within various classes. Different models of Crisp, Hierarchical, Overlapping and Fuzzy clustering algorithms have been developed which serve different purposes. The main deficiency that most of the algorithms face is that the number of clusters...

of the data set (X) via the prototypes (V). The separation measure is defined as the average value of the degrees of overlap of all possible pairs of fuzzy clusters in the system. The proposed index is tested and validated using several data sets. The results...

on the hybridization of soft computing paradigms in order to increase the efficiency of rainfall-runoff modeling. For doing that, the idea of fuzzy clustering is combined with feedforward neural networks for achieving a two-layer system, in which the first layer...

A New Hybrid Recommender System Using Dynamic Fuzzy Clustering...

and fuzzy clustering approaches. The experimental results demonstrate that the proposed fuzzy neural network algorithm is able to reveal a better performance than conventional back propagation NN and FCM algorithms....

Short-term load forecasting (STLF) plays a decisive role in electric power system operation and planning. Accurate load forecasting not only reduces the generation costs of power systems, but also serves to maximize profit ...