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  • 标题:Double-layer Modificatory Linguistic Truth-value Lattice-valued Evaluation Method
  • 本地全文:下载
  • 作者:Dan Meng ; Xu Huang ; Zaiqiang Zhang, Yang,Xu
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2006
  • 卷号:6
  • 期号:9A
  • 页码:167-174
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:In this paper, a double-layer modificatory linguistic truth-value lattice-valued evaluation method is presented. Its logic basic is based on modificatory linguistic truth-value lattice-valued proposition logic system MLTVLP(X) and operator modificatory linguistic truth-value lattice-valued proposition logic OMLTVLP(X). MLTVLP(X) and OMLTVLP(X) are similar to LTVLP(X) and MLTVLP(X), which have been given in our previous research paper. But they have different valuation field, i.e. different type of Lattice Implication Algebra. It is an attempt to solve the double-layer evaluation problem with incomparable linguistic qualitative information. In this evaluation method, every valuator can specify a modificatory linguistic truth-value for every sub-criterion. Likewise, different valuator can be endowed with different importance according to their different background, knowledge or experience. Moreover, different valuator can specify different weight for every sub-criterion according to their experience or preference. All different importance is aggregated to the final evaluation result. It is shown that incomparable linguistic information can be dealt with in this evaluation method.
  • 关键词:Artificial Intelligence, Lattice Implication Algebra, Lattice-valued Logic system, Double-layer Evaluation Method with Linguistic Truth-value
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