Innovative Concepts of Fuzzy logic which Improve the Human and Organizational Capabilities

Abstract

This thesis has been realized following a design science approach, it therefore aims at first creating innovative concepts which improve the actual human and organizational capabilities, secondly, at evaluating these concepts by providing concrete instantiations. According to this research paradigm, the objectives of this thesis are the following: The first objective of this thesis is to extend the querying ability of the fuzzy classification approach proposed by Schindler. By adding new clauses to the fuzzy Classification Query Language, the user should be given more powerful means for selecting elements within a fuzzy classification. The second objective of this thesis is convert classical value to fuzzy value which base on fuzzy membership function such as S shape membership function, Pi shape membership function and Z shape membership junction. The third objective is, considering the application domain specificities, to extend the original fuzzy queries approach by new concepts which provide additional capabilities to the system and proved that the proposed intelligent fuzzy query is faster than the conventional query and it provides the user the flexibility to query the database using natural language. The fourth and last objective is to also make a comparison between traditional database and fuzzy database by computing the time cost of classical query over classical database, fuzzy query over classical database and fuzzy query over fuzzy database.