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For: Weng X, Heidari AA, Liang G, Chen H, Ma X. An evolutionary Nelder–Mead slime mould algorithm with random learning for efficient design of photovoltaic models. Energy Reports 2021;7:8784-804. [DOI: 10.1016/j.egyr.2021.11.019] [Cited by in Crossref: 7] [Cited by in F6Publishing: 9] [Article Influence: 3.5] [Reference Citation Analysis]
Number Citing Articles
1 Lakshmanan M, Kumar C, Jasper JS. Optimal parameter characterization of an enhanced mathematical model of solar photovoltaic cell/module using an improved white shark optimization algorithm. Optim Control Appl Methods 2023. [DOI: 10.1002/oca.2984] [Reference Citation Analysis]
2 Gharehchopogh FS, Ucan A, Ibrikci T, Arasteh B, Isik G. Slime Mould Algorithm: A Comprehensive Survey of Its Variants and Applications. Arch Comput Methods Eng 2023;:1-41. [PMID: 36685136 DOI: 10.1007/s11831-023-09883-3] [Reference Citation Analysis]
3 Ekinci S, Izci D, Abualigah L. A novel balanced Aquila optimizer using random learning and Nelder–Mead simplex search mechanisms for air–fuel ratio system control. J Braz Soc Mech Sci Eng 2023;45:68. [DOI: 10.1007/s40430-022-04008-6] [Reference Citation Analysis]
4 Chen H, Li C, Mafarja M, Heidari AA, Chen Y, Cai Z. Slime mould algorithm: a comprehensive review of recent variants and applications. International Journal of Systems Science 2022. [DOI: 10.1080/00207721.2022.2153635] [Reference Citation Analysis]
5 Premkumar M, Jangir P, Ramakrishnan C, Kumar C, Sowmya R, Deb S, Kumar NM. An enhanced Gradient-based Optimizer for parameter estimation of various solar photovoltaic models. Energy Reports 2022;8:15249-15285. [DOI: 10.1016/j.egyr.2022.11.092] [Reference Citation Analysis]
6 Pop CB, Cioara T, Anghel I, Antal M, Chifu VR, Antal C, Salomie I. Review of bio-inspired optimization applications in renewable-powered smart grids: Emerging population-based metaheuristics. Energy Reports 2022;8:11769-98. [DOI: 10.1016/j.egyr.2022.09.025] [Reference Citation Analysis]
7 Lin C, Wang P, Zhao X, Chen H. Double Mutational Salp Swarm Algorithm: From Optimal Performance Design to Analysis. J Bionic Eng. [DOI: 10.1007/s42235-022-00262-5] [Reference Citation Analysis]
8 Izci D, Ekinci S, Eker E, Demirören A. Multi-strategy modified INFO algorithm: Performance analysis and application to functional electrical stimulation system. Journal of Computational Science 2022;64:101836. [DOI: 10.1016/j.jocs.2022.101836] [Reference Citation Analysis]
9 Xu B, Heidari AA, Zhang S, Chen H, Shao Q. Extremal Nelder–Mead colony predation algorithm for parameter estimation of solar photovoltaic models. Energy Science & Engineering. [DOI: 10.1002/ese3.1273] [Reference Citation Analysis]
10 Shi B, Chen J, Chen H, Lin W, Yang J, Chen Y, Wu C, Huang Z. Prediction of recurrent spontaneous abortion using evolutionary machine learning with joint self-adaptive sime mould algorithm. Computers in Biology and Medicine 2022. [DOI: 10.1016/j.compbiomed.2022.105885] [Reference Citation Analysis]
11 Zhong C, Li G, Meng Z. A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems. Neural Comput & Applic. [DOI: 10.1007/s00521-022-07277-3] [Reference Citation Analysis]
12 Shi B, Zhou T, Lv S, Wang M, Chen S, Heidari AA, Huang X, Chen H, Wang L, Wu P. An evolutionary machine learning for pulmonary hypertension animal model from arterial blood gas analysis. Comput Biol Med 2022;146:105529. [PMID: 35594682 DOI: 10.1016/j.compbiomed.2022.105529] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]