BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Çelik E, Öztürk N, Arya Y. Advancement of the search process of salp swarm algorithm for global optimization problems. Expert Systems with Applications 2021;182:115292. [DOI: 10.1016/j.eswa.2021.115292] [Cited by in Crossref: 15] [Cited by in F6Publishing: 17] [Article Influence: 7.5] [Reference Citation Analysis]
Number Citing Articles
1 Zhang L, Hu T, Zhang L, Yang Z, Mcloone S, Menhas MI, Guo Y. A novel dynamic opposite learning enhanced Jaya optimization method for high efficiency plate–fin heat exchanger design optimization. Engineering Applications of Artificial Intelligence 2023;119:105778. [DOI: 10.1016/j.engappai.2022.105778] [Reference Citation Analysis]
2 Singh B, Bishnoi S, Sharma M, Singh P, Dhundhara S. An application of nature inspried algorithm based dual-stage frequency control strategy for multi micro-grid system. Ain Shams Engineering Journal 2023. [DOI: 10.1016/j.asej.2023.102125] [Reference Citation Analysis]
3 Wang X. The analysis and re-optimization of food systems by using intelligent optimization algorithms and machine learning. All Life 2022;15:656-677. [DOI: 10.1080/26895293.2022.2079732] [Reference Citation Analysis]
4 Wang Z, Ding H, Yang J, Hou P, Dhiman G, Wang J, Yang Z, Li A. Orthogonal pinhole-imaging-based learning salp swarm algorithm with self-adaptive structure for global optimization. Front Bioeng Biotechnol 2022;10. [DOI: 10.3389/fbioe.2022.1018895] [Reference Citation Analysis]
5 Zhao J, Zhang B, Guo X, Qi L, Li Z. Self-Adapting Spherical Search Algorithm with Differential Evolution for Global Optimization. Mathematics 2022;10:4519. [DOI: 10.3390/math10234519] [Reference Citation Analysis]
6 Kumar V, Sharma V, Naresh R. Load Frequency Control in Wind Penetrated Power System using a Novel IGWO based MPC Controller. 2022 IEEE 10th Power India International Conference (PIICON) 2022. [DOI: 10.1109/piicon56320.2022.10045258] [Reference Citation Analysis]
7 Çelik E. IEGQO-AOA: Information-Exchanged Gaussian Arithmetic Optimization Algorithm with Quasi-opposition learning. Knowledge-Based Systems 2022. [DOI: 10.1016/j.knosys.2022.110169] [Reference Citation Analysis]
8 Singh B, Slowik A, Bishnoi SK. A Dual-Stage Controller for Frequency Regulation in a Two-Area Realistic Diverse Hybrid Power System Using Bull–Lion Optimization. Energies 2022;15:8063. [DOI: 10.3390/en15218063] [Reference Citation Analysis]
9 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]
10 Yang Y, Gao Y, Tan S, Zhao S, Wu J, Gao S, Zhang T, Tian Y, Wang Y. An opposition learning and spiral modelling based arithmetic optimization algorithm for global continuous optimization problems. Engineering Applications of Artificial Intelligence 2022;113:104981. [DOI: 10.1016/j.engappai.2022.104981] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
11 Iqbal M, Gulzar MM. Master‐slave design for frequency regulation in hybrid power system under complex environment. IET Renewable Power Gen. [DOI: 10.1049/rpg2.12553] [Reference Citation Analysis]
12 Çelik E, Öztürk N, Houssein EH. Influence of energy storage device on load frequency control of an interconnected dual-area thermal and solar photovoltaic power system. Neural Comput & Applic. [DOI: 10.1007/s00521-022-07558-x] [Reference Citation Analysis]
13 Çelik E, Öztürk N. Novel fuzzy 1PD-TI controller for AGC of interconnected electric power systems with renewable power generation and energy storage devices. Engineering Science and Technology, an International Journal 2022. [DOI: 10.1016/j.jestch.2022.101166] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 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]
15 Murali S, Shankar R. Assessment of Amelioration in Frequency Regulation by deploying Novel Intelligent based Controller with Modified HVDC Tie-Line in Deregulated Environment. Smart Science. [DOI: 10.1080/23080477.2022.2054197] [Reference Citation Analysis]
16 Srivastava J, Yadav NK. Rescheduling‐based congestion management by metaheuristic algorithm: Hybridizing lion and moth search models. Int J Numerical Modelling 2022;35. [DOI: 10.1002/jnm.2952] [Reference Citation Analysis]
17 Pahade JK, Jha M. A Hybrid Fuzzy-SCOOT Algorithm to Optimize Possibilistic Mean Semi-absolute Deviation Model for Optimal Portfolio Selection. Int J Fuzzy Syst . [DOI: 10.1007/s40815-022-01251-w] [Reference Citation Analysis]
18 Çelik E. Performance analysis of SSA optimized fuzzy 1PD-PI controller on AGC of renewable energy assisted thermal and hydro-thermal power systems. J Ambient Intell Human Comput. [DOI: 10.1007/s12652-022-03751-x] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
19 Ding H, Cao X, Wang Z, Dhiman G, Hou P, Wang J, Li A, Hu X. . MBE 2022;19:7756-804. [DOI: 10.3934/mbe.2022364] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
20 Zheng X, Nguyen H, Bui X. Exploring the relation between production factors, ore grades, and life of mine for forecasting mining capital cost through a novel cascade forward neural network-based salp swarm optimization model. Resources Policy 2021;74:102300. [DOI: 10.1016/j.resourpol.2021.102300] [Cited by in Crossref: 2] [Article Influence: 1.0] [Reference Citation Analysis]
21 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]
22 Zhou S, Han Y, Sha L, Zhu S. A multi-sample particle swarm optimization algorithm based on electric field force. Math Biosci Eng 2021;18:7464-89. [PMID: 34814258 DOI: 10.3934/mbe.2021369] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]