@inproceedings{93ed2d3ca0044b9a895244eb5c5a51c5,
title = "Factor space is the adaptive and deepening theory of fuzzy sets",
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.",
keywords = "Aerospace electronics, Artificial intelligence, Fuzzy sets, Probability distribution, Random variables, Shape, factor space, fuzzy sets, power of sets, falling shadow, probability, random sets",
author = "Haitao Liu and Runjun Wan and Shanshan Xue and Tiantian Wang and Sizong Guo and Jing He",
note = "Funding Information: ACKNOWLEDGMENT Special thanks and respects to Professor P. Z. Wang for his guidance and suggestions for this paper. And many thanks to Prof. H. X. Li and Prof. Y. Shi for their supports. This work was supported by the grant (Grant Nos. 61350003) from the Natural science Foundation of China, and the grants (Grant Nos. L2014133, LJ2019JL019) from the department of education of Liaoning Province. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), FUZZ-IEEE ; Conference date: 19-07-2020 Through 24-07-2020",
year = "2020",
month = jul,
day = "24",
doi = "10.1109/FUZZ48607.2020.9177855",
language = "English",
isbn = "978-1-7281-6933-0",
series = "IEEE International Conference on Fuzzy Systems",
publisher = "IEEE",
number = "22254",
pages = "1--8",
booktitle = "2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",
address = "United States",
}