International Journal of Computational Intelligence Systems (Jan 2017)

A Linguistic-Valued Approximate Reasoning Approach for Financial Decision Making

  • Xin Liu,
  • Ying Wang,
  • Xiaonan Li,
  • Li Zou

DOI
https://doi.org/10.2991/ijcis.2017.10.1.21
Journal volume & issue
Vol. 10, no. 1

Abstract

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In order to process the linguistic-valued information with uncertainty in the financial decision- making, the present work uses a lattice-valued logical algebra - lattice implication algebra to deal with both comparable and incomparable linguistic truth-values. A new personal financial decision auxiliary modeling framework based on the lattice-ordered linguistic truth-valued logic is proposed. The concepts of linguistic-valued similarity and linguistic valued degree assignment function are introduced, and then a linguistic-valued approximate reasoning approach for financial decision making is presented. A case study is then provided which illustrates that the proposed approach is more flexible and effective with handling the financial decision-making problem involved with linguistic-valued information with uncertainty.

Keywords