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Volume 46 Issue 2
Feb.  2024
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ZHAO Keqin. Some Applications and Progress of Set Pair Theory in Artificial Intelligence[J]. Journal of Electronics & Information Technology, 2024, 46(2): 383-407. doi: 10.11999/JEIT230889
Citation: ZHAO Keqin. Some Applications and Progress of Set Pair Theory in Artificial Intelligence[J]. Journal of Electronics & Information Technology, 2024, 46(2): 383-407. doi: 10.11999/JEIT230889

Some Applications and Progress of Set Pair Theory in Artificial Intelligence

doi: 10.11999/JEIT230889
Funds:  Project on Artificial Intelligence, Associated Institute of Mathematics, Zhuji (zjc202301)
  • Received Date: 2023-08-14
  • Rev Recd Date: 2023-12-08
  • Available Online: 2023-12-18
  • Publish Date: 2024-02-29
  • Set Pair Theory(SPT) regards the spacetime of things as a Deterministic Uncertainty(D-U) spacetime which is both definite and uncertain, treats certainty and uncertainty of things as a system of certainty and uncertainty, and “Objective recognition, systematic description, quantitative description, concrete analysis and practical test” of uncertainty, in the application of continuous development. After reviewing the source and property of Set Pair (SP) and its Connection Number (CN), the pairwise principles and uncertainty principle of set pair theory, the uncertainty system theory and the theory of similarities and differences, and the basic algorithms; some applications of set pair theory in intelligent definition, space data rapid evaluation and multi-radar signal sorting, intelligent prediction of complex systems, intelligent decision-making under uncertainty, connection digitalization of natural numbers and intelligent calculation of groups are summarized. This paper briefly introduces some progresses of set pair theory in the field of intelligent algorithm innovation, including the green intelligent computation involving the calculation of partial connection coefficient and the conservation of system energy of connection number, etc.. It is expected that the green intelligent algorithm based on “set-to-theory non-set-to-theory” integration will be more applied in the new generation of artificial intelligence.
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