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 43 Citations 6,632 228 World Ranking 3852 National Ranking 359

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Gene

Kwong-Sak Leung mainly focuses on Artificial intelligence, Data mining, Machine learning, Genetic algorithm and Fuzzy logic. His Artificial intelligence research incorporates themes from Gene chip analysis and Logistic regression. His biological study spans a wide range of topics, including Feature, Cluster analysis, Mixture model, Evolutionary computation and Genetic programming.

His Machine learning study deals with Docking intersecting with Protein structure. His Genetic algorithm research is multidisciplinary, relying on both Optimization problem, Bayesian network and Set. He has included themes like Legal expert system, Expert system and Model-based reasoning in his Fuzzy logic study.

His most cited work include:

  • A Survey of Crowdsourcing Systems (292 citations)
  • Data Mining Using Grammar Based Genetic Programming and Applications (166 citations)
  • Convergence analysis of cellular neural networks with unbounded delay (155 citations)

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

His scientific interests lie mostly in Artificial intelligence, Data mining, Machine learning, Genetic algorithm and Mathematical optimization. His research on Artificial intelligence often connects related topics like Pattern recognition. His work carried out in the field of Data mining brings together such families of science as Fuzzy logic and Cluster analysis.

Kwong-Sak Leung has researched Fuzzy logic in several fields, including Legal expert system and Expert system. The Genetic algorithm study combines topics in areas such as Optimization problem, Set, Cancer chemotherapy and Benchmark. His research in Mathematical optimization intersects with topics in Algorithm, Regularization and Nonlinear system.

He most often published in these fields:

  • Artificial intelligence (29.72%)
  • Data mining (16.67%)
  • Machine learning (16.39%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (29.72%)
  • Computational biology (8.06%)
  • Machine learning (16.39%)

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

His primary areas of study are Artificial intelligence, Computational biology, Machine learning, Data mining and Gene. His Artificial intelligence study combines topics from a wide range of disciplines, such as Natural language processing and Pattern recognition. His studies in Computational biology integrate themes in fields like RNA, DNA sequencing and Cluster analysis.

His studies deal with areas such as Crowdsourcing, Scalability, Inference and Bioinformatics as well as Machine learning. His work deals with themes such as Protein dna, Normalization and Gene expression profiling, which intersect with Data mining. His work on Genetic representation as part of general Genetic programming study is frequently linked to Adaptive grammar, therefore connecting diverse disciplines of science.

Between 2014 and 2021, his most popular works were:

  • A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems (136 citations)
  • Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets. (94 citations)
  • ViRBase: a resource for virus–host ncRNA-associated interactions (58 citations)

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

  • Artificial intelligence
  • Machine learning
  • Gene

The scientist’s investigation covers issues in Artificial intelligence, Computational biology, Machine learning, Data mining and Random forest. Kwong-Sak Leung usually deals with Artificial intelligence and limits it to topics linked to Pattern recognition and Drug discovery. His Computational biology research includes elements of RNA, Non-coding RNA, Gene and Web server.

His research investigates the connection with Non-coding RNA and areas like Virology which intersect with concerns in Genome. Kwong-Sak Leung combines subjects such as Data science, Complex system, Docking and Bioinformatics with his study of Machine learning. His Data mining study integrates concerns from other disciplines, such as Normalization, Preprocessor and Transcriptome, RNA-Seq.

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 Survey of Crowdsourcing Systems

Man-Ching Yuen;Irwin King;Kwong-Sak Leung.
privacy security risk and trust (2011)

503 Citations

Data Mining Using Grammar Based Genetic Programming and Applications

Man Leung Wong;Kwong Sak Leung.
(2000)

320 Citations

Fuzzy concepts in expert systems

K.S. Leung;W. Lam.
IEEE Computer (1988)

232 Citations

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems

Wei Ying Yi;Kin Ming Lo;Terrence Mak;Kwong Sak Leung.
Sensors (2015)

213 Citations

Convergence analysis of cellular neural networks with unbounded delay

Zhang Yi;Pheng Ann Heng;Kwong Sak Leung.
IEEE Transactions on Circuits and Systems I-regular Papers (2001)

194 Citations

An expanding self-organizing neural network for the traveling salesman problem

Kwong-Sak Leung;Hui-Dong Jin;Zong-Ben Xu.
Neurocomputing (2004)

175 Citations

Using evolutionary programming and minimum description length principle for data mining of Bayesian networks

Man Leung Wong;Wai Lam;Kwong Sak Leung.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1999)

152 Citations

An efficient data mining method for learning Bayesian networks using an evolutionary algorithm-based hybrid approach

Man Leung Wong;Kwong Sak Leung.
IEEE Transactions on Evolutionary Computation (2004)

152 Citations

A genetic algorithm for determining nonadditive set functions in information fusion

Zhenyuan Wang;Kwong-sak Leung;Jia Wang.
Fuzzy Sets and Systems (1999)

150 Citations

Sparse logistic regression with a L1/2 penalty for gene selection in cancer classification

Yong Liang;Cheng Liu;Xin-Ze Luan;Kwong-Sak Leung.
BMC Bioinformatics (2013)

134 Citations

Best Scientists Citing Kwong-Sak Leung

Sabri Arik

Sabri Arik

Istanbul University

Publications: 28

Yong Liang

Yong Liang

Jianghan University

Publications: 26

Ronald R. Yager

Ronald R. Yager

Iona College

Publications: 26

Michael O'Neill

Michael O'Neill

University College Dublin

Publications: 24

Sebastián Ventura

Sebastián Ventura

University of Córdoba

Publications: 21

Alex A. Freitas

Alex A. Freitas

University of Kent

Publications: 19

Guo-Wei Wei

Guo-Wei Wei

Michigan State University

Publications: 19

Francisco Herrera

Francisco Herrera

University of Granada

Publications: 18

Witold Pedrycz

Witold Pedrycz

University of Alberta

Publications: 16

John R. Koza

John R. Koza

Stanford University

Publications: 15

Jinde Cao

Jinde Cao

Southeast University

Publications: 14

Yong Shi

Yong Shi

Chinese Academy of Sciences

Publications: 13

Zhigang Zeng

Zhigang Zeng

Huazhong University of Science and Technology

Publications: 13

Xi-Zhao Wang

Xi-Zhao Wang

Tsinghua University

Publications: 13

Shyi-Ming Chen

Shyi-Ming Chen

National Taiwan University of Science and Technology

Publications: 13

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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