Modeling Complex And Dynamic Real Life Scenario

Foo, Ming Yee (2013) Modeling Complex And Dynamic Real Life Scenario. Project Report. UTeM, Melaka. (Submitted)

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Abstract

Soft computing model is replacing conventional mathematical models. In this research, soft computation discovers the causal relationship exists among the factors within a closed system. The strength of relationship between factor A and factor B could be expressed in form of weights in artificial neural network. Soft computing models come into sight because there are challenges to solve complex and dynamic problems. The troubles to solve these problems are mainly involving bulky computation and time consuming. Besides, it is difficult to seek unbiased expert’s advice. Instead of performing mathematical calculations, artificial neural network model such as fuzzy cognitive map (FCM) could realistically mimic the system. FCM tuned the weights of all relationship within a system independently through learning. An algorithm based on perceptron is applied in FCM learning process. MATLAB is the software used to build the FCM model. The comparison of computation time and the accuracy of the output results are done. The more input data, the more FCM behaves similarly to the real system. A case study is chosen to validate the FCM model. Future research could explore more on the algorithm used on FCM model to achieve shorter computation time along with higher accuracy.

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