H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 65 Citations 16,725 405 World Ranking 1118 National Ranking 105

Overview

What is he best known for?

The fields of study he is best known for:

  • Quantum mechanics
  • Artificial intelligence
  • Organic chemistry

Jun Zhang mostly deals with Mathematical optimization, Evolutionary algorithm, Particle swarm optimization, Algorithm design and Artificial intelligence. His work investigates the relationship between Mathematical optimization and topics such as Benchmark that intersect with problems in Global optimization. His Evolutionary algorithm research is multidisciplinary, incorporating perspectives in Evolutionary computation, Schedule, Differential evolution and Wireless sensor network.

The study incorporates disciplines such as Computational complexity theory and Heuristic in addition to Particle swarm optimization. His Algorithm design study incorporates themes from Time complexity and Vehicle routing problem. His Artificial intelligence study combines topics in areas such as Genetic algorithm and Machine learning.

His most cited work include:

  • Adaptive Particle Swarm Optimization (1300 citations)
  • Phase diagram and electronic indication of high-temperature superconductivity at 65 K in single-layer FeSe films (534 citations)
  • Orthogonal Learning Particle Swarm Optimization (514 citations)

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

Mathematical optimization, Artificial intelligence, Optimization problem, Evolutionary algorithm and Particle swarm optimization are his primary areas of study. His research investigates the link between Mathematical optimization and topics such as Benchmark that cross with problems in Convergence. His Artificial intelligence research is multidisciplinary, relying on both Algorithm design, Machine learning, Computer vision and Pattern recognition.

His Optimization problem study frequently draws connections between adjacent fields such as Multi-objective optimization. His research integrates issues of Swarm behaviour and Metaheuristic in his study of Multi-swarm optimization. His research links Algorithm with Evolutionary computation.

He most often published in these fields:

  • Mathematical optimization (25.38%)
  • Artificial intelligence (11.60%)
  • Optimization problem (11.38%)

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

  • Mathematical optimization (25.38%)
  • Optimization problem (11.38%)
  • Evolutionary algorithm (10.18%)

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

His primary areas of study are Mathematical optimization, Optimization problem, Evolutionary algorithm, Particle swarm optimization and Evolutionary computation. His Mathematical optimization study frequently links to other fields, such as Process. His research in Optimization problem intersects with topics in Convergence, Differential evolution, Multi-objective optimization and Benchmark.

His Evolutionary algorithm study is concerned with the field of Artificial intelligence as a whole. His Particle swarm optimization study often links to related topics such as Distributed computing. The Evolutionary computation study combines topics in areas such as Theoretical computer science and Computational intelligence.

Between 2019 and 2021, his most popular works were:

  • Automatic Niching Differential Evolution With Contour Prediction Approach for Multimodal Optimization Problems (40 citations)
  • Conjugate solid-liquid phase change heat transfer in heatsink filled with phase change material-metal foam (27 citations)
  • Processing and valorization of cellulose, lignin and lignocellulose using ionic liquids (23 citations)

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

  • Quantum mechanics
  • Artificial intelligence
  • Organic chemistry

Jun Zhang mainly focuses on Optimization problem, Mathematical optimization, Evolutionary algorithm, Benchmark and Particle swarm optimization. The concepts of his Optimization problem study are interwoven with issues in Test data generation, Differential evolution, Artificial intelligence and Shortest path problem. His Multi-objective optimization study in the realm of Mathematical optimization connects with subjects such as Supply chain network.

His study in Evolutionary algorithm is interdisciplinary in nature, drawing from both Evolutionary computation, Data-driven, Linear programming and Heuristic. His Particle swarm optimization research includes elements of Local optimum, Virtualization, Distributed computing, Metaheuristic and Heuristic. His Algorithm research focuses on Convergence and how it relates to Local search.

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

Adaptive Particle Swarm Optimization

Zhi-Hui Zhan;Jun Zhang;Yun Li;H.S.-H. Chung.
systems man and cybernetics (2009)

1782 Citations

Phase Diagram and High Temperature Superconductivity at 65 K in Tuning Carrier Concentration of Single-Layer FeSe Films

Shaolong He;Junfeng He;Wenhao Zhang;Lin Zhao.
arXiv: Superconductivity (2012)

761 Citations

Orthogonal Learning Particle Swarm Optimization

Zhi-Hui Zhan;Jun Zhang;Yun Li;Yu-Hui Shi.
IEEE Transactions on Evolutionary Computation (2011)

694 Citations

Phase diagram and electronic indication of high-temperature superconductivity at 65 K in single-layer FeSe films

Shaolong He;Junfeng He;Wenhao Zhang;Wenhao Zhang;Lin Zhao.
Nature Materials (2013)

673 Citations

Electronic origin of high-temperature superconductivity in single-layer FeSe superconductor

Defa Liu;Wenhao Zhang;Wenhao Zhang;Daixiang Mou;Junfeng He.
Nature Communications (2012)

485 Citations

Particle Swarm Optimization With an Aging Leader and Challengers

Wei-Neng Chen;Jun Zhang;Ying Lin;Ni Chen.
IEEE Transactions on Evolutionary Computation (2013)

472 Citations

An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem With Various QoS Requirements

Wei-Neng Chen;Jun Zhang.
systems man and cybernetics (2009)

419 Citations

A Novel Set-Based Particle Swarm Optimization Method for Discrete Optimization Problems

Wei-Neng Chen;Jun Zhang;H.S.H. Chung;Wen-Liang Zhong.
IEEE Transactions on Evolutionary Computation (2010)

411 Citations

Cloud Computing Resource Scheduling and a Survey of Its Evolutionary Approaches

Zhi-Hui Zhan;Xiao-Fang Liu;Yue-Jiao Gong;Jun Zhang.
ACM Computing Surveys (2015)

401 Citations

Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms

Jun Zhang;Henry Shu-Hung Chung;Wai-Lun Lo.
IEEE Transactions on Evolutionary Computation (2007)

328 Citations

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Best Scientists Citing Jun Zhang

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CINVESTAV

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