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There are variety of methods available to solve multi-objective optimization problems, very few utilizes criterion linkage between data objects in the searching phase, to improve final result. This article proposes an evolutionary clustering algorithm for multi-objective optimization. This paper aims to identify more relevant features based on criterion knowledge from the given data sets and also...
There are variety of methods available to solve multi-objective optimization problems, very few utilizes criterion linkage between data objects in the searching phase, to improve final result. This article proposes an evolutionary clustering algorithm for multi-objective optimization. This paper aims to identify more relevant features based on criterion knowledge from the given data sets and also...
Data mining is one of the most significant research area in computer science. It is a calculation process of finding and determining valuable information from huge data set. Image classification is an important technique to generate valuable information. The classification method provides the accurate result in their target class. This review compares the some predominant hybrid classification algorithms...
Data mining is the method of extracting the valuable systematic information from huge databases. Image classification has constantly been a vital task for several applications such as remote sensing medical field, pattern recognition. It converses to the task of removing information classes from a multiband raster image. The resolving of the classification method is to classify all pixels in a one...
Video compression is the contemporary coding techniques to reduce redundancy in raw video. This paper addresses the various visual quality metrics, in the digital image processing such as PSNR, MSE, and VQM. The encoder is used to convert the source data into compressed bytes. The decoder decodes the compression form into its original video sequence. Data compression is achieved by removing redundancy...
The selection of an appropriate web service from the Internet is a great challenge for the web clients. It plays a vital role to choose the best, from different service providers offering the services with same functionalities. Mostly the web users may need certain service that needs to be combined with existing atomic services, termed as composite service. Many researchers have carried out their...
Supervised leaning classifier is usually constructing based on models through learning to achieve high accuracy. Support Vector Machine (SVM) is more useful classification technique in supervised learning model. In this paper, we examined SVM with linear kernel function and pre-computed kernel function using micro array data sets. In this observation is focused major three aspects such as accuracy,...
K-means algorithm is sensitive to the initial cluster centers and clustering results diverge with different initial input which in turn falls into local optimum. Genetic Algorithms are randomized searching technique which provides a better optimal solution for fitness function of an optimization problem. This paper proposes an enhanced K-means Genetic Algorithm for optimal clustering of data (EKMG)...
The recent development in the field of Web services technology has transformed the software industry radically by integrating a wide range of web users, vendors, and enterprise applications worldwide. There are various research initiatives made in Web services security which is an emerging trend in the field of Web services technology for the development of a large variety of enterprise applications...
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