Data clustering is a recognized data analysis method in data mining whereas K-Means is the well known partitional clustering method, possessing pleasant features. We observed that, K-Means and other partitional clustering techniques suffer from several limitations such as initial cluster centre selection, preknowledge of number of clusters, dead unit problem, multiple cluster membership and pre...

There is an increasing interest in modeling groundwater contamination, particularly geogenic contaminant, on a large scale both from the researcher’s as well as policy maker’s point of view. However, modeling large scale groundwater contamination is very challenging due to the incomplete understanding of geochemical and hydrological processes in the aquifer. Despite the incomplete understanding...

A precise predictive model is important for obtaining a clear understanding of the changes in dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved oxygen content is fundamental to reduce risk, and three-dimensional prediction can provide more accurate results and overall guidance. In this study, a hybrid three-dimensional (3D) dissolved oxygen content predic...

This paper presents a tool condition monitoring approach using Takagi-Sugeno-Kang (TSK) fuzzy logic incorporating a subtractive clustering method. The experimental results show its effectiveness and satisfactory comparisons with several other artificial intelligence methods.

a r t i c l e i n f o Keywords: Subtractive clustering Adaptive network-based fuzzy inference system Technical indicators Adaptive learning Genetic algorithm Technical analysis is one of the useful forecasting methods to predict the future stock prices. For professional stock analysts and fund managers, how to select necessary technical indicators to forecast stock trends is important. Traditio...

Three Phase Induction motor is the major running part in the Industries and is the most used electrical machines. Hence detection of faults in the motor is very important in order to improve the performance of the induction motor, avoid the production lost and also to reduce the operational costs. The methods used for this process is mainly based on measuring and analyzing the vibration and cur...

This paper summarizes work undertaken in the area of modeling Shape Memory Alloy (SMA) and airfoil hysteresis using a Sugeno-type fuzzy modeling approach based on subtractive clustering. Two alternative approaches to develop a fuzzy model for hysteresis are proposed and evaluated. The first consists in building a mirror image of the lower curve in order to model both curves concurrently and the...

Intrusion Detection System (IDS) provides additional security for the most vulnerable Mobile Adhoc Networks (MANET). Use of Fuzzy Inference System (FIS) in the design of IDS is proven to be efficient in detecting routing attacks in MANETs. Clustering is a vital means in the detection process of FIS based hybrid IDS. This study describes the design of such a system to detect black hole attack in...