Nonnegative matrix factorization method is a kind of new matrix rotting method. It is an effective tool for large data processing and analysis. At the same time, NMF has an important performance on in intellectual information processing and pattern recognition. We then aim for increasing an efficiency and accuracy of data clustering and classification based on NMF. NMF method is used to reduce ...

This article presents a study of academic performance evaluation using soft computing techniques inspired by the successful application of K-means, fuzzy C-means (FCM), subtractive clustering (SC), hybrid subtractive clustering-fuzzy C-means (SC-FCM) and hybrid subtractive clustering-adaptive neuro fuzzy inference system (SC-ANFIS) methods for solving academic performance evaluation problems. M...

Fuzzy C-means (FCM) is an important clustering algorithm with broad applications such as retail market data analysis, network monitoring, web usage mining, and stock prediction. Especially, parameters in FCM have influence on results. However, a lot of did not solve the problem, that is, how to set parameters. In this study, we present kind method for computing values according role process. Ne...

Intention recognition has significant applications in ambient intelligence, assisted living and care of the elderly, games and intrusion and other crime detection. In this chapter we explore an approach to intention recognition based on clustering. To this end we show how to map the intention recognition problem into a clustering problem. We then use three different clustering algorithms, Fuzzy...