Data clustering is a key technique in the field of data mining, pattern recognition, bioinformatics and machine learning which concerns the organization and unexplored relationship between the huge amounts of data. It can analyse the data without knowing the size and distribution. Thus, this paper presents a new approach based on the charged system search (CSS) with chaotic map for partition cl...

In pattern recognition, clustering is a powerful technique that can be used to find the identical group of objects from a given dataset. It has proven its importance in various domains such as bioinformatics, machine learning, pattern recognition, document clustering, and so on. But, in clustering, it is difficult to determine the optimal cluster centers in a given set of data. So, in this pape...

in this paper, an algorithm is presented for the formation of optimal null basis vectors corresponding to sparse flexibility matrices. for controlling the independence of the vectors, a generator is selected in each corresponding self-equilibrating systems, and the sequence of generators is modeled as decision variables. since the equilibrium conditions and uniqueness of generators consists a u...

Classifier subset selection (CSS) from a large ensemble is an effective way to design multiple classifier systems (MCSs). Given a validation dataset and a selection criterion, the task of CSS is reduced to searching the space of classifier subsets to find the optimal subset. This study investigates the search efficiency of genetic algorithm (GA) and sequential search methods for CSS. In experim...

the main aim of this paper is to find the optimum shape of arch dams subjected to multiple natural frequency constraints by using an efficient methodology. the optimization is carried out by charged system search algorithm and its enhanced version. computing the natural frequencies by finite element analysis (fea) during the optimization process is time consuming. in order to reduce the computa...

A number of risk-group stratification or staging systems have been found useful at stratifying patients with differentiated thyroid carcinoma into risk groups. Those identified as high risk could be subjected to more aggressive treatment, while those at low risk could be spared of such treatment. However, the best stratification system in patients with follicular thyroid carcinoma (FTC) remains...

Identifying semantic expressions (so-called concept strings (CSs)) in multilingual corpora is an important NLP task, as it allows web search engines to define and perform semantic queries over large collection of documents. Existing web search engines in the legal domain are mainly limited to keyword search, in which the query word is matched against the textual content of the documents. This p...

Shape retrieval programs are comprised of two components: shape representation, and matching algorithm. Building the representation on scale space filtering and the curvature function of a closed boundary curve, curvature scale space (CSS) has been demonstrated to be a robust 2D shape representation. The adoption of the CSS image as the default in the MPEG-7 standard, using a matching algorithm...