Placer, JohnJeck, Steven2012-05-202013-07-012012http://hdl.handle.net/10342/3898Fuzzy rules have been used to model complex human behavior in order to develop sophisticated industrial control systems. The use of fuzzy rules to create a behavioral model provides a quantitative basis for discussing the contribution of elements of the model to theories about the behavior. The application of a protocol and tool simplifies the development of a behavioral model from observational data. Extraction of a high level, linguistic behavioral model from the observational data is used to discover knowledge about the data. Tuning of the model is accomplished by parameter optimization through the adjustment of membership functions using the genetic fuzzy, self-adaptive system. A case study demonstrating the use of the protocol and tool is presented. In the study, a behavioral model is developed that integrates the analysis of the observational data with Social Network Analysis. The integrated behavioral model provides an effective platform for a quantitative analysis of the activities impacting behavior.  64 p.dissertations, academicArtificial intelligenceComputer scienceComputer engineeringFuzzy rule based systemGenetic algorithmGenetic fuzzy systemsLinguistic modelSocial network analysisHuman behavior modelsData miningMaster's Thesis