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For: Zhou J, Zhang Y, Zhang Y, Shang W, Yang Z, Feng W. Parameters identification of photovoltaic models using a differential evolution algorithm based on elite and obsolete dynamic learning. Applied Energy 2022;314:118877. [DOI: 10.1016/j.apenergy.2022.118877] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 Satria H, Syah RBY, Nehdi ML, Almustafa MK, Adam AOI. Parameters Identification of Solar PV Using Hybrid Chaotic Northern Goshawk and Pattern Search. Sustainability 2023;15:5027. [DOI: 10.3390/su15065027] [Reference Citation Analysis]
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3 Su Z, Yang L, Song J, Jin X, Wu X, Li X. Sensitivity analysis and exergoeconomic optimization of an improved He-CO2 cascade Brayton cycle for concentrated solar power. Energy Conversion and Management 2023;279:116756. [DOI: 10.1016/j.enconman.2023.116756] [Reference Citation Analysis]
4 Zhang Q, He Y, Shu M, Zhang W, Yang D, Song J, Li G, Zheng Y, Yang Y, Tie J, Li J, Li M. A Level-Based Learning Swarm Optimizer with Stochastic Fractal Search for Parameters Identification of Solar Photovoltaic Models. Mathematical Problems in Engineering 2023;2023:1-16. [DOI: 10.1155/2023/3397430] [Reference Citation Analysis]
5 Lv Z, Wang N, Lou R, Tian Y, Guizani M. Towards carbon Neutrality: Prediction of wave energy based on improved GRU in Maritime transportation. Applied Energy 2023;331:120394. [DOI: 10.1016/j.apenergy.2022.120394] [Reference Citation Analysis]
6 Liu Q, Li H, Shang W, Wang K. Spatio-temporal distribution of Chinese cities’ air quality and the impact of high-speed rail. Renewable and Sustainable Energy Reviews 2022;170:112970. [DOI: 10.1016/j.rser.2022.112970] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Hua L, Zhang C, Sun W, Li Y, Xiong J, Nazir MS. An evolutionary deep learning soft sensor model based on random forest feature selection technique for penicillin fermentation process. ISA Transactions 2022. [DOI: 10.1016/j.isatra.2022.10.044] [Reference Citation Analysis]
8 Li F, Li Y, Zhou S, Chen Y, Sun X, Deng Y. Wireless power transfer tuning model of electric vehicles with pavement materials as transmission media for energy conservation. Applied Energy 2022;323:119631. [DOI: 10.1016/j.apenergy.2022.119631] [Reference Citation Analysis]
9 Xian S, Lei H, Chen K, Li Z. A novel fuzzy time series model based on improved sparrow search algorithm and CEEMDAN. Appl Intell. [DOI: 10.1007/s10489-022-04036-8] [Reference Citation Analysis]
10 Bai S, Bi X, Han C, Zhou Q, Shang W, Yang M, Wang L, Ieromonachou P, He H. Evaluating R&D efficiency of China’s listed lithium battery enterprises. Front Eng Manag . [DOI: 10.1007/s42524-022-0213-5] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
11 Qiao D, Wei X, Fan W, Jiang B, Lai X, Zheng Y, Tang X, Dai H. Toward safe carbon–neutral transportation: Battery internal short circuit diagnosis based on cloud data for electric vehicles. Applied Energy 2022;317:119168. [DOI: 10.1016/j.apenergy.2022.119168] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]