A Binary Superior Tracking Artificial Bee Colony with Dynamic Cauchy Mutation for Feature Selection

Chu, Xianghua; Li, Shuxiang; Gao, Da; Zhao, Wei; Cui, Jianshuang; Huang, Linya

doi:10.1155/2020/8864315

Cited by 6 publications

(5 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e Cauchy inverse function [26] is shown in (22). Referring to (22), we can write the new position of the individual as (23); that is, the new position of the individual is obtained by the Cauchy mutation.…”

Section: 25mentioning

confidence: 99%

“…(1) if rand < P m , the elastic collision variation was carried out on some new positions, according to (26), to obtain new x ECSOA,G , and the range of x ECSOA,G is judged and modified to meet (x min , x max ).…”

Section: ) E Elastic Collision Variationmentioning

confidence: 99%

“…An elite symbiotic organisms search algorithm with mutually beneficial factor is adopted to optimize the functions [25]. An artificial bee colony with dynamic Cauchy mutation is adopted to solve feature selection [26]. A new elastic collision optimization algorithm is applied in sensor cloud resource scheduling [27].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Elastic Collision Seeker Optimization Algorithm for Optimization Constrained Engineering Problems

Duan

Luo

Liu

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

To improve the seeker optimization algorithm (SOA), an elastic collision seeker optimization algorithm (ECSOA) was proposed. The ECSOA evolves some individuals in three situations: completely elastic collision, completely inelastic collision, and non-completely elastic collision. These strategies enhance the individuals’ diversity and avert falling into the local optimum. The ECSOA is compared with the particle swarm optimization (PSO), the simulated annealing and genetic algorithm (SA_GA), the gravitational search algorithm (GSA), the sine cosine algorithm (SCA), the multiverse optimizer (MVO), and the seeker optimization algorithm (SOA); then, fifteen benchmark functions, four PID control parameter models, and six constrained engineering optimization problems were selected for the experiment. According to the experimental results, the ECSOA can be used in the benchmark functions, the PID control parameter optimization, and the optimization constrained engineering problems. The optimization ability and robustness of ECSOA are better.

show abstract

Section: 25mentioning

confidence: 99%

Section: ) E Elastic Collision Variationmentioning

confidence: 99%

See 1 more Smart Citation

An Elastic Collision Seeker Optimization Algorithm for Optimization Constrained Engineering Problems

Duan

Luo

Liu

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…Ding et al [ 89 ] presented a modified ABC algorithm to improve structural damage identification. Chu et al [ 90 ] proposed a binary superior tracking ABC with dynamic Cauchy mutation to improve the feature selection algorithm. Chen et al [ 91 ] proposed a fireworks explosion-based ABC framework to solve the problem of slow convergence of the ABC algorithm.…”

Section: Introductionmentioning

confidence: 99%

Horizontal and vertical search artificial bee colony for image segmentation of COVID-19 X-ray images

Zhao

et al. 2022

Computers in Biology and Medicine

View full text Add to dashboard Cite

“…An elite symbiotic organisms search algorithm with mutually beneficial factors was adopted to optimize the functions [15]. An artificial bee colony (ABC) with dynamic Cauchy mutation is adopted to solve feature selection [16]. Polynomial variation combined genetic adaptive search is applied to optimize constrained engineering design problems [17].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Strategy Seeker Optimization Algorithm for Optimization Constrained Engineering Problems

2022

View full text Add to dashboard Cite

This paper proposes a multi-strategy seeker optimization algorithm (MSSOA) for optimization constrained engineering problems. In this paper, three strategies were adopted to improve the poor searching capability of the seeker optimization algorithm (SOA). The first strategy was triple black hole system capture to solve the local optima issue. The second and third strategies were the multi-dimensional random interference and the precocious interference to balance the exploration and exploitation processes. These three strategies are proposed to improve respectively the SOA algorithm, and compared with the three strategies to improve together the SOA algorithm for optimizing 15 benchmark functions; the way these three strategies work together is called multi-strategy; and the efficiency of the multi-strategy is illustrated the numerical optimizing results and the convergence curves, population's positions with iterations and the search history of the benchmark functions. The proposed multi-strategy method achieved better performance in optimizing of the benchmark functions compared to other six optimization methods. The numerical and experimental results analysis were observed with respect to the optimal solution curve, the convergence curve of the fitness function, the ANOVA tests, the calculation complexity of the algorithm, the running time of the algorithm routine, the exploration and exploitation capability, the Wilcoxon's rank-sum test, the performance profile of algorithm. The results showed that the proposed multi-strategy method was efficient in the benchmark functions. The proposed multi-strategy method also achieved better performance in optimizing of the engineering problems and provided better solutions compared to other six optimization methods.INDEX TERMS Seeker optimization algorithm, triple black hole system capture, multi-dimensional random interference, precocious interference, constrained engineering optimization problems.

show abstract

A Binary Superior Tracking Artificial Bee Colony with Dynamic Cauchy Mutation for Feature Selection

Cited by 6 publications

References 37 publications

An Elastic Collision Seeker Optimization Algorithm for Optimization Constrained Engineering Problems

An Elastic Collision Seeker Optimization Algorithm for Optimization Constrained Engineering Problems

Horizontal and vertical search artificial bee colony for image segmentation of COVID-19 X-ray images

A Multi-Strategy Seeker Optimization Algorithm for Optimization Constrained Engineering Problems

Contact Info

Product

Resources

About