Approximate reasoning with fuzzy soft set

In this work, we develop a reasoning mechanism under uncertainty for a typical class of decision making problems based on the theory of fuzzy soft set. Accordingly, we consider a logic of fuzzy soft sets. In the sequel, implication operations dealing with fuzzy soft sets over different universal sets and different sets of parameters have been studied extensively. An algorithm for rule based reasoning has been developed for a modus ponens type rule of inference using the proposed logical structure. The entire proposal is illustrated with an example. Results of application of our proposed inference are compared with those obtained by Mondal and Raha on the problem of management of hypertension using a medical diagnostic support system.

Automated summary

In this study, a reasoning mechanism under uncertainty for decision making problems based on fuzzy soft set theory was developed. A logic of fuzzy soft sets was considered, and implication operations dealing with fuzzy soft sets over different universal sets and parameters were extensively studied. An algorithm for rule based reasoning was developed, and the proposed inference was compared with results from another study on managing hypertension using a medical diagnostic support system.