Analysis and Research of Several New Intelligent Optimization Algorithms
日期：2024-03-12 11:19:29 / 人气：
| [1] | 王凌. 智能优化算法及其应用[M]. 北京: 清华大学出版社, 2001. |
| WANG L. Intelligent optimization algorithm and its appli-cation[M]. Beijing: Tsinghua University Press, 2001. | |
| [2] | 李士勇, 里研, 林永茂. 智能优化算法与涌现计算[M]. 北京: 清华大学出版社, 2019. |
| LI S Y, LI Y, LIN Y M. Intelligent optimization algorithm and emergent computing[M]. Beijing: Tsinghua University Press, 2019. | |
| [3] |
RUMELHART D E, HINTON G E, WILLIAMS R J. Learn-ing representations by back propagating errors[J]. Nature, 1986, 323(6088):533-536.
DOI URL |
| [4] | HART E, ROSS P, NELSON J. Producing robust schedules via an artificial immune system[C]// Proceedings of the 1998 IEEE International Conference on Evolutionary Computa-tion, IEEE World Congress on Computational Intelligence, Anchorage, May 4-9, 1998. Piscataway: IEEE, 1998: 464-469. |
| [5] | GLOVER F. Tabu search—part I[J]. ORSA Journal on Com-puting, 1989, 1(3):190-206. |
| [6] | SHI Y H. Brain storm optimization algorithm[C]// LNCS 6728: Proceedings of the 2nd International Conference on Swarm Intelligence, Chongqing, Jun 12-15, 2011. Berlin, Heidelberg: Springer, 2011: 303-309. |
| [7] | ATASHPAZ-GARGARI E, LUCAS C. Imperialist competi-tive algorithm: an algorithm for optimization inspired by imperialistic competition[C]// Proceedings of the 2007 IEEE Congress on Evolutionary Computation, Singapore, Sep 25-28, 2007. Piscataway: IEEE, 2007: 4661-4667. |
| [8] | 王艳丽, 梁静, 薛冰, 等. 基于进化计算的特征选择方法研究概述[J]. 郑州大学学报(工学版), 2020, 41(1):49-57. |
| WANG Y L, LIANG J, XUE B, et al. Research on evolu-tionary computation for feature selection[J]. Journal of Zhengzhou University (Engineering Science), 2020, 41(1):49-57. | |
| [9] | GOLDBERG D E, HOLLAND J H. Genetic algorithms and machine learning[J]. Machine Learning, 1988, 3(2/3):95-99. |
| [10] |
STORN R, PRICE K. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of Global Optimization, 1997, 11(4):341-359.
DOI URL |
| [11] | FERREIRA C. Gene expression programming: a new adap-tive algorithm for solving problems[J]. Complex Systems, 2001, 13(2):87-129. |
| [12] | 程适, 王锐, 伍国华, 等. 群体智能优化算法[J]. 郑州大学学报(工学版), 2018, 39(6):1-2. |
| CHENG S, WANG R, WU G H, et al. Swarm intelligence optimization algorithm[J]. Journal of Zhengzhou University (Engineering Edition), 2018, 39(6):1-2. | |
| [13] | COLORNI A, DORIGO M, MANIEZZO V, et al. Distributed optimization by ant colonies[C]// Proceedings of the 1991 European Conference on Artificial Life, London, Sep 12-16, 1991. Amsterdam: Elsevier Science Publishers, 1991: 134-142. |
| [14] | KENNEDY J, EBERHART R. Particle swarm optimization[C]// Proceedings of the 1995 International Conference on Neural Networks, Perth, Nov 27-Dec 1, 1995. Piscataway: IEEE, 1995: 1942-1948. |
| [15] | KARABOGA D. An idea based on honey bee swarm for numerical optimization[R]. Erciyes University. Engineering Faculty. Computers Engineering Department, 2005. |
| [16] | YANG X S, DEB S. Cuckoo search via Lévy flights[C]// Proceedings of the 2009 World Congress on Nature & Bio-logically Inspired Computing, Coimbatore, Dec 9-11, 2009. Piscataway: IEEE, 2009: 210-214. |
| [17] | MEHRABIAN A R, LUCAS C. A novel numerical optimiz-ation algorithm inspired from weed colonization[J]. Ecolog-ical Informatics, 2006, 1(4):355-366. |
| [18] |
GHAEMI M, FEIZI-DERAKHSHI M R. Forest optimiza-tion algorithm[J]. Expert Systems with Applications, 2014, 41(15):6676-6687.
DOI URL |
| [19] | YANG X S. Flower pollination algorithm for global optimi-zation[C]// LNCS 7445: Proceedings of the 11th International Conference on Unconventional Computation and Natural Computation, Orléan, Sep 3-7, 2012. Berlin, Heidelberg: Springer, 2012: 240-249. |
| [20] |
KIRKPATRICK S, GELATT C D, VECCHI M P. Optimiza-tion by simulated annealing[J]. Science, 1983, 220(4598):671-680.
DOI URL |
| [21] |
SHAREEF H, IBRAHIM A A, MUTLAG A H. Lightning search algorithm[J]. Applied Soft Computing, 2015, 36:315-333.
DOI URL |
| [22] |
RASHEDI E, NEZAMABADI-POUR H, SARYAZDI S. GSA: a gravitational search algorithm[J]. Information Sciences, 2009, 179(13):2232-2248.
DOI URL |
| [23] |
PATEL V K, SAVSANI V J. Heat transfer search (HTS): a novel optimization algorithm[J]. Information Sciences, 2015, 324:217-246.
DOI URL |
| [24] | 雍龙泉, 黎延海, 贾伟. 正弦余弦算法的研究及应用综述[J]. 计算机工程与应用, 2020, 56(14):26-34. |
| YONG L Q, LI Y H, JIA W. Literature survey on research and application of sine cosine algorithm[J]. Computer Eng-ineering and Applications, 2020, 56(14):26-34. | |
| [25] | 林诗洁, 董晨, 陈明志, 等. 新型群智能优化算法综述[J]. 计算机工程与应用, 2018, 54(12):1-9. |
| LIN S J, DONG C, CHEN M Z, et al. Summary of new group intelligent optimization algorithms[J]. Computer Engineer-ing and Applications, 2018, 54(12):1-9. | |
| [26] |
ARORA S, SINGH S. Butterfly optimization algorithm: a novel approach for global optimization[J]. Soft Computing, 2019, 23(3):715-734.
DOI URL |
| [27] | ARORA S, SINGH S. Butterfly algorithm with Lèvy flights for global optimization[C]// Proceedings of the 2015 Interna-tional Conference on Signal Processing, Computing and Control, Waknaghat, Sep 24-26, 2015. Piscataway: IEEE, 2015: 220-224. |
| [28] |
REYNOLDS A M. Cooperative random Lévy flight searches and the flight patterns of honeybees[J]. Physics Letters A, 2006, 354(5/6):384-388.
DOI URL |
| [29] | 谢聪, 封宇. 一种改进的蝴蝶优化算法[J]. 数学的实践与认识, 2020, 50(13):105-115. |
| XIE C, FENG Y. An improved butterfly optimization algor-ithm[J]. Journal of Mathematics in Practice and Theory, 2020, 50(13):105-115. | |
| [30] | 高文欣, 刘升, 肖子雅, 等. 全局优化的蝴蝶优化算法[J]. 计算机应用研究, 2020, 37(10):2966-2970. |
| GAO W X, LIU S, XIAO Z Y, et al. Butterfly optimization algorithm for global optimization[J]. Application Research of Computers, 2020, 37(10):2966-2970. | |
| [31] | 高文欣, 刘升, 肖子雅, 等. 柯西变异和自适应权重优化的蝴蝶算法[J]. 计算机工程与应用, 2020, 56(15):43-50. |
| GAO W X, LIU S, XIAO Z Y, et al. Butterfly algorithm for Cauchy mutation and adaptive weight optimization[J]. Com-puter Engineering and Applications, 2020, 56(15):43-50. | |
| [32] | ARORA S, SINGH S, YETILMEZSOY K. A modified but-terfly optimization algorithm for mechanical design optimi-zation problems[J]. Journal of the Brazilian Society of Me-chanical Sciences and Engineering, 2018, 40(1):1-17. |
| [33] | 和树森, 刘天羽. 基于改进蝴蝶算法的冷热电联供微网日前优化调度研究[J]. 电气技术, 2021, 22(3):14-19. |
| HE S S, LIU T Y. Research on optimized scheduling of combined cooling heating and power microgrid based on improved butterfly algorithm[J]. Electrical Technology, 2021, 22(3):14-19. | |
| [34] |
ARORA S, SINGH S. An improved butterfly optimization algorithm for global optimization[J]. Advanced Science, Engineering and Medicine, 2017, 8(9):711-717.
DOI URL |
| [35] |
ARORA S, ANAND P. Learning automata-based butterfly optimization algorithm for engineering design problems[J]. International Journal of Computational Materials Science and Engineering, 2018, 7(4):1850021.
DOI URL |
| [36] | 宁杰琼, 何庆. 混合策略改进的蝴蝶优化算法[J]. 计算机应用研究, 2021, 38(6):1718-1723. |
| NING J Q, HE Q. Mixed strategy to improve butterfly opti-mization algorithm[J]. Application Research of Computers, 2021, 38(6):1718-1723. | |
| [37] |
RACHAPUDI V, DEVI G L, CHAITANYA N S. A nuclei segmentation method based on butterfly algorithm for H&E stained images[J]. International Journal of Engineering and Advanced Technology, 2019, 8(4):159.
DOI URL |
| [38] | 李鹏, 李立伟, 杨玉新. 基于IBOA-PF的锂电池健康状态预测[J]. 储能科学与技术, 2021, 10(2):705-713. |
| LI P, LI L W, YANG Y X. Estimation of lithium-ion battery state of health based on IBOA-PF[J]. Energy Storage Sci-ence and Technology, 2021, 10(2):705-713. | |
| [39] | MIRJALILI S. Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm[J]. Knowledge-Based Sys-tems, 2015, 89:228-249. |
| [40] | HELMI A, ALENANY A. An enhanced moth-flame optimi-zation algorithm for permutation-based problems[J]. Evolu-tionary Intelligence, 2020, 13(4):741-764. |
| [41] | 李志明, 莫愿斌. 基于Lévy飞行的飞蛾扑火优化算法[J]. 计算机工程与设计, 2017, 38(3):807-813. |
| LI Z M, MO Y B. Moth-flame optimization algorithm based on Lévy flights[J]. Computer Engineering and Design, 2017, 38(3):807-813. | |
| [42] | 王子琪, 陈金富, 张国芳, 等. 基于飞蛾扑火优化算法的电力系统最优潮流计算[J]. 电网技术, 2017, 41(11):3641-3647. |
| WANG Z Q, CHEN J F, ZHANG G F, et al. Optimal power flow calculation with moth-flame optimization algorithm[J]. Power System Technology, 2017, 41(11):3641-3647. | |
| [43] | 李伟琨, 阙波, 王万良, 等. 基于多目标飞蛾算法的电力系统无功优化研究[J]. 计算机科学, 2017, 44(S2):503-509. |
| LI W K, QUE B, WANG W L, et al. Multi-objective moth-flame optimization algorithm based optimal reactive power dispatch for power system[J]. Computer Science, 2017, 44(S2):503-509. | |
| [44] | 徐慧, 方策, 刘翔, 等. 改进的飞蛾扑火优化算法在网络入侵检测系统中的应用[J]. 计算机应用, 2018, 38(11):3231-3235. |
| XU H, FANG C, LIU X, et al. Network intrusion detection system based on improved moth-flame optimization algor-ithm[J]. Journal of Computer Applications, 2018, 38(11):3231-3235. | |
| [45] |
王娇, 李琦, 高军萍, 等. 基于改进飞蛾扑火优化算法的MIMO雷达相位编码信号集设计[J]. 信息与控制, 2019, 48(3):279-284.
DOI |
| WANG J, LI Q, GAO J P, et al. Phase-coded signal set design of MIMO radar based on modified moth-flame opti-mization algorithm[J]. Information and Control, 2019, 48(3):279-284. | |
| [46] | 李唐兵, 胡锦泓, 周求宽. 基于Lévy飞行的改进飞蛾扑火算法优化红外图像分割[J]. 红外技术, 2020, 42(9):846-854. |
| LI T B, HU J H, ZHOU Q K. Improved moth-flame optimi-zation algorithm based on Lévy flight to optimize infrared image segmentation[J]. Infrared Technology, 2020, 42(9):846-854. | |
| [47] | 王光, 金嘉毅. 融合折射原理反向学习的飞蛾扑火算法[J]. 计算机工程与应用, 2019, 55(11):46-51. |
| WANG G, JIN J Y. Moth-flame optimization algorithm fused on refraction principle and opposite-based learning[J]. Com-puter Engineering and Applications, 2019, 55(11):46-51. | |
| [48] | 刘小龙. 基于统计指导的飞蛾扑火算法求解大规模优化问题[J]. 控制与决策, 2020, 35(4):901-908. |
| LIU X L. Moth-flame algorithm based on statistical guid-ance for large-scale optimization problems[J]. Control and Decision, 2020, 35(4):901-908. | |
| [49] |
PELUSI D, MASCELLA R, TALLINI L G, et al. An im-proved moth-flame optimization algorithm with hybrid search phase[J]. Knowledge-Based Systems, 2020, 191:105277.
DOI URL |
| [50] |
SINGH P, PRAKASH S. Optical network unit placement in Fiber-Wireless (FiWi) access network by whale optimization algorithm[J]. Optical Fiber Technology, 2019, 52:101965.
DOI URL |
| [51] | 张学典, 孙俊峰, 秦晓飞. 基于飞蛾火焰优化算法的PMSM分数阶PIλ研究[J]. 计算机应用研究, 2019, 36(5):1323-1327. |
| ZHANG X D, SUN J F, QIN X F. Research of fractional order PIλ for PMSM based on moths fire optimization algo-rithm[J]. Application Research of Computers, 2019, 36(5):1323-1327. | |
| [52] |
MIRJALILI S. SCA: a sine cosine algorithm for solving optimization problems[J]. Knowledge-Based Systems, 2016, 96:120-133.
DOI URL |
| [53] | 刘勇, 马良. 转换参数非线性递减的正弦余弦算法[J]. 计算机工程与应用, 2017, 53(2):1-5. |
| LIU Y, MA L. Sine cosine algorithm with nonlinear decrea-sing conversion parameter[J]. Computer Engineering and Applications, 2017, 53(2):1-5. | |
| [54] | 徐松金, 龙文. 求解高维优化问题的改进正弦余弦算法[J]. 计算机应用研究, 2018, 35(9):2574-2577. |
| XU S J, LONG W. Improved sine cosine algorithm for solv-ing high-dimensional optimization problems[J]. Application Research of Computers, 2018, 35(9):2574-2577. | |
| [55] |
KUMAR L, BHARTI K K. A novel hybrid BPSO-SCA approach for feature selection[J]. Natural Computing, 2021, 20(1):39-61.
DOI URL |
| [56] | 郭文艳, 王远, 戴芳, 等. 基于精英混沌搜索策略的交替正余弦算法[J]. 控制与决策, 2019, 34(8):1654-1662. |
| GUO W Y, WANG Y, DAI F, et al. Alternating sine cosine algorithm based on elite chaotic search strategy[J]. Control and Decision, 2019, 34(8):1654-1662. | |
| [57] | 徐明, 焦建军, 龙文. 基于Logistic模型和随机差分变异的正弦余弦算法[J]. 计算机科学, 2020, 47(2):206-212. |
| XU M, JIAO J J, LONG W. Sine cosine algorithm based on logistic model and random difference variation[J]. Computer Science, 2020, 47(2):206-212. | |
| [58] |
GUPTA S, DEEP K. Improved sine cosine algorithm with crossover scheme for global optimization[J]. Knowledge-Based Systems, 2019, 165:374-406.
DOI URL |
| [59] | 何庆, 徐钦帅, 魏康园. 基于改进正弦余弦算法的无线传感器节点部署优化[J]. 计算机应用, 2019, 39(7):2035-2043. |
| HE Q, XU Q S, WEI K Y. Enhanced sine cosine algorithm based node deployment optimization of wireless sensor net-work[J]. Journal of Computer Applications, 2019, 39(7):2035-2043. | |
| [60] | NAYAK D R, DASH R, MAJHI B, et al. Combining extreme learning machine with modified sine cosine algorithm for detection of pathological brain[J]. Computers & Electrical Engineering, 2018, 68:366-380. |
| [61] | 于坤, 焦青亮, 刘子龙, 等. 基于改进正弦余弦算法的光谱特征峰定位方法[J]. 光学学报, 2019, 39(9):403-409. |
| YU K, JIAO Q L, LIU Z L, et al. Positioning of characteri-stic spectral peaks based on improved sine cosine algorithm[J]. Acta Optica Sinica, 2019, 39(9):403-409. | |
| [62] |
ABUALIGAH L M, DULAIMI A J. A novel feature selec-tion method for data mining tasks using hybrid sine cosine algorithm and genetic algorithm[J]. Cluster Computing, 2021, 24(3):2161-2176.
DOI URL |
| [63] |
SAREMI S, MIRJALILI S, LEWIS A. Grasshopper optimi-sation algorithm: theory and application[J]. Advances in Engineering Software, 2017, 105:30-47.
DOI URL |
| [64] |
MIRJALILI S Z, MIRJALILI S, SAREMI S, et al. Gras-shopper optimization algorithm for multi-objective optimi-zation problems[J]. Applied Intelligence, 2018, 48(4):805-820.
DOI URL |
| [65] | 李洋州, 顾磊. 基于曲线自适应和模拟退火的蝗虫优化算法[J]. 计算机应用研究, 2019, 36(12):3637-3643. |
| LI Y Z, GU L. Grasshopper optimization algorithm based on curve adaptation and simulated annealing[J]. Application Research of Computers, 2019, 36(12):3637-3643. | |
| [66] | 赵然, 郭志川, 朱小勇. 一种基于Lévy飞行的改进蝗虫优化算法[J]. 计算机与现代化, 2020(1):104-110. |
| ZHAO R, GUO Z C, ZHU X Y. An improved grasshopper optimization algorithm based on Lévy flight[J]. Computer and Modernization, 2020(1):104-110. | |
| [67] | 杨文珍, 何庆, 杜逆索. 具有扰动机制和强化莱维飞行的蝗虫优化算法[J/OL]. 小型微型计算机系统 [2021-04-16]. http://kns.cnki.net/kcms/detail/21.1106.TP.20210322.0922.002.html. |
| YANG W Z, HE Q, DU N S. Grasshopper optimization algorithm with disturbance mechanism and enhanced Levy flight[J/OL]. Journal of Chinese Computer Systems [2021-04-16]. http://kns.cnki.net/kcms/detail/21.1106.TP.20210322.0922.002.html. | |
| [68] | 闫旭, 叶春明. 混合蝗虫优化算法求解作业车间调度问题[J]. 计算机工程与应用, 2019, 55(6):257-264. |
| YAN X, YE C M. Hybrid grasshopper optimization algorithm for job shop scheduling problem[J]. Computer Engineering and Applications, 2019, 55(6):257-264. | |
| [69] | 程泽新, 李东生, 高杨. 基于蝗虫算法的无人机三维航迹规划[J]. 飞行力学, 2019, 37(2):46-50. |
| CHENG Z X, LI D S, GAO Y. UAV 3D path planning based on grasshopper optimization algorithm[J]. Flight Dynamics, 2019, 37(2):46-50. | |
| [70] | PINTO H. PEÑA A, VALENZUELA M, et al. A binary grasshopper algorithm applied to the knapsack problem[C]// Proceedings of the 7th Computer Science On-line Confer-ence on Artificial Intelligence and Algorithms in Intelligent Systems, Vsetin, Apr 25-28, 2018. Cham: Springer, 2018: 132-143. |
| [71] | 王博, 刘连生, 韩绍程, 等. 基于多策略融合的混合多目标蝗虫优化算法[J]. 计算机应用, 2020, 40(9):2670-2676. |
| WANG B, LIU L S, HAN S C, et al. Hybrid multi-objective grasshopper optimization algorithm based on fusion of mul-tiple strategies[J]. Journal of Computer Applications, 2020, 40(9):2670-2676. | |
| [72] |
EWEES A A, ABD ELAZIZ M E, HOUSSEIN E H. Im-proved grasshopper optimization algorithm using opposition-based learning[J]. Expert Systems with Applications, 2018, 112:156-172.
DOI URL |
| [73] |
ARORA S, ANAND P. Chaotic grasshopper optimization algorithm for global optimization[J]. Neural Computing and Applications, 2019, 31(8):4385-4405.
DOI URL |
| [74] | ŁUKASIK S, KOWALSKI P A, CHARYTANOWICZ M, et al. Data clustering with grasshopper optimization algori-thm[C]// Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, Prague, Sep 3-6, 2017. Piscataway: IEEE, 2017: 71-74. |
| [75] | 潘峰, 孙红霞. 基于蝗虫算法的图像多阈值分割方法[J]. 电子测量与仪器学报, 2019, 33(1):149-155. |
| PAN F, SUN H X. Algorithm for image segmentation based on grasshopper optimization algorithm[J]. Journal of Elec-tronic Measurement and Instrumentation, 2019, 33(1):149-155. | |
| [76] | HEIDARI A A, MIRJALILI S, FARIS H, et al. Harris hawks optimization: algorithm and applications[J]. Future Genera-tion Computer Systems, 2019, 97:849-872. |
| [77] |
HUSSAIN K, ZHU W, SALLEH M M. Long-term memory Harris’ hawk optimization for high dimensional and optimal power flow problems[J]. IEEE Access, 2019, 7:147596-147616.
DOI URL |
| [78] | QU C, HE W, PENG X, et al. Harris hawks optimization with information exchange[J]. Applied Mathematical Mod-elling, 2020, 84:52-75. |
| [79] |
ELGAMAL Z M, YASIN N B M, TUBISHAT M, et al. An improved Harris hawks optimization algorithm with simul-ated annealing for feature selection in the medical field[J]. IEEE Access, 2020, 8:186638-186652.
DOI URL |
| [80] | 郭雨鑫, 刘升, 高文欣, 等. 精英反向学习与黄金正弦优化的HHO算法[J/OL]. 计算机工程与应用 [2021-08-12]. http://kns.cnki.net/kcms/detail/11.2127.TP.20210714.1521.015.html. |
| GUO Y X, LIU S, GAO W X et al. HHO algorithm for elite reverse learning and golden sinusoidal optimization[J/OL]. Computer Engineering and Applications [2021-08-12]. http://kns.cnki.net/kcms/detail/11.2127.TP.20210714.1521.015.html. | |
| [81] | 马一鸣, 石志东, 赵康, 等. 基于改进哈里斯鹰优化算法的TDOA定位[J]. 计算机工程, 2020, 46(12):179-184. |
| MA Y M, SHI Z D, ZHAO K, et al. TDOA localization based on improved Harris hawk optimization algorithm[J]. Computer Engineering, 2020, 46(12):179-184. | |
| [82] | 汤安迪, 韩统, 徐登武, 等. 混沌精英哈里斯鹰优化算法[J]. 计算机应用, 2021, 41(8):2265-2272. |
| TANG A D, HAN T, XU D W, et al. Chaotic elite Harris hawks optimization algorithm[J]. Journal of Computer App-lications, 2021, 41(8):2265-2272. | |
| [83] |
ZHANG Y, ZHOU X, SHIH P C. Modified Harris hawks optimization algorithm for global optimization problems[J]. Arabian Journal for Science and Engineering, 2020, 45(12):10949-10974.
DOI URL |
| [84] |
JIA H M, PENG X X, KANG L F, et al. Pulse coupled neural network based on Harris hawks optimization algorithm for image segmentation[J]. Multimedia Tools and Applications, 2020, 79(37):28369-28392.
DOI URL |
| [85] |
JIA H M, LANG C B, OLIVA D, et al. Dynamic Harris hawks optimization with mutation mechanism for satellite image segmentation[J]. Remote Sensing, 2019, 11(12):1421.
DOI URL |
| [86] | FAN C C, ZHOU Y Q, TANG Z H. Neighborhood centroid opposite-based learning Harris hawks optimization for train-ing neural networks[J]. Evolutionary Intelligence, 2020: 1-21. |
| [87] | XUE J K, SHEN B. A novel swarm intelligence optimiza-tion approach: sparrow search algorithm[J]. Systems Science & Control Engineering, 2020, 8(1):22-34. |
| [88] | 毛清华, 张强. 融合柯西变异和反向学习的改进麻雀算法[J]. 计算机科学与探索, 2021, 15(6):1155-1164. |
| MAO Q H, ZHANG Q. Improved sparrow algorithm com-bining cauchy mutation and opposition-based learning[J]. Journal of Frontiers of Computer Science and Technology, 2021, 15(6):1155-1164. | |
| [89] |
ZHU Y, YOUSEFI N. Optimal parameter identification of PEMFC stacks using adaptive sparrow search algorithm[J]. International Journal of Hydrogen Energy, 2021, 46(14):9541-9552.
DOI URL |
| [90] |
ZHANG C L, DING S F. A stochastic configuration network based on chaotic sparrow search algorithm[J]. Knowledge-Based Systems, 2021, 220:106924.
DOI URL |
| [91] | 吕鑫, 慕晓冬, 张钧. 基于改进麻雀搜索算法的多阈值图像分割[J]. 系统工程与电子技术, 2021, 43(2):318-327. |
| LYU X, MU X D, ZHANG J. Multi-threshold image seg-mentation based on improved sparrow search algorithm[J]. Systems Engineering and Electronics, 2021, 43(2):318-327. | |
| [92] | 汤安迪, 韩统, 徐登武, 等. 基于混沌麻雀搜索算法的无人机航迹规划方法[J]. 计算机应用, 2021, 41(7):2128-2136. |
| TANG A D, HAN T, XU D W, et al. Path planning method of unmanned aerial vehicle based on chaos sparrow search algorithm[J]. Journal of Computer Applications, 2021, 41(7):2128-2136. | |
| [93] | 温泽宇, 谢珺, 谢刚, 等. 基于新型拥挤度距离的多目标麻雀搜索算法[J]. 计算机工程与应用, 2021, 57(22):102-109. |
| WEN Z Y, XIE J, XIE G, et al. Multi-objective sparrow search algorithm based on new congestion distance[J]. Computer Engineering and Applications, 2021, 57(22):102-109. | |
| [94] | 史春天, 曾艳阳, 侯守明. 群体智能算法在图像分割中的应用综述[J]. 计算机工程与应用, 2021, 57(8):36-47. |
| SHI C T, ZENG Y Y, HOU S M. Summary of application of swarm intelligence algorithms in image segmentation[J]. Computer Engineering and Applications, 2021, 57(8):36-47. | |
| [95] |
XIN Y, YONG L, LIN G M. Evolutionary programming made faster[J]. IEEE Transactions on Evolutionary Computation, 1999, 3(2):82-102.
DOI URL |
| [96] |
DIGALAKIS J G, MARGARITIS K G. On benchmarking functions for genetic algorithms[J]. International Journal of Computer Mathematics, 2001, 77(4):481-506.
DOI URL |
| [97] |
YANG X S. Firefly algorithm, stochastic test functions and design optimisation[J]. International Journal of Bio-Inspired Computation, 2010, 2(2):78-84.
DOI URL |
