Journal ArticleDOI
A comparative study of Artificial Bee Colony algorithm
Dervis Karaboga,Bahriye Akay +1 more
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Results show that the performance of the ABC is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters.About:
This article is published in Applied Mathematics and Computation.The article was published on 2009-08-01. It has received 2835 citations till now. The article focuses on the topics: Artificial bee colony algorithm & Meta-optimization.read more
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New inspirations in swarm intelligence: a survey
TL;DR: This tutorial highlights the most recent nature-based inspirations as metaphors for swarm intelligence meta-heuristics and describes the biological behaviours from which a number of computational algorithms were developed.
Journal ArticleDOI
Parameter identification of solar cells using artificial bee colony optimization
TL;DR: The ABC (artificial bee colony) algorithm is proposed, an evolutionary method inspired by the intelligent foraging behavior of honey bees, which exhibits a better search capacity to face multi-modal objective functions in comparison with other evolutionary algorithms.
Journal ArticleDOI
Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm
TL;DR: An integrated system where wavelet transforms and recurrent neural network (RNN) based on artificial bee colony (abc) algorithm are combined for stock price forecasting is presented and can be implemented in a real-time trading system for forecasting stock prices and maximizing profits.
Journal ArticleDOI
ABCluster: the artificial bee colony algorithm for cluster global optimization.
Jun Zhang,Michael Dolg +1 more
TL;DR: This work introduces a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm, inspired by the foraging behavior of a bee colony, which is applied to several potential functions of quite different nature, and reveals that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum.
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A Novel Artificial Bee Colony Algorithm Based on Modified Search Equation and Orthogonal Learning
TL;DR: An improved ABC method called as CABC is proposed where a modified search equation is applied to generate a candidate solution to improve the search ability of ABC and the orthogonal experimental design (OED) is used to form an Orthogonal learning (OL) strategy for variant ABCs to discover more useful information from the search experiences.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Book
Self-Organizing Maps
TL;DR: The Self-Organising Map (SOM) algorithm was introduced by the author in 1981 as mentioned in this paper, and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technologies have already been based on it.
Book
Genetic Algorithms + Data Structures = Evolution Programs
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.