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 38 Citations 6,060 217 World Ranking 4965 National Ranking 464

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 Rough set, Artificial intelligence, Data mining, Pattern recognition and Algorithm. His Rough set research includes themes of Discrete mathematics, Structure and Reduction. His Artificial intelligence study frequently involves adjacent topics like Machine learning.

His Data mining research incorporates elements of Fuzzy set operations, Type-2 fuzzy sets and systems, Membership function, Defuzzification and Fuzzy logic. As part of the same scientific family, Duoqian Miao usually focuses on Pattern recognition, concentrating on Automatic image annotation and intersecting with Semantic gap, Statistical classification and Class. His studies in Algorithm integrate themes in fields like Granular computing, Complete graph and Spanning tree.

His most cited work include:

  • A rough set approach to feature selection based on ant colony optimization (222 citations)
  • From soft sets to information systems (208 citations)
  • Best basis-based wavelet packet entropy feature extraction and hierarchical EEG classification for epileptic detection (208 citations)

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

Artificial intelligence, Rough set, Pattern recognition, Data mining and Algorithm are his primary areas of study. His research integrates issues of Machine learning and Computer vision in his study of Artificial intelligence. Rough set is often connected to Reduction in his work.

His work on Discriminative model, Feature selection, Linear discriminant analysis and Dimensionality reduction as part of general Pattern recognition study is frequently connected to Metric, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Data mining research incorporates themes from Representation, Cluster analysis, Feature vector, Type-2 fuzzy sets and systems and Fuzzy logic. In general Algorithm, his work in Computation is often linked to Information system linking many areas of study.

He most often published in these fields:

  • Artificial intelligence (51.54%)
  • Rough set (48.46%)
  • Pattern recognition (29.62%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (51.54%)
  • Rough set (48.46%)
  • Three way (8.85%)

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

Duoqian Miao mostly deals with Artificial intelligence, Rough set, Three way, Pattern recognition and Machine learning. He combines subjects such as Relation and Algorithm, Reduction with his study of Rough set. His biological study spans a wide range of topics, including Incremental learning and Multi-label classification.

His work on Feature extraction and Discriminative model as part of general Pattern recognition research is often related to Metric, thus linking different fields of science. His Machine learning research is multidisciplinary, incorporating perspectives in Exploit and Data set. He interconnects Multi label learning and Cluster analysis in the investigation of issues within Data mining.

Between 2018 and 2021, his most popular works were:

  • Three-Way Group Conflict Analysis Based on Pythagorean Fuzzy Set Theory (40 citations)
  • Three-way enhanced convolutional neural networks for sentence-level sentiment classification (38 citations)
  • Three-way enhanced convolutional neural networks for sentence-level sentiment classification (38 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

His scientific interests lie mostly in Artificial intelligence, Three way, Pattern recognition, Benchmark and Fuzzy logic. His research on Artificial intelligence often connects related areas such as Machine learning. His biological study spans a wide range of topics, including Object, Salient and Image retrieval.

The concepts of his Fuzzy logic study are interwoven with issues in Algorithm and Uncertain data, Data mining, Data classification. Duoqian Miao interconnects Relation, Rough set and Cluster analysis in the investigation of issues within Fuzzy set. Duoqian Miao performs multidisciplinary study in the fields of Rough set and Conflict analysis via his papers.

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

From soft sets to information systems

Daowu Pei;Duoqian Miao.
granular computing (2005)

536 Citations

A rough set approach to feature selection based on ant colony optimization

Yumin Chen;Duoqian Miao;Ruizhi Wang.
Pattern Recognition Letters (2010)

303 Citations

Best basis-based wavelet packet entropy feature extraction and hierarchical EEG classification for epileptic detection

Deng Wang;Duoqian Miao;Chen Xie.
Expert Systems With Applications (2011)

291 Citations

Analysis on attribute reduction strategies of rough set

Jue Wang;Duoqian Miao.
Journal of Computer Science and Technology (1998)

204 Citations

Relative reducts in consistent and inconsistent decision tables of the Pawlak rough set model

D. Q. Miao;Y. Zhao;Y. Y. Yao;H. X. Li.
Information Sciences (2009)

204 Citations

A graph-theoretical clustering method based on two rounds of minimum spanning trees

Caiming Zhong;Duoqian Miao;Ruizhi Wang.
Pattern Recognition (2010)

137 Citations

Rough Cluster Quality Index Based on Decision Theory

P. Lingras;Min Chen;Duoqian Miao.
IEEE Transactions on Knowledge and Data Engineering (2009)

123 Citations

Constructive methods of rough approximation operators and multigranulation rough sets

Xiaohong Zhang;Duoqian Miao;Caihui Liu;Meilong Le.
Knowledge Based Systems (2016)

117 Citations

Hybrid approaches to attribute reduction based on indiscernibility and discernibility relation

J. Qian;D. Q. Miao;Z. H. Zhang;W. Li.
International Journal of Approximate Reasoning (2011)

115 Citations

A rough set approach to feature selection based on power set tree

Yumin Chen;Duoqian Miao;Ruizhi Wang;Keshou Wu.
Knowledge Based Systems (2011)

110 Citations

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Best Scientists Citing Duoqian Miao

Yiyu Yao

Yiyu Yao

University of Regina

Publications: 51

Guoyin Wang

Guoyin Wang

Chongqing University of Posts and Telecommunications

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Tianrui Li

Tianrui Li

Southwest Jiaotong University

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Witold Pedrycz

Witold Pedrycz

University of Alberta

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Hamido Fujita

Hamido Fujita

Association for Computing Machinery

Publications: 37

Dun Liu

Dun Liu

Southwest Jiaotong University

Publications: 32

Xibei Yang

Xibei Yang

Jiangsu University

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Aboul Ella Hassanien

Aboul Ella Hassanien

Cairo University

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Jianming Zhan

Jianming Zhan

Minzu University of China

Publications: 25

Qinghua Hu

Qinghua Hu

Tianjin University

Publications: 24

Yuhua Qian

Yuhua Qian

Shanxi University

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Pawan Lingras

Pawan Lingras

Saint Mary's University

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Jiye Liang

Jiye Liang

Shanxi University

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Yingxu Wang

Yingxu Wang

University of Calgary

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Degang Chen

Degang Chen

North China Electric Power University

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Zhihui Lai

Zhihui Lai

Shenzhen University

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