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177 articles for “selection algorithm”
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Research ArticleOpen accessPhrase in the titleHYBRID FEATURE SELECTION ALGORITHM FOR INTRUSION DETECTION SYSTEMSeyed Reza Hasani, Zulaiha Ali Othman, Seyed Mostafa Mousavi KahakiNetwork security is a serious global concern. Usefulness Intrusion Detection Systems (IDS) are increasing incredibly in Information Security research using Soft computing techniques. In the previous researches having irrelevant and redundant features are recognized causes of increasing the processing speed of evaluating the known intrusive patterns. In addition, an efficient feature selection method eliminates dimension of data and reduce redundancy … …Journal of Computer Science, Vol. 10, Issue 6 · 31 Jan 2014 · 7,350 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Gene Selection Algorithm using Bayesian Classification ApproachAlok Sharma, Kuldip K. PaliwalIn this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using gene expression profiles. Approach: The feature selection … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,307 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePerformance Analysis of Resource Selection Algorithms in Grid Computing EnvironmentMalarvizhi Nandagopal, Rhymend UthariarajProblem statement: Meta- scheduling has become important due to increased number of jobs and resources in the area of grid computing to achieve the objectives of grid users and grid resources. Approach: A variety of factors need to be considered for effective scheduling of resources in such environments such as total time job spend in the grid system, global and … …Journal of Computer Science, Vol. 7, Issue 4 · 4 Apr 2011 · 6,899 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleOptimizing Cluster Head Selection Algorithms to Improve Power Efficiency in Agricultural Wireless Sensor NetworksSaed TarapiahThe current research addresses the management of Wireless Sensor Networks (WSNs) with a focus on optimizing power consumption, a critical concern in current research. The study uses agricultural WSNs to monitor farming areas, aiming to enhance decision-making in farm management. The importance of such monitoring systems in the region is emphasized. Previous research highlights clustering as an effective technique for … …Journal of Computer Science, Vol. 21, Issue 4 · 3 Mar 2025 · 4,940 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Novel Distinguishability Based Weighted Feature Selection Algorithms for Improved Classification of Gene Microarray DatasetJ. Jeyachidra, M. PunithavalliData mining played vital role in comprehending, analyzing, understanding and interpreting microarray technology expression data. That includes search for genes that had similar or correlated patterns of expression. For that, the feature selection was one of the frequently used important techniques for data preprocessing. Many feature selection algorithms had been developed. Yet the persisting problem was in selecting optimal subset … …Journal of Computer Science, Vol. 11, Issue 2 · 2 Feb 2015 · 6,376 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSingle Pass Seed Selection Algorithm for k-MeansK. Karteeka Pavan, Allam Appa Rao, A.V. Dattatreya Rao, G. R. SridharProblem statement: The k-means method is one of the most widely used clustering techniques for various applications. However, the k-means often converges to local optimum and the result depends on the initial seeds. Inappropriate choice of initial seeds may yield poor results. k-means++ is a way of initializing k-means by choosing initial seeds with specific probabilities. Due to the random … …Journal of Computer Science, Vol. 6, Issue 1 · 31 Jan 2010 · 7,541 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSwarm Negative Selection Algorithm for Electroencephalogram Signals ClassificationNasser Omer Sahel Ba-Karait, Siti Mariyam Shamsuddin, Rubita SudirmanProblem statement: The process of epilepsy diagnosis from EEG signals by a human scorer is a very time consuming and costly task considering the large number of epileptic patients admitted to the hospitals and the large amount of data needs to be scored. Therefore, there is a strong need to automate this process. Such automated systems must rely on robust … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 7,205 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimized Feature Selection for Kidney Ultrasound Image Classification Using Binary Coati Weighted Mean Vector AlgorithmFizhan Kausar, Ramamurthy B.The analysis of medical images presents many challenges, especially when making precise diagnoses. In pediatric Chronic Kidney Disease (CKD), early identification is critical because of its gradual progression to significant kidney failure. This study proposes a diagnostic framework for pediatric ultrasound image classification that incorporated machine learning and advanced feature selection methods. This approach is divided into four stages: Preprocessing, … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,563 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleGenetic Algorithm for Variable and Samples Selection in Multivariate Calibration ProblemsKelton de Souza Santiago, Anderson Silva Soares, Telma Woerle de Lima et al.One of the main problems of quantitative analytical chemistry is to estimate the concentration of one or more species from the values of certain physicochemical properties of the system of interest. For this it is necessary to construct a calibration model, i.e., to determine the relationship between measured properties and concentrations. The multivariate calibration is one of the most successful … …Journal of Computer Science, Vol. 11, Issue 4 · 8 Jun 2015 · 7,381 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFeature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector MachinesSandra Johnson, Valli ShanmugamProblem statement: All compilers have simple profiling-based heuristics to identify and predict program hot methods and also to make optimization decisions. The major challenge in the profile-based optimization is addressing the problem of overhead. The aim of this work is to perform feature subset selection using Genetic Algorithms (GA) to improve and refine the machine learnt static hot method predictive … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,234 accessesView PDFCite