拼在荆楚理工学院六周年学术小结之群体智能

来源: 高正明/

荆楚理工学院

1594

2023-03-08 14:27:41

2024-10-23

最早是在2014年，接触到群体智能，那时候还只是小白，和老婆一起探索了下处于起步阶段的算法，随后在精读灰狼优化算法时，发现一些存在冲突的地方，于是提出了改进，偿试写英文SCI期刊论文，但一直未果，2018年转业后，不知道做什么，阅读了中科院白皮书人工智能概要，发现群体智能也是一个大方向，于是转入较为深入的研究，积累素材，先是发掘了168个基础函数，然后据此深入做一些单目标优化，构建了基准，引导学生加入团队一起做。随后逐步想转入应用和多目标优化，目前还在路上。

这几天接受了一个会议keynote speaker邀请，准备稿子，想把过去的工作总结一下，于是汇总工作发现，在群体智能上，已经有40篇稿子了，其中SCI检索差不多10篇，其余都是在会议上宣读的小改进。

价值不算太高，主要是还没有找到应用，从今年起，开始慢慢深入了。

2024年10月23日补充：

早满第六年了，现在是第七个年头，整理和更新一下群体智能相关的成果，仅列出SCI检索，目前16篇，团队SCI数量刚突破2位数不久。

2024

[1] Zhang, Yujun, Wang, Yufei, Yan, Yuxin, Zhao, Juan, Gao, Zhengming*. Historical Knowledge Transfer Driven Self-Adaptive Evolutionary Multitasking Algorithm with Hybrid Resource Release for Solving Nonlinear Equation Systems. Swarm and Evolutionary Computation, Elsevier BV, 2024

[2] Zhang, Yu-Jun, Wang, Yu-Fei, Yan, Yu-Xin, Zhao, Juan, Gao, Zheng-Ming*. Self-adaptive hybrid mutation slime mould algorithm: Case studies on UAV path planning, engineering problems, photovoltaic models and infinite impulse response. Alexandria Engineering Journal, Elsevier BV, 2024, 98

[3] Zhang, Yujun, Li, Shuijia, Wang, Yufei, Yan, Yuxin, Zhao, Juan, Gao, Zhengming*. Self-adaptive enhanced learning differential evolution with surprisingly efficient decomposition approach for parameter identification of photovoltaic models. Energy Conversion and Management, Elsevier BV, 2024, 308

2023

[4] Wang, Yufei, Zhang, Yujun, Yan, Yuxin, Zhao, Juan, Gao, Zhengming*. An enhanced aquila optimization algorithm with velocity-aided global search mechanism and adaptive opposition-based learning. Mathematical Biosciences and Engineering, American Institute of Mathematical Sciences (AIMS), 2023, 20(4): 6422–6467

2022

[5] Zhang, Yu-Jun, Wang, Yu-Fei, Tao, Liu-Wei, Yan, Yu-Xin, Zhao, Juan*, Gao, Zheng-Ming. Self-adaptive classification learning hybrid JAYA and Rao-1 algorithm for large-scale numerical and engineering problems. Engineering Applications of Artificial Intelligence, Elsevier BV, 2022, 114

[6] Zhang, Yu-Jun, Wang, Yu-Fei, Yan, Yu-Xin, Zhao, Juan*, Gao, Zheng-Ming. LMRAOA: An improved arithmetic optimization algorithm with multi-leader and high-speed jumping based on opposition-based learning solving engineering and numerical problems. Alexandria Engineering Journal, Elsevier BV, 2022, 61(12)

[7] Zhang, Yu-Jun, Yan, Yu-Xin, Zhao, Juan, Gao, Zheng-Ming*. AOAAO: The Hybrid Algorithm of Arithmetic Optimization Algorithm With Aquila Optimizer. IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2022, 10: 10907–10933

[8] Zhao, Juan, Gao, Zheng-Ming*, Chen, Hua-Feng. The Simplified Aquila Optimization Algorithm. IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2022, 10: 22487–22515

[9] Zhang, Jiahao, Gao, Zhengming*, Li, Suruo, Zhao, Juan, Song, Wenguang. Improved intelligent clonal optimizer based on adaptive parameter strategy. Mathematical Biosciences and Engineering, American Institute of Mathematical Sciences (AIMS), 2022, 19(10): 10275–10315

[10] Zhang, Yujun, Wang, Yufei, Li, Shuijia, Yao, Fengjuan, Tao, Liuwei, Yan, Yuxin, Zhao, Juan*, Gao, Zhengming. An enhanced adaptive comprehensive learning hybrid algorithm of Rao-1 and JAYA algorithm for parameter extraction of photovoltaic models. Mathematical Biosciences and Engineering, American Institute of Mathematical Sciences (AIMS), 2022, 19(6): 5610–5637

[11] ZHAO, Juan, GAO, Zheng-Ming*. The heterogeneous Aquila optimization algorithm. Mathematical Biosciences and Engineering, American Institute of Mathematical Sciences (AIMS), 2022, 19(6): 5867–5904

[12] Zhao, Juan, Zhang, Yujun, Li, Shuijia, Wang, Yufei, Yan, Yuxin, Gao, Zhengming. A chaotic self-adaptive JAYA algorithm for parameter extraction of photovoltaic models. Mathematical Biosciences and Engineering, American Institute of Mathematical Sciences (AIMS), 2022, 19(6): 5638–5670

[13] Zhang, Yu-Jun, Yan, Yu-Xin, Zhao, Juan*, Gao, Zheng-Ming. CSCAHHO: Chaotic hybridization algorithm of the Sine Cosine with Harris Hawk optimization algorithms for solving global optimization problems. PLOS ONE, Public Library of Science (PLoS), 2022, 17(5)

[14] GAO, Zheng-Ming*, ZHAO, Juan, Zhang, Yu-Jun. Review of chaotic mapping enabled nature-inspired algorithms. Mathematical Biosciences and Engineering, 2022, 19(8): 8215-8258

2021

[15] Gao, Zheng-Ming*, Zhao, Juan, Hu, Yu-Rong, Chen, Hua-Feng. The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions. IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2021, 9: 106317–106339

2019

[16] Gao, Zheng-Ming*, Zhao, Juan. An Improved Grey Wolf Optimization Algorithm with Variable Weights. Computational Intelligence and Neuroscience, Hindawi Limited, 2019, 2019

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