Study of Artificial Neural Network Model Based on Fuzzy Clustering

During the application of artificial neural network, there is a question of how to deal with a great lot of the complicated sample set and the long time of training. The article proposes an artificial neural network model based on fuzzy clustering. Firstly, it clusters the training data into different sub-data using by fuzzy clustering model. Subsequently, it uses different artificial neural network to train the sub-data. Because of doing this, the number and complexity of training data by every artificial neural network is reduced and the efficiency of every artificial neural network is enhanced greatly. Lastly, the article uses the UCI´s databases to prove the utility of the new artificial neural network and gets the satisfied answers