are involved, it is less likely for these algorithms to get trapped in local minima. The scheme imitates nature's cleansing phenomena of natural selection and survival of the fittest to generate individual controllers with the best fitness values. A hybrid coding method and several appropriate modifications of the classical genetic algorithms for NN control purposes are discussed. To overcome the difficulties of saturation and fluctuation in the controller output, the output of the NN controller is obtained as the sum of several small sigmoidal functions. This effectively increases the linear range of operation of controller output without affecting the nonlinear feature of a sigmoidal function It is noted in this case that, better control is achieved. Fuzzy logic with dynamic features is used to provide an optimal direction for genetic search. It, thus, speeds up the process of convergence by bringing the chromosomes near to the problem space and bringing more exploration amongst the most desirable ones. The method is demonstrated with the control of a single-link flexible manipulator.

关键词： Learning systems

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On-line implementation of a model predictive controller on a multivariable chemical process

On-line implementation of a model predictive controller on a...

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作者： Yu, D.L. Williams, D. Gomm, J.B. Control Systems Research Group School of Engineering Liverpool John Moores University Byrom Street Liverpool L3 3AF

An investigation into neural network model predictive control is described in this paper. The control strategy developed is applied to a laboratory process to control temperature, pH and dissolved oxygen. The main difficulties in control of this process are non-linearity, coupling effects among variables and long time-delay in the heat exchanger. Parallel neural models are developed from real process data for the use with on-line model predictive control and off-line simulations. The on-line control results are demonstrated.

关键词： neural networks

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Hybrid neural symbolic agent architectures for multimedia

Hybrid neural symbolic agent architectures for multimedia

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Proceedings of the 1998 iee colloquium on neural networks in Interactive Multimedia systems

作者： Wermter, Stefan Univ of Sunderland Sunderland United Kingdom

The general principles of neural and hybrid architectures for multimedia in general are discussed. From the perspective of knowledge engineering, hybrid symbolic/neural agents are advantageous since different mutually complementary properties can be combined. Symbolic representations have advantages with respect to easy interpretation, explicit control, fast initial coding, dynamic variable binding and knowledge abstraction. neural agents show advantages for gradual analog plausibility, learning, robust fault-tolerant processing, and generalization to similar input. Since these advantages are mutually complementary, a hybrid symbolic neural architecture can be useful if different processing strategies have to be supported.

关键词： neural networks

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Proceedings of the 1997 4th International Conference on advances in Power System control, Operation and Management. Part 1 (of 2)

Proceedings of the 1997 4th International Conference on Adva...

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Proceedings of the 1997 4th International Conference on advances in Power System control, Operation and Management. Part 1 (of 2)

The proceedings contains 73 papers from the Fourth International Conference on advances in Power System control, Operation and Management. Topics discussed include: operation development;power research;intelligent control systems;change management;flexible alternating current transmission systems;power system planning;neural networks;integrated fuzzy logic generator controller;adaptive variable window algorithm;digital distance protection;high impedance fault protection;power frequency model;voltage support devices;power system voltage stability;electric load forecasting;and distributed feeder expansion planning method.

关键词： Electric power systems

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