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 34 Citations 4,256 146 World Ranking 3849 National Ranking 415

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of study are Data mining, Artificial intelligence, Group analysis, Decision analysis and Machine learning. As a member of one scientific family, he mostly works in the field of Data mining, focusing on Quality of service and, on occasion, Customer satisfaction and Similarity. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Econometrics.

The Group analysis study combines topics in areas such as Attributive, Process, Selection and Identification. He interconnects Fuzzy logic, Electrical load and Cluster analysis in the investigation of issues within Process. His studies deal with areas such as Nonlinear programming and Problem domain as well as Selection.

His most cited work include:

  • A review of electric load classification in smart grid environment (138 citations)
  • Energy Internet: The business perspective (118 citations)
  • Combining QoS prediction and customer satisfaction estimation to solve cloud service trustworthiness evaluation problems (97 citations)

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

Shanlin Yang spends much of his time researching Mathematical optimization, Artificial intelligence, Real-time computing, Job shop scheduling and Field. Shanlin Yang has included themes like Space and Computational intelligence in his Mathematical optimization study. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Data mining, Identification, Machine learning, Process and Pattern recognition.

His Data mining study combines topics in areas such as Mains electricity and Support vector machine. His study looks at the relationship between Machine learning and fields such as Decision analysis, as well as how they intersect with chemical problems. Shanlin Yang combines subjects such as Group analysis and Selection with his study of Process.

He most often published in these fields:

  • Mathematical optimization (28.11%)
  • Artificial intelligence (20.74%)
  • Real-time computing (15.21%)

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

  • Mathematical optimization (28.11%)
  • Group decision-making (13.36%)
  • Computational intelligence (9.68%)

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

His main research concerns Mathematical optimization, Group decision-making, Computational intelligence, Job shop scheduling and Field. His work on Dynamic programming as part of his general Mathematical optimization study is frequently connected to Set cover problem, thereby bridging the divide between different branches of science. His Group decision-making research is multidisciplinary, incorporating elements of Preference, Data mining, Ranking, Decision problem and Operations research.

The concepts of his Field study are interwoven with issues in Algorithm, Optimization problem and Real-time computing. He has researched Selection in several fields, including Preference relation, Preference, Artificial intelligence, Machine learning and Process. His Machine learning research incorporates elements of Multiple-criteria decision analysis and Interval.

Between 2019 and 2021, his most popular works were:

  • Multiple criteria group decision making based on group satisfaction (16 citations)
  • Multiple criteria group decision making based on group satisfaction (16 citations)
  • Comparison of Evidential Reasoning Algorithm with Linear Combination in Decision Making (11 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

Shanlin Yang mostly deals with Group decision-making, Mathematical optimization, Operations research, Reliability and Decision problem. His Group decision-making research is multidisciplinary, relying on both Semantics, Style, Preference and Pairwise comparison. His research on Mathematical optimization focuses in particular on Hybrid algorithm.

His Operations research research includes elements of Key, Decision support system, Rank correlation and Measure. His studies in Reliability integrate themes in fields like Variation, Group analysis and Process. His work deals with themes such as Context, Preference, Consistency, Probabilistic logic and Fuzzy logic, which intersect with Decision problem.

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 review of electric load classification in smart grid environment

Kai-le Zhou;Shan-lin Yang;Chao Shen.
Renewable & Sustainable Energy Reviews (2013)

206 Citations

Energy Internet: The business perspective

Kaile Zhou;Shanlin Yang;Zhen Shao.
Applied Energy (2016)

174 Citations

On electricity consumption and economic growth in China

Chi Zhang;Kaile Zhou;Shanlin Yang;Zhen Shao.
Renewable & Sustainable Energy Reviews (2017)

140 Citations

An improved boosting based on feature selection for corporate bankruptcy prediction

Gang Wang;Jian Ma;Shanlin Yang.
Expert Systems With Applications (2014)

136 Citations

Blockchain-Based Medical Records Secure Storage and Medical Service Framework

Yi Chen;Shuai Ding;Zheng Xu;Handong Zheng.
Journal of Medical Systems (2019)

132 Citations

Combining QoS prediction and customer satisfaction estimation to solve cloud service trustworthiness evaluation problems

Shuai Ding;Shanlin Yang;Youtao Zhang;Changyong Liang.
Knowledge Based Systems (2014)

130 Citations

The group consensus based evidential reasoning approach for multiple attributive group decision analysis

Chao Fu;Chao Fu;Shan-Lin Yang;Shan-Lin Yang.
European Journal of Operational Research (2010)

126 Citations

An evidential reasoning based consensus model for multiple attribute group decision analysis problems with interval-valued group consensus requirements

Chao Fu;Chao Fu;Shanlin Yang;Shanlin Yang.
European Journal of Operational Research (2012)

111 Citations

Demand side management in China: The context of China’s power industry reform

Kaile Zhou;Shanlin Yang.
Renewable & Sustainable Energy Reviews (2015)

104 Citations

Residential electricity consumption behavior: Influencing factors, related theories and intervention strategies

Zhifeng Guo;Kaile Zhou;Chi Zhang;Xinhui Lu.
Renewable & Sustainable Energy Reviews (2018)

95 Citations

Best Scientists Citing Shanlin Yang

Panos M. Pardalos

Panos M. Pardalos

University of Florida

Publications: 27

Yong Deng

Yong Deng

Southwest University

Publications: 25

Gleb Beliakov

Gleb Beliakov

Deakin University

Publications: 17

Zeshui Xu

Zeshui Xu

Sichuan University

Publications: 13

Nadeem Javaid

Nadeem Javaid

COMSATS University Islamabad

Publications: 13

Jian-Bo Yang

Jian-Bo Yang

University of Manchester

Publications: 12

Jiuping Xu

Jiuping Xu

Sichuan University

Publications: 11

Francisco Herrera

Francisco Herrera

University of Granada

Publications: 9

Huchang Liao

Huchang Liao

Sichuan University

Publications: 9

Tao Yu

Tao Yu

South China University of Technology

Publications: 9

Witold Pedrycz

Witold Pedrycz

University of Alberta

Publications: 8

Luis Martínez

Luis Martínez

University of Jaén

Publications: 7

Dong-Ling Xu

Dong-Ling Xu

University of Manchester

Publications: 7

Ronald R. Yager

Ronald R. Yager

Iona College

Publications: 7

Enrique Herrera-Viedma

Enrique Herrera-Viedma

University of Granada

Publications: 7

Yejun Xu

Yejun Xu

Hohai University

Publications: 6

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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