| Summary: | 碩士 === 東海大學 === 工業工程與經營資訊學系 === 98 === In this study the level two chaotic systems and fuzzy chaotic systems are presented based on the chaotic systems. Traditional chaotic systems can be observed that may be incomplete to illustrate the real world phenomena due to that variable and parameters may belong to uncertain factors. It is more beneficial if the chaotic systems are extended to deal with also imprecise information or vague parameters and variables. The evaluations with the level two or termed chaoticized chaotic and fuzzy arithmetic operations may provide more insightful information regarding the uncertainties of the world for the decision makers.
The complexity of the level two chaotic systems stems from the parameter value which is generated by the chaotic systems as well. And therefore for these systems, we will also investigate the internal diversification phenomenon of initial conditions as well. Especially, the system characteristics for convergence and divergence and system range from the initial condition.
On the other hand, the complexity of the fuzzy chaotic systems is from the interaction of the parameters and variables in the chaotic systems. In this study two methods are presented: fuzzy chaos and chaotic fuzzy interval. For that, we will investigate system diversification form the parameter and the variable. Also, the two methods are examined here in detail with two types of fuzzy arithmetic, -cut fuzzy arithmetic and weakest t-norm T operator.
Moreover, it is found in this study that the level two chaotic system have lost the phenomenon of traditional chaotic systems. And in fuzzy chaotic systems, initial values may have more influence on the system than the parameter values. The system phenomena are consistent with business or social phenomena.
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