International Journal of the Computer, the Internet and Management
نویسنده
چکیده
Model validation is an important step in system identification process. However, theoretical derivation of model validity tests for neural network such as RBF network is very complicated. The current study, investigate the capability of some of the model validity tests that are widely been used namely one step ahead prediction, model predicted output, means square error and correlation tests. This paper also explores the appropriateness of these validity tests to provide some inside information about network model deficiencies.
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