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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FBI inspired meta-optimization
Jui-Sheng Chou,Ngoc-Mai Nguyen +1 more
TL;DR: This study provided the scientific community with a metaheuristic optimization platform for graphically and logically manipulating optimization algorithms and demonstrated FBI’s robustness, efficiency, stability, and user-friendliness.
Journal ArticleDOI
A modified artificial bee colony algorithm based on converge-onlookers approach for global optimization
Jun Luo,Qian Wang,Xianghai Xiao +2 more
TL;DR: The experimental results tested on numerical benchmark functions show that the COABC algorithm has excellent solution quality and convergence characteristics comparing to basic ABC algorithm and performs better than the state-of-art algorithm in some problems.
Journal ArticleDOI
A multi-threshold segmentation approach based on Artificial Bee Colony optimization
TL;DR: In this article, an image 1-D histogram is approximated through a Gaussian mixture model whose parameters are calculated by the ABC algorithm, each Gaussian function represents a pixel class and therefore a threshold point.
Journal ArticleDOI
Liver segmentation in MRI images based on whale optimization algorithm
TL;DR: This paper proposes an approach for liver segmentation in MRI images based on Whale optimization algorithm (WOA), used to extract the different clusters in the abdominal image to support the segmentation process.
Journal ArticleDOI
Image Processing–Based Classification of Asphalt Pavement Cracks Using Support Vector Machine Optimized by Artificial Bee Colony
TL;DR: This study establishes an intelligent approach for automatic recognition of pavement crack recognition that is compatible with EMMARM, and shows real-time and accurate detection of asphalt pavement crack.
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.