D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 51 Citations 8,075 220 World Ranking 2706 National Ranking 1432

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Control theory
  • Algorithm

The scientist’s investigation covers issues in Artificial neural network, Recurrent neural network, Control theory, Mathematical optimization and Quadratic programming. The study incorporates disciplines such as Computation and Robustness in addition to Artificial neural network. His Recurrent neural network research incorporates themes from Control system, Stability, Control, Nonlinear system and Activation function.

His biological study spans a wide range of topics, including Winner-take-all and Topology. His work carried out in the field of Control theory brings together such families of science as Convergence and Robotic arm. His Mathematical optimization study combines topics from a wide range of disciplines, such as Function and Monotonic function.

His most cited work include:

  • A Nonnegative Latent Factor Model for Large-Scale Sparse Matrices in Recommender Systems via Alternating Direction Method (181 citations)
  • Manipulability Optimization of Redundant Manipulators Using Dynamic Neural Networks (179 citations)
  • Accelerating a Recurrent Neural Network to Finite-Time Convergence for Solving Time-Varying Sylvester Equation by Using a Sign-Bi-power Activation Function (168 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Control theory, Artificial neural network, Robot, Recurrent neural network and Artificial intelligence. In general Control theory, his work in Nonlinear system, Control theory and Optimal control is often linked to Redundancy linking many areas of study. His study focuses on the intersection of Artificial neural network and fields such as Mathematical optimization with connections in the field of Algorithm.

His studies deal with areas such as Control engineering, Control, Task and Trajectory as well as Robot. Recurrent neural network is closely attributed to Stability in his work. His research in Artificial intelligence intersects with topics in Machine learning, Computer vision and Pattern recognition.

He most often published in these fields:

  • Control theory (36.46%)
  • Artificial neural network (26.30%)
  • Robot (22.66%)

What were the highlights of his more recent work (between 2019-2021)?

  • Control theory (36.46%)
  • Robot (22.66%)
  • Artificial neural network (26.30%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Control theory, Robot, Artificial neural network, Recurrent neural network and Nonlinear system. Shuai Li combines subjects such as Convergence and Quadratic programming with his study of Control theory. His Convergence research includes elements of Jacobian matrix and determinant and Motion control.

His Robot study incorporates themes from Task, Trajectory and Identification. His Recurrent neural network study frequently intersects with other fields, such as Stability. The concepts of his Nonlinear system study are interwoven with issues in Mathematical optimization and Optimal control.

Between 2019 and 2021, his most popular works were:

  • Adaptive Neural Output-Feedback Decentralized Control for Large-Scale Nonlinear Systems With Stochastic Disturbances (62 citations)
  • Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications (39 citations)
  • Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach (31 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Control theory
  • Algorithm

His primary areas of study are Control theory, Artificial neural network, Robot, Robustness and Motion planning. His research integrates issues of Recurrent neural network and Quadratic programming in his study of Control theory. Shuai Li has researched Recurrent neural network in several fields, including Stability, Control theory, Trajectory and Match moving.

His studies deal with areas such as Discretization, Convergence and Linear system as well as Artificial neural network. His work deals with themes such as Control engineering and Feature extraction, which intersect with Robot. The Motion planning study combines topics in areas such as Search algorithm and Motion control.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Manipulability Optimization of Redundant Manipulators Using Dynamic Neural Networks

Long Jin;Shuai Li;Hung Manh La;Xin Luo.
IEEE Transactions on Industrial Electronics (2017)

235 Citations

Accelerating a Recurrent Neural Network to Finite-Time Convergence for Solving Time-Varying Sylvester Equation by Using a Sign-Bi-power Activation Function

Shuai Li;Sanfeng Chen;Bo Liu.
Neural Processing Letters (2013)

208 Citations

A Nonnegative Latent Factor Model for Large-Scale Sparse Matrices in Recommender Systems via Alternating Direction Method

Xin Luo;MengChu Zhou;Shuai Li;Zhuhong You.
IEEE Transactions on Neural Networks (2016)

208 Citations

Distributed Recurrent Neural Networks for Cooperative Control of Manipulators: A Game-Theoretic Perspective

Shuai Li;Jinbo He;Yangming Li;Muhammad Usman Rafique.
IEEE Transactions on Neural Networks (2017)

198 Citations

Kinematic Control of Redundant Manipulators Using Neural Networks

Shuai Li;Yunong Zhang;Long Jin.
IEEE Transactions on Neural Networks (2017)

187 Citations

Distributed Task Allocation of Multiple Robots: A Control Perspective

Long Jin;Shuai Li.
IEEE Transactions on Systems, Man, and Cybernetics (2018)

157 Citations

Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

Shuai Li;Yangming Li.
IEEE Transactions on Systems, Man, and Cybernetics (2014)

153 Citations

Decentralized kinematic control of a class of collaborative redundant manipulators via recurrent neural networks

Shuai Li;Sanfeng Chen;Bo Liu;Yangming Li.
Neurocomputing (2012)

150 Citations

Design and Analysis of FTZNN Applied to the Real-Time Solution of a Nonstationary Lyapunov Equation and Tracking Control of a Wheeled Mobile Manipulator

Lin Xiao;Bolin Liao;Shuai Li;Zhijun Zhang.
IEEE Transactions on Industrial Informatics (2018)

139 Citations

Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data

Xin Luo;MengChu Zhou;Shuai Li;YunNi Xia.
IEEE Transactions on Systems, Man, and Cybernetics (2018)

135 Citations

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