學(xué)者網(wǎng)
最早是在2014年，接觸到群體智能，那時候還只是小白，和老婆一起探索了下處于起步階段的算法 ，隨后在精讀灰狼優(yōu)化算法時，發(fā)現(xiàn)一些存在沖突的地方，于是提出了改進(jìn)，償試寫英文SCI期刊論文，但一直未果，2018年轉(zhuǎn)業(yè)后，不知道做什么，閱讀了中科院白皮書人工智能概要，發(fā)現(xiàn)群體智能也是一個大方向，于是轉(zhuǎn)入較為深入的研究，積累素材，先是發(fā)掘了168個基礎(chǔ)函數(shù)，然后據(jù)此深入做一些單目標(biāo)優(yōu)化，構(gòu)建了基準(zhǔn)，引導(dǎo)學(xué)生加入團(tuán)隊一起做。隨后逐步想轉(zhuǎn)入應(yīng)用和多目標(biāo)優(yōu)化，目前還在路上。
這幾天接受了一個會議keynote speaker邀請，準(zhǔn)備稿子，想把過去的工作總結(jié)一下，于是匯總工作發(fā)現(xiàn)，在群體智能上，已經(jīng)有40篇稿子了，其中SCI檢索差不多10篇，其余都是在會議上宣讀的小改進(jìn)。
價值不算太高，主要是還沒有找到應(yīng)用，從今年起，開始慢慢深入了。
2024年10月23日補(bǔ)充：
早滿第六年了，現(xiàn)在是第七個年頭，整理和更新一下群體智能相關(guān)的成果，僅列出SCI檢索，目前16篇，團(tuán)隊SCI數(shù)量剛突破2位數(shù)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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