화학공학소재연구정보센터
검색결과 : 15건
No. Article
1 Co-estimation of capacity and state-of-charge for lithium-ion batteries in electric vehicles
Li XY, Wang ZP, Zhang L
Energy, 174, 33, 2019
2 Recurrent wavelet-based Elman neural network with modified gravitational search algorithm control for integrated offshore wind and wave power generation systems
Lu KH, Hong CM, Xu QQ
Energy, 170, 40, 2019
3 Optimization of critical parameters of PEM fuel cell using TLBO-DE based on Elman neural network
Guo CJ, Lu JC, Tian Z, Guo W, Darvishan A
Energy Conversion and Management, 183, 149, 2019
4 An indirect RUL prognosis for lithium-ion battery under vibration stress using Elman neural network
Li WH, Jiao ZP, Du L, Fan WY, Zhu YZ
International Journal of Hydrogen Energy, 44(23), 12270, 2019
5 Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network
Liu H, Mi XW, Li YF
Energy Conversion and Management, 156, 498, 2018
6 Short-term power prediction for photovoltaic power plants using a hybrid improved Kmeans-GRA-Elman model based on multivariate meteorological factors and historical power datasets
Lin PJ, Peng ZN, Lai YF, Cheng SY, Chen ZC, Wu LJ
Energy Conversion and Management, 177, 704, 2018
7 Condition classification and performance of mismatched photovoltaic arrays via a pre-filtered Elman neural network decision making tool
Liu GY, Yu WJ, Zhu L
Solar Energy, 173, 1011, 2018
8 Comparative study on three new hybrid models using Elman Neural Network and Empirical Mode Decomposition based technologies improved by Singular Spectrum Analysis for hour-ahead wind speed forecasting
Yu CJ, Li YL, Zhang MJ
Energy Conversion and Management, 147, 75, 2017
9 An improved Wavelet Transform using Singular Spectrum Analysis for wind speed forecasting based on Elman Neural Network
Yu CJ, Li YL, Zhang MJ
Energy Conversion and Management, 148, 895, 2017
10 Elman Neural Networks with Sensitivity Pruning for Modeling Fed-Batch Fermentation Processes
Ni CJ, Yan XF
Journal of Chemical Engineering of Japan, 48(3), 230, 2015