Parameters of GFSSAM: coding the parameters of a hybrid genetic fuzzy system

Context-driven systems provide information and/or services to the user and have specific features: a vaguely defined range of variables, contextual model, and context-sensitive services. This paper is focused on coding the parameters of a hybrid genetic fuzzy system that is designed to use a genetic algorithm for optimizing the knowledge base of a previously created fuzzy system. The hybrid context-driven rule-based system (GFSSAM=Genetic Fuzzy Software System for Asset Management) is a real-time software system for supporting the decision process in managing investment assets. In the investment process stakeholders analyse, model, use raw data, and make decisions in which the perspective context plays a key role and so any software system in this area has to provide reliable context-aware results. GFSSAM is developed and tested on real-time data from the stock exchange in a project for extensive research on optimization of the inference machine and knowledge base of a fuzzy system through hybridization.

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