中国科学院重庆绿色智能技术研究院机构知识库

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发表日期：2022

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	Predicting Monthly Runoff of the Upper Yangtze River Based on Multiple Machine Learning Models 期刊论文 SUSTAINABILITY, 2022, 卷号: 14, 期号: 18, 页码: 23 作者:  Li, Xiao;  Zhang, Liping;  Zeng, Sidong;  Tang, Zhenyu;  Liu, Lina;  Zhang, Qin;  Tang, Zhengyang;  Hua, Xiaojun 收藏  |  浏览/下载：42/0  |  提交时间：2022/12/26 monthly runoff prediction  machine learning  copula entropy  stepwise regression  Upper Yangtze River
	A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis 期刊论文 IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2022, 卷号: 9, 期号: 3, 页码: 533-546 作者:  Wu, Hao;  Luo, Xin;  Zhou, MengChu;  Rawa, Muhyaddin J.;  Sedraoui, Khaled;  Albeshri, Aiiad 收藏  |  浏览/下载：55/0  |  提交时间：2022/08/22 Big data  high dimensional and incomplete (HDI) tensor  latent factorization-of-tensors (LFT)  machine learning  missing data  optimization  proportional-integral-derivative (PID) controller
	RNN for Repetitive Motion Generation of Redundant Robot Manipulators: An Orthogonal Projection-Based Scheme 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 2, 页码: 615-628 作者:  Xie, Zhengtai;  Jin, Long;  Luo, Xin;  Sun, Zhongbo;  Liu, Mei 收藏  |  浏览/下载：50/0  |  提交时间：2022/08/22 Manipulators  Kinematics  Recurrent neural networks  Task analysis  Redundancy  Error elimination  gradient descent method  orthogonal projection method  recurrent neural network (RNN)  redundant manipulators  repetitive motion generation (RMG)