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The stability analysis of Bat Algorithm
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017The equations describing the position and movement of the new individuals in Bath Algorithm have the form of difference equations. The analysis of the behavior of solutions of this equation and in particular its stability is possible, after omitting of randomness in parameters and treatment of the algorithm as stationary.
Janusz P. Paplinski +1 more
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Bat Algorithm and Directional Bat Algorithm with Case Studies
2017In recent years, the Bat Algorithm (BA) is becoming a standard optimization tool used by scientists and engineers to solve many problems in different engineering fields. One of the most important characteristics of the bat algorithm is its easy, comprehensible structure which simplifies the computer implementation, in addition to its ability to obtain ...
Asma Chakri, Haroun Ragueb, Xin-She Yang
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On the convergence of a cooperative bat searching algorithm
European Journal of Control, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Bat Algorithm with Adaptive Speed
2019As a famous heuristic algorithm, bat algorithm (BA) simulates the behavior of bat echolocation, which has simple model, fast convergence and distributed characteristics. But it also has some defects like slow convergence and low optimizing accuracy. Facing the shortages above, an optimization bat algorithm based on adaptive speed strategy is proposed ...
Siqing You +3 more
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A double-subpopulation variant of the bat algorithm
Applied Mathematics and Computation, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jun Luo 0003, Liheng Liu, Xianyi Wu
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2013
In this chapter, we present two algorithms that are inspired by the behaviours of bats, i.e., bat algorithm (BaA) and bat intelligence (BI) algorithm. We first describe the general knowledge of the foraging behaviour of bats in Sect. 3.1. Then, the fundamentals and performances of the BaA and BI algorithm are introduced in Sects.
Bo Xing, Wen-Jing Gao
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In this chapter, we present two algorithms that are inspired by the behaviours of bats, i.e., bat algorithm (BaA) and bat intelligence (BI) algorithm. We first describe the general knowledge of the foraging behaviour of bats in Sect. 3.1. Then, the fundamentals and performances of the BaA and BI algorithm are introduced in Sects.
Bo Xing, Wen-Jing Gao
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Bat algorithm with principal component analysis
International Journal of Machine Learning and Cybernetics, 2018The bat algorithm (BA) is a novel evolutionary optimization algorithm, most studies of which have been performed with low-dimensional problems. To test and improve the global search ability of BA with large-scale problems, two new variants using principal component analysis (PCA_BA and PCA_LBA) are designed in this paper.
Zhihua Cui +2 more
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A two-stage framework for bat algorithm
Neural Computing and Applications, 2016Bat algorithm (BA) is a new approach designed by imitating bat’s behavior of searching and capturing preys. The existing results have demonstrated the effectiveness and efficiency in comparison with other heuristic algorithms such as genetic algorithms and particle swarm optimization.
Boyang Zhang +5 more
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The Effect of Bat Population in Bat-BP Algorithm
2014A new metaheuristic based back-propagation algorithm known as Bat-BP is presented in this paper. The proposed Bat-BP algorithm successfully solves the problems like slow convergence to global minima and network stagnancy in back-propagation neural network (BPNN) algorithm. In this paper, the bat population is increased from 10 to 500 bats to detect the
Nazri Mohd. Nawi +2 more
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A Multi-objective Binary Bat Algorithm
Proceedings of the International Conference on Intelligent Information Processing, Security and Advanced Communication, 2015Bat Algorithm (BA) is a recently proposed heuristic algorithm based on the echolocation behavior of bats. BA has proven to have better performance than other well-known algorithms like particle swarm optimization (PSO) and genetic algorithm (GA). However, the research on using BA for binary and multi-objective optimization has just begun. In this paper
Mohamed Amine Laamari, Nadjet Kamel
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