Factor space is the adaptive and deepening theory of fuzzy sets

Haitao Liu, Runjun Wan, Shanshan Xue, Tiantian Wang, Sizong Guo, Jing He

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

In recent years, the factor space theory has been promoted gradually as math foundation for mechanistic artificial intelligence theory. The theory was put forward in 1982 by Prof. P Z Wang, he took the fundamental space Ω in probability and the universe U of fuzzy sets both as factor spaces, but put Ω in the sky 2U=P(U). The established fuzzy shadow theory says that the membership function on the ground is the coverage of random set in the sky, and had proved the Existence and Uniqueness Theorem on the correspondence between earth and heaven. This theory points out that the adaptive platform of intelligent description and subjective measurement is the factor space; and the core transform in between different levels is the power mapping (falling shadow). This is the mathematical secret of artificial intelligence, but also the direction of further improvement of fuzzy sets and systems.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
PublisherIEEE Xplore
Pages1-8
Number of pages8
ISBN (Print)978-1-7281-6933-0
DOIs
Publication statusPublished - 24 Jul 2020
Event2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) - Glasgow, United Kingdom
Duration: 19 Jul 202024 Jul 2020

Conference

Conference2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Abbreviated titleFUZZ-IEEE
Country/TerritoryUnited Kingdom
CityGlasgow
Period19/07/2024/07/20

Keywords

  • Probability distribution
  • Fuzzy sets
  • Random variables
  • Shape
  • Artificial intelligence
  • Aerospace electronics

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