AN INTELLIGENT DECISION SUPPORT USING GENETIC FUZZY INTEGRATION FOR CAPABILITY ANALYSIS

Kunjal B. Mankad

Abstract


Soft Computing is a consortium of computing methodologies that provides a foundation for the conception, design, and deployment of intelligent systems to provide economical and feasible solutions with reduced complexity. Fuzzy Logic deals with uncertainty and imprecision for real world’s problems while Genetic Algorithm mimics natural evolution with robust search. The hybridization of Genetic-Fuzzy Systems is gaining popularity in handling real world problems in different domains. The paper focuses on education domain in order to identify human capabilities. Here, integrated genetic-fuzzy approach is utilized for evolving rules automatically. It discusses need of intelligent decision support, role of genetic-fuzzy hybridization with literature survey in various application domains, Theory of Multiple Intelligence and its types. The paper presents a novel architecture using genetic fuzzy techniques for intelligent decision support to classify human intelligence. Theory of Multiple Intelligence has been utilized for prototype implementation of the system. Result is presented in form of charts showing capabilities for different user categories.

Keywords- Genetic Fuzzy Systems (GFS), Soft Computing (SC) and Theory of Multiple Intelligence (MI).

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