NDLI: An incremental modeling approach with a hierarchical structure and progressive accuracy using dyadic wavelet-based neural networks

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2005 Intelligent Systems Application to Power Systems - Welcome to ISAP 2005

2005 Intelligent Systems Application to Power Systems - Committee Listing

2005 Intelligent Systems Application to Power Systems - Preface

2005 Intelligent Systems Application to Power Systems - Sponsors

2005 Intelligent Systems Application to Power Systems - author index

2005 Intelligent Systems Application to Power Systems - Copyright

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Artificial Neural Network based Method for Fault Location in Distribution Systems

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On-line fault diagnosis with incomplete information in a power transmission network

An expert system for diagnosis of digital relay operation

Incremental knowledge-based partial discharge diagnosis in oil-filled power transformers

Overview of intelligent systems for naval shipboard systems

A multi-agent based algorithm for mesh-structured shipboard power system reconfiguration

An incremental modeling approach with a hierarchical structure and progressive accuracy using dyadic wavelet-based neural networks

Multi-agent system for diagnostics, monitoring and control of electric systems

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Multimachine power system stabilizer design based on a simplified version of genetic algorithms combined with learning

Coordinated tuning of AVRs and PSSs by multiobjective genetic algorithms

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An evolutionary computation solution to the governor-turbine parameter estimation problem

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New parallel radial basis function neural network for voltage security analysis

Dynamic voltage stability assessment and control by computational intelligence

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Expert symbolic transient simulator based on quadratic integration method

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A novel H/sub /spl infin// based controller for wind turbine applications operating under unbalanced voltage conditions

Contribution of power electronics for load frequency control of interconnected power system

Output power leveling of wind turbine generators using pitch angle control for all operating regions in wind farm

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Experimental study on rotary frequency converter

Concepts and approaches in multi-agent systems for power applications

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Decentralized approach to normal operations for power system network

Hierarchical stabilization control with upper level multi-agent based controller and lower level local controller

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Absolute stochastic simulated annealing approach to unit commitment problem

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ANN-based risk assessment for short-term load forecasting

Probabilistic short-term load forecasting with Gaussian processes

A market-based analysis on the generation expansion planning strategies

Impact of inter-regional energy trade on the net welfare of an individual market

Payment minimization auction for deregulated electricity markets considering transmission capacity constraints

Replicator agents for electricity markets

Evolving agents in a market simulation platform - a test for distinct meta-heuristics

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Particle swarm optimization for economic dispatch of units with non-smooth input-output characteristic functions

Adaptive unit commitment strategy for sudden load demand change

Comparison of two metaheuristics with mathematical programming methods for the solution of OPF

Para-consistent case-based reasoning

Unit commitment using adaptive dynamic programming

Modeling a decision maker

A polynomial chaos theory approach to uncertainty in electrical engineering

Computation of Contingency Probabilities for Electric Transmission Decision Problems

Market feedback for bounding future uncertainties in power system planning

Dynamic planning of medium voltage open-loop distribution networks under uncertainty

Proceedings of International Conference on Intelligent System Application to Power Systems

An incremental modeling approach with a hierarchical structure and progressive accuracy using dyadic wavelet-based neural networks

Content Provider	IEEE Xplore Digital Library
Author	Song, Y. Ponci, F.
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. Eng., South Carolina Univ., Columbia, SC (Song, Y.; Ponci, F.)
Abstract	The wavelet neural network (WNN) is a recently developed mathematical tool that can be used in nonlinear system modeling. Motivated by the multi-resolution definition in multi-resolution approximation theory, this paper proposes a novel WNN-based modeling approach possessing two unique characteristics. Firstly, a multi-resolution system model, having an output corresponding to each resolution, is developed from a coarser approximation to a finer representation by adding more details progressively. Secondly, the model at a low resolution is compatible with the model at a high resolution, which means that the well trained WNNs used in a low resolution can be directly incorporated into a high resolution without any modification. The theoretical verification of this approach shows that the incremental characteristic and the compatibility feature of the system modeling at different resolutions is guaranteed by the definition of the modeling subspace division and by the utilization of the dyadic activation functions in WNNs. As a result, by applying this technology into electric ship design and simulation, different users can activate different resolutions according to their requirements during model utilization. At the same time, the compatible modeling structure avoids a large amount of modeling repetition for model developers and thus lightens the computational burden
File Size	393095
File Format	PDF
ISBN	1599751747
DOI	10.1109/ISAP.2005.1599262
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	ISAP
Subject Keyword	Waste management Computational modeling Neural networks Buildings Stochastic processes Mathematical model Approximation methods Nonlinear systems Marine vehicles Contracts
Content Type	Text
Resource Type	Article

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