论文信息 - Artificial Neural Nets and Genetic Algorithms

Artificial Neural Nets and Genetic Algorithms

Radial basis functions network (RBFN) is considered as a knowledge model. The model is established from a data 'set by leam'ing. For the performance assessment a novel model validation method is introduced. The method consists of sensitivity analysis integrated into a mathematicalbased technique known as analytical hierarchy process (AHP). It ranks the relative importance of factors being compared where the factors are the sensitivities in this case. The relative importance of the sensitivities is computed from the model and based on this information, the consistency of this information is tested by AHP. The degree of consistency is a measure of confidence for the validity of the model.

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