Based-on Euclidean Distance Method for Improving the Classification Errors of Artificial Neural Networks
Dong Jin Ji · Mini-micro Systems · 2004
Described a topology and an algorithm of Probabilistic Neural Networks. The dot product, growing vector, growing factor and other terms had been defined, their characters were studied. A method to improve the accuracy of Probabilistic Neural Networks was proposed. In the simulation experiment, the algorithm of PNN can not recognize the cement strength testing samples perfectly, the proposed algorithm can identify the cement strength testing samples perfectly, the recognition rate is 100%. The simulating result showed that the method is feasible and efficient.