In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automa...

|Two training algorithms for self evolving neural networks are discussed for rule based data analysis. E cient classi cation is achieved with less number of automatically added clusters and application data is analysed by interpreting the trained neural network as a fuzzy rule based system. Learning Vector Quantisation algorithm has been modied acquiring the self evolvement character in the pro...

The fuzzy and neuro fuzzy systems have been successfully used to solve problems in various fields such as medicine, manufacturing, control, agriculture and academic applications. In recent decades, neural networks have been used to the identification, assessment and diagnosis of diseases. In this thesis we performed a comparative study among fuzzy neural networks (ANFIS), multilayer perceptron ...

We propose Adaptive Fuzzy Neural Trees as an appropriate tool for intelligent data analysis, comprehension , and prediction. Instead of using a single technique Adaptive Fuzzy Neural Trees as a mixture of paradigms combine the main advantages of neural networks, decision trees, and fuzzy logic. Like neural networks they are able to model smooth functions and can be adapted incrementally. Like d...