Hybrid neuro-swarm optimization approach for design of distributed generation power systems

The global energy sector faces major challenges in providing sufficient energy to the worlds ever-increasing energy demand. Options to produce greener, cost effective, and reliable source of alternative energy need to be explored and exploited. One of the major advances in the development of this so...

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Bibliographic Details
Published in:	Neural computing & applications Vol. 23; no. 1; pp. 105 - 117
Main Authors:	Ganesan, T., Vasant, P., Elamvazuthi, I.
Format:	Journal Article
Language:	English
Published:	London Springer-Verlag 01.07.2013 Springer
Subjects:	Applied sciences Artificial Intelligence Calculus of variations and optimal control Combinatorics Combinatorics. Ordered structures Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer science; control theory; systems Data Mining and Knowledge Discovery Designs and configurations Exact sciences and technology Image Processing and Computer Vision Learning and adaptive systems Mathematical analysis Mathematics Numerical analysis Numerical analysis. Scientific computation Numerical methods in mathematical programming, optimization and calculus of variations Numerical methods in optimization and calculus of variations Original Article Probability and Statistics in Computer Science Sciences and techniques of general use Hybrid algorithms Particle swarm optimization (PSO) Alternative energy Optimization strategy Hopfield neural networks (HNN) Multi-objective Distributed generation (DG) Hopfield neural nets Wind Neural computation Optimization method Neural network Distributed system System reliability Optimization Pollutant Generation Energy Experimental design Development Objective function Comparative study Generator
ISSN:	0941-0643, 1433-3058
Online Access:	Get full text
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