首页|Studies from Tianjin University of Technology Further Understanding of Machine L earning (Capacity Prediction of Lithium-ion Batteries Based On Ensemble Empirica l Mode Decomposition and Hybrid Machine Learning)
Studies from Tianjin University of Technology Further Understanding of Machine L earning (Capacity Prediction of Lithium-ion Batteries Based On Ensemble Empirica l Mode Decomposition and Hybrid Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating from Tianjin, People’s Republic of China, by NewsRx correspondents, research stated, “Considering the i nfluence of capacity regeneration on the prediction accuracy of the remaining us eful life (RUL) of lithium-ion batteries (LIB), a multi-stage capacity predictio n method based on ensemble empirical mode decomposition (EEMD) and hybrid machin e learning is proposed. Firstly, the aging data of LIB is decomposed into residual sequence (degradation trends) and intrinsic mode function (IMF) by the EEMD algorithm.”
TianjinPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningTianjin University of Technology
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