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
Engineering and Technology D-index 35 Citations 4,660 146 World Ranking 3546 National Ranking 381

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer network
  • Algorithm

Haipeng Peng spends much of his time researching Control theory, Mathematical optimization, Economic dispatch, Synchronization and Memristor. The concepts of his Control theory study are interwoven with issues in Control and Identification. Mathematical optimization is frequently linked to Chaotic in his study.

His Economic dispatch research is multidisciplinary, incorporating perspectives in Swarm intelligence and Chaotic particle swarm optimization. His research on Memristor frequently connects to adjacent areas such as Artificial neural network. His Artificial neural network research is multidisciplinary, relying on both Differential inclusion and Lyapunov stability.

His most cited work include:

  • A multi-objective chaotic particle swarm optimization for environmental/economic dispatch (159 citations)
  • Parameters identification of chaotic systems via chaotic ant swarm (116 citations)
  • A hybrid CPSO–SQP method for economic dispatch considering the valve-point effects (99 citations)

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

His primary scientific interests are in Control theory, Synchronization, Artificial neural network, Memristor and Synchronization. His study connects Differential inclusion and Control theory. His Differential inclusion study combines topics from a wide range of disciplines, such as Recurrent neural network and Boundary.

His research integrates issues of Correctness, Settling time and Bounded function in his study of Artificial neural network. Haipeng Peng interconnects Finite time, Cellular neural network and Fuzzy logic in the investigation of issues within Memristor. His Identification study combines topics in areas such as Chaotic and Mathematical optimization.

He most often published in these fields:

  • Control theory (33.95%)
  • Synchronization (24.69%)
  • Artificial neural network (19.75%)

What were the highlights of his more recent work (between 2017-2021)?

  • Synchronization (24.69%)
  • Artificial neural network (19.75%)
  • Control theory (33.95%)

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

His scientific interests lie mostly in Synchronization, Artificial neural network, Control theory, Memristor and Compressed sensing. Throughout his Synchronization studies, he incorporates elements of other sciences such as Lyapunov function, Nonlinear system, Stability, Differential inclusion and Fixed time. His Artificial neural network research is multidisciplinary, incorporating elements of System parameters, Settling time and Linear matrix.

His Adaptive control study in the realm of Control theory interacts with subjects such as Simple. The various areas that Haipeng Peng examines in his Memristor study include Finite time, Control theory, Fuzzy logic and Topology. The concepts of his Compressed sensing study are interwoven with issues in Hash function, Secure transmission, Encryption and Matrix multiplication.

Between 2017 and 2021, his most popular works were:

  • Propagation analysis and prediction of the COVID-19 (90 citations)
  • Finite-time stability and synchronization of memristor-based fractional-order fuzzy cellular neural networks (55 citations)
  • Fixed-time synchronization of inertial memristor-based neural networks with discrete delay (45 citations)

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

  • Artificial intelligence
  • Computer network
  • Algorithm

Synchronization, Control theory, Artificial neural network, Memristor and Settling time are his primary areas of study. His Synchronization research covers fields of interest such as Lyapunov function, Stability, Simple and Computational intelligence. His studies deal with areas such as Control, Banach fixed-point theorem and Stability theorem as well as Stability.

His Artificial neural network research is multidisciplinary, relying on both Correctness and Nonlinear system. His Memristor research includes themes of Cellular neural network, Linear matrix, System parameters and Fuzzy logic. In his study, which falls under the umbrella issue of Settling time, Stability criterion, Stability, Applied mathematics and Plaintext is strongly linked to Upper and lower bounds.

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

A multi-objective chaotic particle swarm optimization for environmental/economic dispatch

Jiejin Cai;Xiaoqian Ma;Qiong Li;Lixiang Li.
Energy Conversion and Management (2009)

204 Citations

Parameters identification of chaotic systems via chaotic ant swarm

Lixiang Li;Yixian Yang;Haipeng Peng;Xiangdong Wang.
Chaos Solitons & Fractals (2006)

158 Citations

Propagation analysis and prediction of the COVID-19

Lixiang Li;Zihang Yang;Zhongkai Dang;Cui Meng.
Infectious Disease Modelling (2020)

146 Citations

Chaotic ant swarm optimization to economic dispatch

Jiejin Cai;Xiaoqian Ma;Lixiang Li;Yixian Yang.
Electric Power Systems Research (2007)

133 Citations

A hybrid CPSO–SQP method for economic dispatch considering the valve-point effects

Jiejin Cai;Qiong Li;Lixiang Li;Haipeng Peng.
Energy Conversion and Management (2012)

133 Citations

A multi-objective chaotic ant swarm optimization for environmental/economic dispatch

Jiejin Cai;Xiaoqian Ma;Qiong Li;Lixiang Li.
International Journal of Electrical Power & Energy Systems (2010)

131 Citations

Multiple routes transmitted epidemics on multiplex networks

Dawei Zhao;Lixiang Li;Haipeng Peng;Qun Luo.
Physics Letters A (2014)

121 Citations

Complex networks-based energy-efficient evolution model for wireless sensor networks

Hailin Zhu;Hong Luo;Haipeng Peng;Lixiang Li.
Chaos Solitons & Fractals (2009)

111 Citations

An Enhanced Biometric-Based Authentication Scheme for Telecare Medicine Information Systems Using Elliptic Curve Cryptosystem

Yanrong Lu;Lixiang Li;Haipeng Peng;Yixian Yang.
Journal of Medical Systems (2015)

103 Citations

Synchronization control of memristor-based recurrent neural networks with perturbations.

Weiping Wang;Lixiang Li;Haipeng Peng;Haipeng Peng;Jinghua Xiao.
Neural Networks (2014)

99 Citations

Best Scientists Citing Haipeng Peng

Jinde Cao

Jinde Cao

Southeast University

Publications: 51

Lixiang Li

Lixiang Li

Beijing University of Posts and Telecommunications

Publications: 34

Haijun Jiang

Haijun Jiang

Xinjiang University

Publications: 21

Ashok Kumar Das

Ashok Kumar Das

International Institute of Information Technology, Hyderabad

Publications: 21

Leandro dos Santos Coelho

Leandro dos Santos Coelho

Pontifícia Universidade Católica do Paraná

Publications: 19

Saru Kumari

Saru Kumari

Chaudhary Charan Singh University

Publications: 19

Tingwen Huang

Tingwen Huang

Texas A&M University at Qatar

Publications: 17

Yixian Yang

Yixian Yang

Beijing University of Posts and Telecommunications

Publications: 15

Xinping Guan

Xinping Guan

Shanghai Jiao Tong University

Publications: 14

Jürgen Kurths

Jürgen Kurths

Potsdam Institute for Climate Impact Research

Publications: 13

Jianzhong Zhou

Jianzhong Zhou

Huazhong University of Science and Technology

Publications: 12

Dongho Won

Dongho Won

Sungkyunkwan University

Publications: 12

Cheng Hu

Cheng Hu

Xinjiang University

Publications: 12

Viviana Cocco Mariani

Viviana Cocco Mariani

Pontifícia Universidade Católica do Paraná

Publications: 11

Muhammad Khurram Khan

Muhammad Khurram Khan

King Saud University

Publications: 10

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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