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For: Zhang H, Cai Z, Ye X, Wang M, Kuang F, Chen H, Li C, Li Y. A multi-strategy enhanced salp swarm algorithm for global optimization. Engineering with Computers. [DOI: 10.1007/s00366-020-01099-4] [Cited by in Crossref: 32] [Cited by in F6Publishing: 26] [Article Influence: 10.7] [Reference Citation Analysis]
Number Citing Articles
1 Wei Y, Wan W, You X, Cheng F, Wang Y. Improved Salp Swarm Algorithm for Tool Wear Prediction. Electronics 2023;12:769. [DOI: 10.3390/electronics12030769] [Reference Citation Analysis]
2 Abdel-nabi H, Ali MZ, Awajan A, Alazrai R, Daoud MI, Suganthan PN. An Iterative cyclic Tri-Strategy Hybrid Stochastic fractal with Adaptive Differential Algorithm for Global Numerical Optimization. Information Sciences 2023. [DOI: 10.1016/j.ins.2023.01.065] [Reference Citation Analysis]
3 Lin C, Wang P, Heidari AA, Zhao X, Chen H. A Boosted Communicational Salp Swarm Algorithm: Performance Optimization and Comprehensive Analysis. J Bionic Eng 2022. [DOI: 10.1007/s42235-022-00304-y] [Reference Citation Analysis]
4 Panwar K, Deep K. Discrete Salp Swarm Algorithm for Euclidean Travelling Salesman Problem. Appl Intell. [DOI: 10.1007/s10489-022-03976-5] [Reference Citation Analysis]
5 Qin H, Meng T, Cao Y. Fuzzy Strategy Grey Wolf Optimizer for Complex Multimodal Optimization Problems. Sensors 2022;22:6420. [DOI: 10.3390/s22176420] [Reference Citation Analysis]
6 Wang C, Xu R, Ma L, Zhao J, Wang L, Xie N, Cheong KH. An efficient salp swarm algorithm based on scale-free informed followers with self-adaption weight. Appl Intell. [DOI: 10.1007/s10489-022-03438-y] [Reference Citation Analysis]
7 Skanderova L. Self-organizing migrating algorithm: review, improvements and comparison. Artif Intell Rev. [DOI: 10.1007/s10462-022-10167-8] [Reference Citation Analysis]
8 Abed-alguni BH, Paul D, Hammad R. Improved Salp swarm algorithm for solving single-objective continuous optimization problems. Appl Intell. [DOI: 10.1007/s10489-022-03269-x] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
9 Bao H, Liang G, Cai Z, Chen H. Random Replacement Crisscross Butterfly Optimization Algorithm for Standard Evaluation of Overseas Chinese Associations. Electronics 2022;11:1080. [DOI: 10.3390/electronics11071080] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
10 Hussien AG, Heidari AA, Ye X, Liang G, Chen H, Pan Z. Boosting whale optimization with evolution strategy and Gaussian random walks: an image segmentation method. Engineering with Computers. [DOI: 10.1007/s00366-021-01542-0] [Cited by in Crossref: 14] [Cited by in F6Publishing: 10] [Article Influence: 14.0] [Reference Citation Analysis]
11 Yu H, Qiao S, Heidari AA, Bi C, Chen H. Individual Disturbance and Attraction Repulsion Strategy Enhanced Seagull Optimization for Engineering Design. Mathematics 2022;10:276. [DOI: 10.3390/math10020276] [Cited by in Crossref: 5] [Cited by in F6Publishing: 9] [Article Influence: 5.0] [Reference Citation Analysis]
12 Chen D, Liu J, Yao C, Zhang Z, Du X. . MBE 2022;19:5269-92. [DOI: 10.3934/mbe.2022247] [Reference Citation Analysis]
13 Nadimi-shahraki MH, Taghian S, Mirjalili S, Ewees AA, Abualigah L, Abd Elaziz M. MTV-MFO: Multi-Trial Vector-Based Moth-Flame Optimization Algorithm. Symmetry 2021;13:2388. [DOI: 10.3390/sym13122388] [Cited by in Crossref: 11] [Cited by in F6Publishing: 12] [Article Influence: 5.5] [Reference Citation Analysis]
14 Kassaymeh S, Abdullah S, Al-laham M, Alweshah M, Al-betar MA, Othman Z. Salp Swarm Optimizer for Modeling Software Reliability Prediction Problems. Neural Process Lett 2021;53:4451-87. [DOI: 10.1007/s11063-021-10607-6] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
15 Zheng R, Jia H, Abualigah L, Liu Q, Wang S. Deep Ensemble of Slime Mold Algorithm and Arithmetic Optimization Algorithm for Global Optimization. Processes 2021;9:1774. [DOI: 10.3390/pr9101774] [Cited by in Crossref: 30] [Cited by in F6Publishing: 32] [Article Influence: 15.0] [Reference Citation Analysis]
16 Shi B, Ye H, Heidari AA, Zheng L, Hu Z, Chen H, Turabieh H, Mafarja M, Wu P. Analysis of COVID-19 severity from the perspective of coagulation index using evolutionary machine learning with enhanced brain storm optimization. Journal of King Saud University - Computer and Information Sciences 2021. [DOI: 10.1016/j.jksuci.2021.09.019] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
17 Ehteram M, Panahi F, Ahmed AN, Huang YF, Kumar P, Elshafie A. Predicting evaporation with optimized artificial neural network using multi-objective salp swarm algorithm. Environ Sci Pollut Res Int 2021. [PMID: 34528189 DOI: 10.1007/s11356-021-16301-3] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
18 Chen C, Wang X, Chen H, Wu C, Mafarja M, Turabieh H. Towards Precision Fertilization: Multi-Strategy Grey Wolf Optimizer Based Model Evaluation and Yield Estimation. Electronics 2021;10:2183. [DOI: 10.3390/electronics10182183] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
19 Weng X, Heidari AA, Liang G, Chen H, Ma X, Mafarja M, Turabieh H. Laplacian Nelder-Mead spherical evolution for parameter estimation of photovoltaic models. Energy Conversion and Management 2021;243:114223. [DOI: 10.1016/j.enconman.2021.114223] [Cited by in Crossref: 20] [Cited by in F6Publishing: 18] [Article Influence: 10.0] [Reference Citation Analysis]
20 Chen C, Wang X, Wu C, Mafarja M, Turabieh H, Chen H. Soil Erosion Prediction Based on Moth-Flame Optimizer-Evolved Kernel Extreme Learning Machine. Electronics 2021;10:2115. [DOI: 10.3390/electronics10172115] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
21 Xia J, Zhang H, Li R, Chen H, Turabieh H, Mafarja M, Pan Z. Generalized Oppositional Moth Flame Optimization with Crossover Strategy: An Approach for Medical Diagnosis. J Bionic Eng 2021;18:991-1010. [DOI: 10.1007/s42235-021-0068-1] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
22 Hadi MH, Issa AH, Sabri AA. Improvement of salp swarm algorithm (SSA2) for intelligent fault detection in smart wireless sensor networks. Materials Today: Proceedings 2021. [DOI: 10.1016/j.matpr.2021.07.248] [Reference Citation Analysis]
23 Ren H, Li J, Chen H, Li C. Stability of salp swarm algorithm with random replacement and double adaptive weighting. Applied Mathematical Modelling 2021;95:503-23. [DOI: 10.1016/j.apm.2021.02.002] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 3.5] [Reference Citation Analysis]
24 Tu J, Chen H, Wang M, Gandomi AH. The Colony Predation Algorithm. J Bionic Eng 2021;18:674-710. [DOI: 10.1007/s42235-021-0050-y] [Cited by in Crossref: 133] [Cited by in F6Publishing: 107] [Article Influence: 66.5] [Reference Citation Analysis]
25 Zhao S, Wang P, Heidari AA, Chen H, Turabieh H, Mafarja M, Li C. Multilevel threshold image segmentation with diffusion association slime mould algorithm and Renyi's entropy for chronic obstructive pulmonary disease. Comput Biol Med 2021;134:104427. [PMID: 34020128 DOI: 10.1016/j.compbiomed.2021.104427] [Cited by in Crossref: 37] [Cited by in F6Publishing: 42] [Article Influence: 18.5] [Reference Citation Analysis]
26 Ren H, Li J, Chen H, Li C. Adaptive levy-assisted salp swarm algorithm: Analysis and optimization case studies. Mathematics and Computers in Simulation 2021;181:380-409. [DOI: 10.1016/j.matcom.2020.09.027] [Cited by in Crossref: 16] [Cited by in F6Publishing: 11] [Article Influence: 8.0] [Reference Citation Analysis]
27 Nautiyal B, Prakash R, Vimal V, Liang G, Chen H. Improved Salp Swarm Algorithm with mutation schemes for solving global optimization and engineering problems. Engineering with Computers. [DOI: 10.1007/s00366-020-01252-z] [Cited by in Crossref: 17] [Cited by in F6Publishing: 11] [Article Influence: 8.5] [Reference Citation Analysis]
28 Zhang Y. Backtracking search algorithm with specular reflection learning for global optimization. Knowledge-Based Systems 2021;212:106546. [DOI: 10.1016/j.knosys.2020.106546] [Cited by in Crossref: 18] [Cited by in F6Publishing: 19] [Article Influence: 9.0] [Reference Citation Analysis]
29 Shi B, Ye H, Zheng J, Zhu Y, Heidari AA, Zheng L, Chen H, Wang L, Wu P. Early Recognition and Discrimination of COVID-19 Severity Using Slime Mould Support Vector Machine for Medical Decision-Making. IEEE Access 2021;9:121996-2015. [DOI: 10.1109/access.2021.3108447] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
30 Xu Z, Gui W, Heidari AA, Liang G, Chen H, Wu C, Turabieh H, Mafarja M. Spiral Motion Mode Embedded Grasshopper Optimization Algorithm: Design and Analysis. IEEE Access 2021;9:71104-32. [DOI: 10.1109/access.2021.3077616] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
31 Chen C, Wang X, Yu H, Zhao N, Wang M, Chen H, Kumarappan N. An Enhanced Comprehensive Learning Particle Swarm Optimizer with the Elite-Based Dominance Scheme. Complexity 2020;2020:1-24. [DOI: 10.1155/2020/4968063] [Cited by in Crossref: 11] [Cited by in F6Publishing: 13] [Article Influence: 3.7] [Reference Citation Analysis]