H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 117 Citations 68,295 1,584 World Ranking 58 National Ranking 3

Research.com Recognitions

Awards & Achievements

2013 - Fuzzy Systems Pioneer Award, IEEE Computational Intelligence Society

2013 - Izaak Walton Killam Memorial Prize, Canada Council

2012 - Fellow of the Royal Society of Canada Academy of Science

2009 - Polish Academy of Science

1999 - IEEE Fellow For the development of methodology, algorithms, and applications of fuzzy and neurofuzzy modeling and fuzzy control.

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 investigation include Artificial intelligence, Fuzzy set, Fuzzy logic, Data mining and Fuzzy classification. Witold Pedrycz has researched Artificial intelligence in several fields, including Machine learning and Pattern recognition. In his study, Data science and Optimization problem is inextricably linked to Granular computing, which falls within the broad field of Fuzzy set.

As part of one scientific family, Witold Pedrycz deals mainly with the area of Fuzzy logic, narrowing it down to issues related to the Group decision-making, and often Consistency. His work in Data mining covers topics such as Fuzzy clustering which are related to areas like Data structure. His Fuzzy classification research integrates issues from Fuzzy set operations and Neuro-fuzzy.

His most cited work include:

  • A fuzzy extension of Saaty's priority theory (2028 citations)
  • Fuzzy control and fuzzy systems (946 citations)
  • An introduction to fuzzy sets : analysis and design (914 citations)

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

His main research concerns Artificial intelligence, Fuzzy logic, Fuzzy set, Data mining and Cluster analysis. His research in Artificial intelligence intersects with topics in Machine learning and Pattern recognition. His study ties his expertise on Algorithm together with the subject of Fuzzy logic.

Witold Pedrycz focuses mostly in the field of Fuzzy set, narrowing it down to topics relating to Granular computing and, in certain cases, Granularity. Witold Pedrycz interconnects Defuzzification and Adaptive neuro fuzzy inference system in the investigation of issues within Neuro-fuzzy. His Fuzzy number research incorporates themes from Discrete mathematics and Membership function.

He most often published in these fields:

  • Artificial intelligence (63.87%)
  • Fuzzy logic (55.51%)
  • Fuzzy set (41.02%)

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

  • Fuzzy logic (55.51%)
  • Artificial intelligence (63.87%)
  • Data mining (36.22%)

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

His primary areas of investigation include Fuzzy logic, Artificial intelligence, Data mining, Cluster analysis and Fuzzy set. His Fuzzy logic research includes themes of Set, Group decision-making, Mathematical optimization and Interval. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Pattern recognition.

Witold Pedrycz has included themes like Granularity and Computational intelligence in his Data mining study. His Cluster analysis research is multidisciplinary, incorporating elements of Process and Series. In his research, Data science is intimately related to Granular computing, which falls under the overarching field of Fuzzy set.

Between 2017 and 2021, his most popular works were:

  • Fifty years of Information Sciences: A bibliometric overview (108 citations)
  • Fifty years of Information Sciences: A bibliometric overview (108 citations)
  • Fifty years of Information Sciences: A bibliometric overview (108 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Fuzzy logic, Artificial intelligence, Fuzzy set, Cluster analysis and Pattern recognition are his primary areas of study. Witold Pedrycz combines subjects such as Consistency, Mathematical optimization, Data mining and Process with his study of Fuzzy logic. The concepts of his Data mining study are interwoven with issues in Search tree, Fuzzy classification, Granularity and Time series.

His work deals with themes such as Machine learning and Selection, which intersect with Artificial intelligence. His Fuzzy set study integrates concerns from other disciplines, such as Semantics, Algorithm, Synthetic data, Series and Operations research. In his research on the topic of Cluster analysis, Pixel is strongly related with Segmentation.

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 fuzzy extension of Saaty's priority theory

P.J.M. van Laarhoven;W. Pedrycz.
Fuzzy Sets and Systems (1983)

3141 Citations

An introduction to fuzzy sets : analysis and design

Witold Pedrycz;Fernando Gomide.
(1998)

1774 Citations

Fuzzy control and fuzzy systems

Witold Pedrycz.
(1989)

1486 Citations

Face recognition

Keun-Chang Kwak;Witold Pedrycz.
Pattern Recognition Letters (2005)

1116 Citations

Granular computing: an introduction

W. Pedrycz.
joint ifsa world congress and nafips international conference (2001)

1064 Citations

Data Mining Methods for Knowledge Discovery

K.J. Cios;W. Pedrycz;R.M. Swiniarsk.
(1998)

888 Citations

Fuzzy Systems Engineering: Toward Human-Centric Computing

Witold Pedrycz;Fernando Gomide.
(2007)

888 Citations

Data Mining: A Knowledge Discovery Approach

Krzysztof J. Cios;Witold Pedrycz;Roman W. Swiniarski;Lukasz Andrzej Kurgan.
(2007)

880 Citations

Why triangular membership functions

Witold Pedrycz.
Fuzzy Sets and Systems (1994)

839 Citations

An identification algorithm in fuzzy relational systems

Witold Pedrycz.
Fuzzy Sets and Systems (1984)

824 Citations

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