Decision Analysis Methods Combining Quantitative Logic and Fuzzy Soft Sets
| Autor: | Jialu Zhang, Xia Wu, Ruhua Lu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Computational intelligence 02 engineering and technology Decision rule computer.software_genre Logical connective Theoretical Computer Science Credit card Computational Theory and Mathematics Artificial Intelligence Metric (mathematics) Formal language 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining Rough set computer Software Decision analysis |
| Zdroj: | International Journal of Fuzzy Systems. 22:1801-1814 |
| ISSN: | 2199-3211 1562-2479 |
| DOI: | 10.1007/s40815-020-00899-6 |
| Popis: | In this paper we propose a new decision analysis method combining quantitative logic and fuzzy soft set theory. Firstly, we transform a fuzzy information system into a fuzzy soft set, and then establish a formal language based on the fuzzy soft set, in which the parameters of fuzzy soft set are regarded as atomic formulas, some atomic formulas are connected by the logical connectives and then a logical formula is formed, and a implicative type of formula is interpreted as a soft decision rule (SDR). Secondly, various types of measures to evaluate the SDR are introduced and then the soft metric between two logical formulas is established. Thirdly, we apply the soft metric to the soft decision analysis, a SDR extraction algorithm for fuzzy decision information system and a corresponding recommendation algorithm are proposed. Finally, some attribute analysis examples, including the example as shown in rough sets and the practical credit card application example, are given to illustrate the newly proposed method and related concepts. |
| Databáze: | OpenAIRE |
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