Unlike to traditional hierarchical and partitional clustering algorithms which always fail to deal with very large databases, a neural network architecture, Projective Adaptive Resonance Theory (PART), is developed for the high dimensional space clustering. However, the success of the PART algorithm depends on both accurate parameters and satisfied orders of input data sets. These disadvantages...

This work is motivated by the following question: given a sample of compositional data trajectories (i.e. sequences of composition measurements along a domain), how can one propose a segmentation procedure leading to homogeneous classes? In other words, our contribution aims at studying statistical methods suited for clustering compositional data, when the observations are constituted by trajec...

Image segmentation is very useful in lesion segmentation which is needed for monitoring and quantifying Lesion. Automated lesion segmentation in CT/MRI poses many challenges with regard to characteristics of an image. Many techniques are involved to detect the lesion in the medical images such watershed, wavelet transform etc. In this paper, we are defining the modified k means cluster to segme...

The liberalization of electricity markets has been resulted in the emergence new players, increasing competitiveness markets, standing those can provide better services for prices. knowledge energy consumers’ profile an important tool to help players make decisions electrical sectors. In this paper, a characterization model typical load curves Low Voltage (LV) customers is proposed and evaluate...

Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. In Bag of words representation of documents the words that appear in documents often have many morphological variants and in most cases, morphological variants of words have similar semantic interpretati...

Partitional clustering of categorical data is normally performed by using K-modes clustering algorithm, which works well for large datasets. Even though the design and implementation of K-modes algorithm is simple and efficient, it has the pitfall of randomly choosing the initial cluster centers for invoking every new execution that may lead to non-repeatable clustering results. This paper addr...

In this paper, a stochastic connectionist approach is proposed for solving function optimization problems with real-valued parameters. With the assumption of increased processing capability of a node in the connectionist network, we show how a broader class of problems can be solved. As the proposed approach is a stochastic search technique, it avoids getting stuck in local optima. Robustness o...

The tree of life is currently an active object of research, though next to vertical gene transmission non vertical gene transfers proved to play a significant role in the evolutionary process. To overcome this difficulty, trees of life are now constructed from genes hypothesized vital, on the assumption that these are all transmitted vertically. This view has been challenged. As a frame for thi...