A Quantum Krill Herd Fusion Algorithm and Its Application

Authors

Zengxi Feng, 1.School of Building Services Science and Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;2.Anhui Key Laboratory of Intelligent Building and Building Energy Conservation, Anhui Jianzhu University, Hefei 230022, China;Follow
Jintong Zhao, 1.School of Building Services Science and Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;
Shiyan Li, 1.School of Building Services Science and Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;
Yalong Yang, 2.Anhui Key Laboratory of Intelligent Building and Building Energy Conservation, Anhui Jianzhu University, Hefei 230022, China;Follow
Haiyue Chen, 1.School of Building Services Science and Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;
Cong Zhang, 1.School of Building Services Science and Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;

Abstract

Abstract: Aiming at the defects of krill herd algorithm and quantum evolutionary algorithm, a quantum krill herd fusion algorithm (QKH) is proposed. The algorithm uses double-chain real numbers to encode the krill position, which can speed up the convergence speed, and avoids the randomness and complexity of quantum observations. The dynamically adjusted quantum krill herd rotation phase update strategy improves the convergence accuracy, and the efficiency of determining the quantum rotation phase. The introduction of an improved quantum full interference crossover strategy can prevent the fusion algorithm from falling into a local optimum, and can improve the optimization efficienal. The advantages of the quantum krill herd fusion optimization algorithm are verified by the classic test functions. A QKH-BPNN prediction model is established for air conditioning load forecasting, and the results show that the model has better accuracy and higher stability.

Recommended Citation

Feng, Zengxi; Zhao, Jintong; Li, Shiyan; Yang, Yalong; Chen, Haiyue; and Zhang, Cong (2022) "A Quantum Krill Herd Fusion Algorithm and Its Application," Journal of System Simulation: Vol. 34: Iss. 10, Article 4.
DOI: 10.16182/j.issn1004731x.joss.21-0534
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss10/4

First Page

2142

Revised Date

2021-09-11

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-0534

Last Page

2151

CLC

TP183

Recommended Citation

Zengxi Feng, Jintong Zhao, Shiyan Li, Yalong Yang, Haiyue Chen, Cong Zhang. A Quantum Krill Herd Fusion Algorithm and Its Application[J]. Journal of System Simulation, 2022, 34(10): 2142-2151.

Corresponding Author

Yalong Yang,yalong_yang2020@163.com

DOI

10.16182/j.issn1004731x.joss.21-0534