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2015 | OriginalPaper | Buchkapitel

Black Hole Algorithm and Its Applications

verfasst von : Santosh Kumar, Deepanwita Datta, Sanjay Kumar Singh

Erschienen in: Computational Intelligence Applications in Modeling and Control

Verlag: Springer International Publishing

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Abstract

Bio-inspired computation is a field of study that connects together numerous subfields of connectionism (neural network), social behavior, emergence field of artificial intelligence and machine learning algorithms for complex problem optimization. Bio-inspired computation is motivated by nature and over the last few years, it has encouraged numerous advance algorithms and set of computational tools for dealing with complex combinatorial optimization problems. Black Hole is a new bio-inspired metaheuristic approach based on observable fact of black hole phenomena. It is a population based algorithmic approach like genetic algorithm (GAs), ant colony optimization (ACO) algorithm, particle swarm optimization (PSO), firefly and other bio-inspired computation algorithms. The objective of this book chapter is to provide a comprehensive study of black hole approach and its applications in different research fields like data clustering problem, image processing, data mining, computer vision, science and engineering. This chapter provides with the stepping stone for future researches to unveil how metaheuristic and bio-inspired commutating algorithms can improve the solutions of hard or complex problem of optimization.

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Vorheriges Kapitel A Computational Intelligence Optimization Algorithm Based on the Behavior of the Social-Spider

Nächstes Kapitel Genetic Algorithm Based Multiobjective Bilevel Programming for Optimal Real and Reactive Power Dispatch Under Uncertainty

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Titel: Black Hole Algorithm and Its Applications
verfasst von: Santosh Kumar
Deepanwita Datta
Sanjay Kumar Singh
Verlag: Springer International Publishing
Buch: Computational Intelligence Applications in Modeling and Control
Print ISBN: 978-3-319-11016-5

Electronic ISBN: 978-3-319-11017-2

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-11017-2_7

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