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2 results on '"Y conditional cloud generator"'

1. A Developed Artificial Bee Colony Algorithm Based on Cloud Model

Author

Ye Jin, Yuehong Sun, and Hongjiao Ma

Subjects
artificial bee colony algorithm (ABC), cloud model, normal cloud model, Y conditional cloud generator, global optimum, Mathematics, QA1-939
Abstract

The Artificial Bee Colony (ABC) algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory and the fuzzy mathematics. A developed ABC algorithm based on cloud model is proposed to enhance accuracy of the basic ABC algorithm and avoid getting trapped into local optima by introducing a new select mechanism, replacing the onlooker bees’ search formula and changing the scout bees’ updating formula. Experiments on CEC15 show that the new algorithm has a faster convergence speed and higher accuracy than the basic ABC and some cloud model based ABC variants.

Published
2018
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2. A Developed Artificial Bee Colony Algorithm Based on Cloud Model

Author

Yuehong Sun, Hongjiao Ma, and Ye Jin

Subjects
0209 industrial biotechnology, Computer science, General Mathematics, Computer Science::Neural and Evolutionary Computation, Cloud computing, 02 engineering and technology, 020901 industrial engineering & automation, Local optimum, Probability theory, Convergence (routing), 0202 electrical engineering, electronic engineering, information engineering, Computer Science (miscellaneous), Quantitative expression, Y conditional cloud generator, Engineering (miscellaneous), artificial bee colony algorithm (ABC), cloud model, normal cloud model, global optimum, business.industry, lcsh:Mathematics, lcsh:QA1-939, Statistics::Computation, Artificial bee colony algorithm, Global optimum, Fuzzy mathematics, 020201 artificial intelligence & image processing, Artificial intelligence, business
Abstract

The Artificial Bee Colony (ABC) algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory and the fuzzy mathematics. A developed ABC algorithm based on cloud model is proposed to enhance accuracy of the basic ABC algorithm and avoid getting trapped into local optima by introducing a new select mechanism, replacing the onlooker bees’ search formula and changing the scout bees’ updating formula. Experiments on CEC15 show that the new algorithm has a faster convergence speed and higher accuracy than the basic ABC and some cloud model based ABC variants.

Published
2018

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