Rchr
J-GLOBAL ID:200901028790721063   Update date: Apr. 01, 2024

UEHARA Kiyohiko

ウエハラ キヨヒコ | UEHARA Kiyohiko
Affiliation and department:
Job title: Associate Professor
Research field  (1): Control and systems engineering
Research keywords  (1): Fuzzy Inference
Papers (21):
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MISC (2):
  • 上原 清彦, 廣田 薫. Fuzzy Inference: Basic Methods and Their Extensions (Part 1). 日本知能情報ファジィ学会誌(解説). 2016. 28. 4. 107-112
  • 上原 清彦, 廣田 薫. Fuzzy Inference: Basic Methods and Their Extensions (Part 2). 日本知能情報ファジィ学会誌(解説). 2016. 28. 5. 141-148
Education (1):
  • - 1983 Ibaraki University Graduate School, Division of Engineering 電子工学専攻
Professional career (1):
  • Dr. Eng. (Tokyo Institute of Technology)
Committee career (28):
  • 2004/10 - 現在 Journal of Advanced Computational Intelligence and Intelligent Informatics, Editorial Board Member Editorial Board Member
  • 2021/06 - 2025/06 日本知能情報ファジィ学会 評議員
  • 2023/06 - 2023/11 The 8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII 2023) Program Committee Member
  • 2021/06 - 2023/06 日本知能ファジィ学会 広報委員
  • 2022/05 - 2022/09 The 10th International Symposium on Computational Intelligence and Industrial Applications (ISCIIA 2022) Program Committee Member
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Awards (9):
  • 2020/11 - ISCIIA2020 Session Best Presentation Award,(ISCIIA2020: The 9th International Symposium on Computational Intelligence and Industrial Applications) Independent Evaluations of Each Fuzzy Rule for Derivative-Free Optimization of Fuzzy Systems: Toward Fast Fuzzy-Rules Learning for Fuzzy Inputs
  • 2019/11/20 - JACIII Outstanding Reviewer Award 2019 (JACIII: Journal of Advanced Computational Intelligence and Intelligent Informatics)
  • 2019/11 - JACIII Outstanding Reviewer Award 2019,(JACIII: Journal of Advanced Computational Intelligence and Intelligent Informatics)
  • 2019/11 - IWACIII2019 Best Presentation Award (IWACIII2019: The 6th International Workshop on Advanced Computational Intelligence and Intelligent Informatics) Independent Evaluations of Each Fuzzy Rule for Derivative-Free Optimization of Fuzzy Systems: A Feasibility Study Toward Fast Fuzzy-Rule Learning
  • 2018/11 - ISCIIA&ITCA2018 Best Presentation Award,(ISCIIA2018: The 8th International Symposium on Computational Intelligence and Industrial Applications, ITCA2018: The 12th China-Japan International Workshop on Information Technology and Control Applications) Noise Reduction with Fuzzy Inference Based on Generalized Mean and Singleton Input-Output Rules: A Feasibility Study
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