| 1 |
Xu B, Heidari AA, Cai Z, Chen H. Dimensional decision covariance colony predation algorithm: global optimization and high−dimensional feature selection. Artif Intell Rev 2023. [DOI: 10.1007/s10462-023-10412-8] [Reference Citation Analysis]
|
| 2 |
Beşkirli A, Dağ İ. Parameter extraction for photovoltaic models with tree seed algorithm. Energy Reports 2023;9:174-185. [DOI: 10.1016/j.egyr.2022.10.386] [Reference Citation Analysis]
|
| 3 |
Deng L, Liu S. An enhanced slime mould algorithm based on adaptive grouping technique for global optimization. Expert Systems with Applications 2023. [DOI: 10.1016/j.eswa.2023.119877] [Reference Citation Analysis]
|
| 4 |
Son PVH, Khoi LNQ. Adaptive opposition slime mold algorithm for time–cost–quality–safety trade-off for construction projects. Asian J Civ Eng 2023. [DOI: 10.1007/s42107-023-00612-6] [Reference Citation Analysis]
|
| 5 |
Pham Vu Hong Son, Luu Ngoc Quynh Khoi. Building projects with time–cost–quality–environment trade-off optimization using adaptive selection slime mold algorithm. Asian J Civ Eng 2023. [ DOI: 10.1007/s42107-023-00572-x] [Reference Citation Analysis]
|
| 6 |
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]
|
| 7 |
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]
|
| 8 |
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]
|
| 9 |
Yin S, Luo Q, Zhou Y. IBMSMA: An Indicator-based Multi-swarm Slime Mould Algorithm for Multi-objective Truss Optimization Problems. J Bionic Eng 2022. [DOI: 10.1007/s42235-022-00307-9] [Reference Citation Analysis]
|
| 10 |
Wei Y, Othman Z, Daud KM, Yin S, Luo Q, Zhou Y. Equilibrium Optimizer and Slime Mould Algorithm with Variable Neighborhood Search for Job Shop Scheduling Problem. Mathematics 2022;10:4063. [DOI: 10.3390/math10214063] [Reference Citation Analysis]
|
| 11 |
Younis A, Bakhit A, Onsa M, Hashim M. A comprehensive and critical review of bio-inspired metaheuristic frameworks for extracting parameters of solar cell single and double diode models. Energy Reports 2022;8:7085-106. [DOI: 10.1016/j.egyr.2022.05.160] [Reference Citation Analysis]
|
| 12 |
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]
|
| 13 |
Al-Qaness MAA, Helmi AM, Dahou A, Elaziz MA. The Applications of Metaheuristics for Human Activity Recognition and Fall Detection Using Wearable Sensors: A Comprehensive Analysis. Biosensors (Basel) 2022;12:821. [PMID: 36290958 DOI: 10.3390/bios12100821] [Reference Citation Analysis]
|
| 14 |
Ćalasan M, Al-dhaifallah M, Ali ZM, Abdel Aleem SHE. Comparative Analysis of Different Iterative Methods for Solving Current–Voltage Characteristics of Double and Triple Diode Models of Solar Cells. Mathematics 2022;10:3082. [DOI: 10.3390/math10173082] [Reference Citation Analysis]
|
| 15 |
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]
|
| 16 |
Ahmadianfar I, Noori RM, Togun H, Falah MW, Homod RZ, Fu M, Halder B, Deo R, Yaseen ZM. Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization. Knowledge-Based Systems 2022;250:109048. [DOI: 10.1016/j.knosys.2022.109048] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
|
| 17 |
Miao H, Qiu Z, Zeng C. Multi-Strategy Improved Slime Mould Algorithm and its Application in Optimal Operation of Cascade Reservoirs. Water Resour Manage 2022;36:3029-48. [DOI: 10.1007/s11269-022-03183-4] [Reference Citation Analysis]
|
| 18 |
Yin S, Luo Q, Zhou G, Zhou Y, Zhu B. An equilibrium optimizer slime mould algorithm for inverse kinematics of the 7-DOF robotic manipulator. Sci Rep 2022;12. [DOI: 10.1038/s41598-022-13516-3] [Reference Citation Analysis]
|
| 19 |
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]
|
| 20 |
Kanimozhi G, Kumar H, Satyanarayana N. A novel hybrid approach for the optimization of double‐diode model parameters of solar cell. Intl J of Energy Research. [DOI: 10.1002/er.8180] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
|
| 21 |
Rawa M, Calasan M, Abusorrah A, Alhussainy AA, Al-Turki Y, Ali ZM, Sindi H, Mekhilef S, Aleem SHEA, Bassi H. Single Diode Solar Cells-Improved Model and Exact Current-Voltage Analytical Solution Based on Lambert's W Function. Sensors (Basel) 2022;22:4173. [PMID: 35684794 DOI: 10.3390/s22114173] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
|
| 22 |
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]
|
| 23 |
Lin H, Ahmadianfar I, Amiri Golilarz N, Jamei M, Heidari AA, Kuang F, Zhang S, Chen H. Adaptive slime mould algorithm for optimal design of photovoltaic models. Energy Science & Engineering. [DOI: 10.1002/ese3.1115] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
|
| 24 |
Rawa M, Abusorrah A, Al-turki Y, Calasan M, Micev M, Ali ZM, Mekhilef S, Bassi H, Sindi H, Aleem SHEA. Estimation of Parameters of Different Equivalent Circuit Models of Solar Cells and Various Photovoltaic Modules Using Hybrid Variants of Honey Badger Algorithm and Artificial Gorilla Troops Optimizer. Mathematics 2022;10:1057. [DOI: 10.3390/math10071057] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
|
| 25 |
Liu J, Wei J, Heidari AA, Kuang F, Zhang S, Gui W, Chen H, Pan Z. Chaotic simulated annealing multi-verse optimization enhanced kernel extreme learning machine for medical diagnosis. Comput Biol Med 2022;144:105356. [PMID: 35299042 DOI: 10.1016/j.compbiomed.2022.105356] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
|
| 26 |
Alfadhli J, Jaragh A, Alfailakawi MG, Ahmad I. FP-SMA: an adaptive, fluctuant population strategy for slime mould algorithm. Neural Comput & Applic. [DOI: 10.1007/s00521-022-07034-6] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
|
| 27 |
Ren L, Heidari AA, Cai Z, Shao Q, Liang G, Chen H, Pan Z. Gaussian kernel probability-driven slime mould algorithm with new movement mechanism for multi-level image segmentation. Measurement 2022;192:110884. [DOI: 10.1016/j.measurement.2022.110884] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
|
| 28 |
Abbassi A, Ben Mehrez R, Touaiti B, Abualigah L, Touti E. Parameterization of photovoltaic solar cell double-diode model based on improved arithmetic optimization algorithm. Optik 2022;253:168600. [DOI: 10.1016/j.ijleo.2022.168600] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 8.0] [Reference Citation Analysis]
|
| 29 |
Hu J, Gui W, Heidari AA, Cai Z, Liang G, Chen H, Pan Z. Dispersed foraging slime mould algorithm: Continuous and binary variants for global optimization and wrapper-based feature selection. Knowledge-Based Systems 2022;237:107761. [DOI: 10.1016/j.knosys.2021.107761] [Cited by in Crossref: 34] [Cited by in F6Publishing: 25] [Article Influence: 34.0] [Reference Citation Analysis]
|
| 30 |
Gao H, Liang G, Chen H. Multi-Population Enhanced Slime Mould Algorithm and with Application to Postgraduate Employment Stability Prediction. Electronics 2022;11:209. [DOI: 10.3390/electronics11020209] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
|
| 31 |
Yu X, Wu X, Luo W. Parameter Identification of Photovoltaic Models by Hybrid Adaptive JAYA Algorithm. Mathematics 2022;10:183. [DOI: 10.3390/math10020183] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
|
| 32 |
Yin S, Luo Q, Zhou Y. EOSMA: An Equilibrium Optimizer Slime Mould Algorithm for Engineering Design Problems. Arab J Sci Eng. [DOI: 10.1007/s13369-021-06513-7] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
|
| 33 |
Fan Y, Wang P, Heidari AA, Chen H, Hamzaturabieh, Mafarja M. Random reselection particle swarm optimization for optimal design of solar photovoltaic modules. Energy 2022;239:121865. [DOI: 10.1016/j.energy.2021.121865] [Cited by in Crossref: 28] [Cited by in F6Publishing: 28] [Article Influence: 28.0] [Reference Citation Analysis]
|
| 34 |
Yin S, Luo Q, Du Y, Zhou Y; College of Artificial Intelligence, Guangxi University for Nationalities, Nanning 530006, China, Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence, Nanning 530006, China, Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis, Nanning 530006, China, College of Information and Communication Engineering, Hainan University, Haikou 570228, China, State Key Laboratory of Marine Resources Utilization in South China Sea, Hainan University, Haikou 570228, China. . MBE 2022;19:2240-85. [DOI: 10.3934/mbe.2022105] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
|
| 35 |
Yeşilbudak M. Afrika Akbabaları Optimizasyon Algoritması Kullanılarak Fotovoltaik Hücre ve Fotovoltaik Modül Parametrelerinin Çıkarımı. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji 2021. [DOI: 10.29109/gujsc.997972] [Reference Citation Analysis]
|
| 36 |
Nicaire NF, Steve PN, Salome NE, Grégroire AO, Riganti-fulginei F. Parameter Estimation of the Photovoltaic System Using Bald Eagle Search (BES) Algorithm. International Journal of Photoenergy 2021;2021:1-20. [DOI: 10.1155/2021/4343203] [Cited by in Crossref: 5] [Cited by in F6Publishing: 8] [Article Influence: 2.5] [Reference Citation Analysis]
|
| 37 |
Wang M, Zhang Q, Chen H, Heidari AA, Mafarja M, Turabieh H. Evaluation of constraint in photovoltaic cells using ensemble multi-strategy shuffled frog leading algorithms. Energy Conversion and Management 2021;244:114484. [DOI: 10.1016/j.enconman.2021.114484] [Cited by in Crossref: 18] [Cited by in F6Publishing: 18] [Article Influence: 9.0] [Reference Citation Analysis]
|
| 38 |
Naik MK, Panda R, Abraham A. Adaptive opposition slime mould algorithm. Soft Comput 2021;25:14297-313. [DOI: 10.1007/s00500-021-06140-2] [Cited by in Crossref: 10] [Cited by in F6Publishing: 9] [Article Influence: 5.0] [Reference Citation Analysis]
|
