Fuzzy Neural Network Classification Model for Multi Labeled Electricity Consumption Data Set

Multi-level Hierarchical Fuzzy classification technique is significant classification model based on fuzzy membership value. The results of classification rules are obtained using MHFRB classification algorithm which has been used in Neural Networks technique for multi labelled data Classification. The proposed MHFRB classification algorithm is constructed on the improvement of a simple semantic Fuzzy Model in a hierarchical structure. The Fuzzy neural network classification model has been used to analysis the regional wise electricity consumption data for different multi labelled dataset. The results of the model provide the need of the electricity energy resources and accuracy of the classification model is considerably improved. Fuzzy Neural Networks technique is used to get a compact and accurate model at multiple levels. In this paper, the proposed methods are used to validate the Classification Model with the multi-label datasets and demonstrated that there is a considerable enhancement in performance when compared with the existing methods in the literature.