— This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automati...
Juan E. Moreno, Oscar Castillo, Juan R. Castro, Lu...
It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining. In general, it is unre...
Abstract. This work presents a clustering method which can be applied to relational knowledge bases. Namely, it can be used to discover interesting groupings of semantically annota...
Abstract. Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular es...
A sensor's data loss or corruption, aka sensor data missing, is a common phenomenon in modern wireless sensor networks. It is more severe for multi-hop sensor network (MSN) a...
Le Gruenwald, Hanqing Yang, Md. Shiblee Sadik, Rah...