[1]ZHAO Keqin.Application overview of set pair analysis in intelligent prediction system[J].CAAI Transactions on Intelligent Systems,2022,17(2):233-247.[doi:10.11992/tis.202103023]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
17
Number of periods:
2022 2
Page number:
233-247
Column:
综述
Public date:
2022-03-05
- Title:
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Application overview of set pair analysis in intelligent prediction system
- Author(s):
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ZHAO Keqin
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Institution of Zhuji Connection Mathematics, Zhuji 311800, China
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- Keywords:
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set pair analysis; system intelligent prediction; prediction model; data structure; cluster; dynamic optimization; connection number; uncertainty analysis; information ability
- CLC:
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TP311
- DOI:
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10.11992/tis.202103023
- Abstract:
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Preparedness ensures success, whereas unpreparedness spells failure. However, predictions are subject to uncertainty. Accordingly, this paper summarizes the application of set pair analysis theory (SPAT) in weather and precipitation forecast, sandstorm forecast, hydrology, water resources; water supply; and demand forecast, electric power and energy forecast, geological disaster forecast, civil aviation risk and accident forecast, crop yield forecast, cerebral forecast, and social economy forecast. The basic steps of intelligent prediction system modeling based on SPAT are summarized into three steps: First, a set pair is constructed; all the relationships between two sets in the set pair, including relationships that are defined and not defined, are analyzed; and proper connection numbers are selected as the characteristic function according to the relationships. Second, a prediction model based on connection numbers is established, including improving and perfecting the existing prediction models using the connection numbers. Third, a prediction or forecast is made using the calculation of the model and uncertainty analysis around the model (being the key part), including retrospective and real-time predictions under current scenarios. By doing so, the prediction accuracy is guaranteed and enhanced; thus, an effective new way toward intelligent prediction of uncertain systems is opened.