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Optimal Elevator Group Control via Deep Asynchronous Actor-Critic Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 12, 页码: 5245-5256
作者:  Wei, Qinglai;  Wang, Lingxiao;  Liu, Yu;  Polycarpou, Marios M.
Adobe PDF(4019Kb)  |  收藏  |  浏览/下载：375/85  |  提交时间：2021/03/08
Elevators  Optimal control  Backpropagation  Machine learning  Neural networks  Learning (artificial intelligence)  Actor  –critic  adaptive dynamic programming  deep learning (DL)  elevator group control (EGC)  optimal control  reinforcement learning (RL)  
Dynamical Channel Pruning by Conditional Accuracy Change for Deep Neural Networks 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 无, 期号: 无, 页码: 无
作者:  Chen, Zhiqiang;  Xu, Ting-Bing;  Du, Changde;  Liu, Cheng-Lin;  He, Huiguang
浏览  |  Adobe PDF(4352Kb)  |  收藏  |  浏览/下载：313/70  |  提交时间：2021/01/27
Conditional accuracy change (CAC), direct criterion, dynamical channel pruning, neural network compression, structure shaping.  
Complex-Valued Discrete-Time Neural Dynamics for Perturbed Time-Dependent Complex Quadratic Programming With Applications 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 9, 页码: 3555-3569
作者:  Qi, Yimeng;  Jin, Long;  Wang, Yaonan;  Xiao, Lin;  Zhang, Jiliang
收藏  |  浏览/下载：219/0  |  提交时间：2021/01/07
Computational modeling  Convergence  Mathematical model  Recurrent neural networks  Perturbation methods  Robots  Numerical models  Complex domain  discrete-time neural dynamics (DTND)  quasi-Newton Broyden-Fletcher-Goldfarb-Shanno (BFGS)  quadratic programming (QP)  
Deep Reinforcement Learning-Based Automatic Exploration for Navigation in Unknown Environment 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 6, 页码: 2064-2076
作者:  Li, Haoran;  Zhang, Qichao;  Zhao, Dongbin
浏览  |  Adobe PDF(4274Kb)  |  收藏  |  浏览/下载：405/123  |  提交时间：2020/08/03
Robot sensing systems  Navigation  Entropy  Neural networks  Task analysis  Planning  Automatic exploration  deep reinforcement learning (DRL)  optimal decision  partial observation