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Wongwan Jung and Daejun Chang
This study proposed a deep reinforcement learning-based energy management strategy (DRL-EMS) that can be applied to a hybrid electric ship propulsion system (HSPS) integrating liquid hydrogen (LH2) fuel gas supply system (FGSS), proton-exchange membrane ...
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Tengjie Yang, Lin Zuo, Xinduoji Yang and Nianbo Liu
In recent years, individual learning path planning has become prevalent in online learning systems, while few studies have focused on teaching path planning for traditional classroom teaching. This paper proposes a target-oriented teaching path optimizat...
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Jeffrey O. Agushaka and Absalom E. Ezugwu
A situation where the set of initial solutions lies near the position of the true optimality (most favourable or desirable solution) by chance can increase the probability of finding the true optimality and significantly reduce the search efforts. In opt...
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Bokyu Kwon and Sang-il Kim
In this paper, the recursive form of an optimal finite impulse response filter is proposed for discrete time-varying state-space models. The recursive form of the finite impulse response filter is derived by employing finite horizon Kalman filtering with...
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Jiang Fan, Qinghao Yuan, Fulei Jing, Hongbin Xu, Hao Wang and Qingze Meng
The emerging Local Maximum-Entropy (LME) approximation, which combines the advantages of global and local approximations, has an unsolved issue wherein it cannot adaptively change the morphology of the basis function according to the local characteristic...
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