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108 results for “Search Algorithms”
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Research ArticleOpen accessIn the abstractClassifying and Predicting Students’ Performance using Improved Decision Tree C4.5 in Higher Education InstitutesMohammed Hikmat Sadiq, Nawzat Sadiq AhmedStudents’ information in higher education institutions increases yearly. It is hard for them to extract meaningful information from the huge amount of data manually. Such information can support academic staff to stop students from dropping out at the end of courses. This can be done by evaluating the students’ performance for the course and also by predicting their performance in … …Journal of Computer Science, Vol. 15, Issue 9 · 12 Sep 2019 · 9,168 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Music Auto-Tagging with Convolutional Neural NetworksShaleen Bengani, S. Vadivel, J. Angel Arul JothiTechnology is revolutionizing the way in which music is distributed and consumed. As a result, millions of songs are instantly available to millions of people, on the Internet. This has created the need for novel music search and discovery services. Music is often searched using descriptive keywords, or tags, based on the content of the song. Hence, one very important … …Journal of Computer Science, Vol. 15, Issue 8 · 27 Aug 2019 · 7,841 accessesView PDFCite
Research ArticleOpen accessIn the abstractMCMC-Fuzzy: A Fuzzy Metric Applied to Bayesian Network Structure LearningBeatriz Wilges, Ademar Crotti Junior, Silvia Modesto NassarBayesian network structure learning is considered a complex task as the number of possible structures grows exponentially with the number of variables. Two main methods are used for Bayesian network structure learning: Conditional independence, a method in which a structure is created consistently with independence tests performed on data; and the heuristic search method that explores the structure space. Hybrid … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 8,243 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Elite Pool-Based Big Bang-Big Crunch Metaheuristic for Data ClusteringIbrahim Al-Marashdeh, Ghaith M. Jaradat, Masri Ayob et al.This paper delves into the capacity of enhanced Big Bang-Big Crunch (EBB-BC) metaheuristic to handle data clustering problems. BB-BC is a product of an evolution theory of the universe in physics and astronomy. Two main phases of BB-BC are big bang and big crunch. The big bang phase involves a creation of a population of random initial solutions, while in … …Journal of Computer Science, Vol. 14, Issue 12 · 19 Jun 2018 · 7,879 accessesView PDFCite
Research ArticleOpen accessIn the abstractSolving Multi-Objective Master Production Scheduling Model of Kalak Refinery System Using Hybrid Evolutionary Imperialist Competitive AlgorithmShereen Saleem Sadiq, Adnan Mohsin Abdulazeez, Habibollah HaronThe improvement of operational planning in the field of oil refinery management is becoming increasingly essential and valid. The influential primary factor, among others, is the ever-changing economic climate. The industry must continually assess the potential impacts of variations in the final product demand, price fluctuations, crude oil compositions and even seek out immediate opportunities within the market. The Master … …Journal of Computer Science, Vol. 16, Issue 2 · 12 Feb 2020 · 7,827 accessesView PDFCite
Research ArticleOpen accessIn the abstractMaximally Distant Codes Allocation Using Chemical Reaction Optimization and Ant Colony Optimization AlgorithmsTaisir Eldos, Waleed Nazih, Aws KananError correcting codes, also known as error controlling codes, are set of codes with redundancy that allows detecting errors. This is quite useful in transmitting data over a noisy channel or when retrieving data from a storage with possible physical defects. The idea is to use a set of code words that are maximally distant from each other, hence reducing … …Journal of Computer Science, Vol. 11, Issue 8 · 5 Nov 2015 · 7,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic 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 accessIn the abstractDocument Clustering Based on Firefly AlgorithmAthraa Jasim Mohammed, Yuhanis Yusof, Husniza HusniDocument clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters. Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization. This study explores the adaptation of another swarm algorithm which … …Journal of Computer Science, Vol. 11, Issue 3 · 26 Mar 2015 · 7,510 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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
EditorialOpen accessIn the abstractNew Kind of Statistical MethodsCagdas Hakan AladagAladag, C.H. and E. Egrioglu, 2012. Advanced Time Series Forecasting Methods. In: Advances in Time Series Forecasting, Aladag, C.H. and E. Egrioglu (Eds.), Bentham Science Publishers, Oak Park, ISBN-10: 1608053733. Aladag, C.H., 2011. A Hybrid Intelligent Technique Combines Neural Networks and Tabu Search Methods for Forecasting, Computer Search Algorithms. 1st Edn., Nova Publisher, ISBN: 978-1-61209-043-6. Aladag, C.H., E Egrioglu, U. … …Journal of Mathematics and Statistics, Vol. 10, Issue 4 · 28 Nov 2014 · 7,588 accessesView PDFCite