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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限定条件	出处：IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS    作者：罗辛    第一作者

已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序发表日期升序发表日期降序题名升序题名降序WOS被引频次升序WOS被引频次降序提交时间升序提交时间降序期刊影响因子升序期刊影响因子降序
	Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 卷号: 16, 期号: 7, 页码: 4670-4680 作者:  Khan, Ameer Hamza;  Li, Shuai;  Luo, Xin 收藏  |  浏览/下载：128/0  |  提交时间：2020/08/24 Manipulators  Collision avoidance  Trajectory  Optimization  Task analysis  Kinematics  Metaheuristic optimization  obstacle avoidance  recurrent neural network (RNN)  tracking control
	New Disturbance Rejection Constraint for Redundant Robot Manipulators: An Optimization Perspective 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 卷号: 16, 期号: 4, 页码: 2221-2232 作者:  Chen, Dechao;  Li, Shuai;  Wu, Qing;  Luo, Xin 收藏  |  浏览/下载：150/0  |  提交时间：2020/02/18 Manipulators  Optimization  Three-dimensional displays  Robustness  Neural networks  Task analysis  Dynamical quadratic programming (DQP)  hybrid multiple objectives  robustness  redundant robot manipulators  time-varying disturbances
	An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 5, 页码: 2011-2022 作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Shang, MingSheng 收藏  |  浏览/下载：508/0  |  提交时间：2018/07/02 Big data  high-dimensional and sparse matrix  learning algorithms  missing-data estimation  nonnegative latent factor analysis  optimization methods recommender system
	A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 3, 页码: 909-920 作者:  Wu, Di;  Luo, Xin;  Wang, Guoyin;  Shang, Mingsheng;  Yuan, Ye;  Yan, Huyong 收藏  |  浏览/下载：216/0  |  提交时间：2018/06/04 Differential evolution (DE)  general framework  industrial application  positioning optimization  self-labeled  semi-supervised classification (SSC)
	Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 卷号: 13, 期号: 6, 页码: 3098-3107 作者:  Luo, Xin;  Sun, Jianpei;  Wang, Zidong;  Li, Shuai;  Shang, Mingsheng Adobe PDF(803Kb)  |  收藏  |  浏览/下载：429/0  |  提交时间：2018/03/05 Big data application  high-dimensional, and sparse (SHiDS) matrix  nonnegative latent factor (NLF) model  symmetry  undirected HiDS network