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45 articles for “parallel algorithms”
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Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Optimization of Physics Simulations Through Genetic AlgorithmsOksana Shadura, Federico Carminati, Anatoliy PetrenkoThe GeantV R&D approach is revisiting the standard particle transport simulation approach to be able to benefit from “Single Instruction, Multiple Data” (SIMD) computational architectures or extremely parallel systems like coprocessors and GPUs. The goal of this work is to develop a mechanism for optimizing the programs used for High-Energy Physics (HEP) particle transport simulations using a “black-box” optimization approach. … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 8,096 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Reformed K-Nearest Neighbors Algorithm for Big Data SetsVo Ngoc Phu, Vo Thi Ngoc TranA Data Mining Has Already Had Many Algorithms Which A K-Nearest Neighbors Algorithm, K-NN, Is A Famous Algorithm For Researchers. K-NN Is Very Effective On Small Data Sets, However It Takes A Lot Of Time To Run On Big Datasets. Today, Data Sets Often Have Millions Of Data Records, Hence, It Is Difficult To Implement K-NN On Big Data. In … …Journal of Computer Science, Vol. 14, Issue 9 · 8 Mar 2018 · 7,477 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Sensors for Monitoring Combustion Quality and Flue Gas Emissions in Power Station BoilersNallamilli P G Bhavani, Kesavan Sujatha, Ponmagal RajendranThis research work includes a combination of Fisher’s Linear Discriminant (FLD) analysis by merging Radial Basis Function (RBF) Network and Back Propagation Algorithm (BPA) for monitoring the combustion conditions of a coal fired boiler. The CCD Camera is used to capture the two dimensional flame images. The features such as images, average intensity, area, brightness and orientation etc., of the … …American Journal of Applied Sciences, Vol. 15, Issue 1 · 7 Feb 2018 · 7,556 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Apache Spark based Algorithm to Solve Dirichlet Problem for Poisson Equation in 3D Computational DomainShomanov Aday, Mansurova MadinaParallel computations are essential tool in solving large-scale computationally demanding problems. Due to large diversity and heterogeneity of the currently available parallel processing techniques and paradigms it is usually difficult to find the right solution that will perform well according to every performance metric. As one of the recent developments in parallel computing Apache Spark framework allows to process petabyte-scale … …Journal of Computer Science, Vol. 12, Issue 10 · 15 Dec 2016 · 7,055 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Innovative Cooling Law for Simulated Annealing AlgorithmsAntonella Certa, Toni Lupo, Gianfranco PassannantiThe present paper proposes an original and innovative cooling law in the field of Simulated Annealing (SA) algorithms. Particularly, such a law is based on the evolution of different initial seeds on which the algorithm works in parallel. The efficiency control of the new proposal, executed on problems of different kind, shows that the convergence quickness by using such a … …American Journal of Applied Sciences, Vol. 12, Issue 6 · 16 Jul 2015 · 6,726 accessesView PDFCite
Research ArticleOpen accessIn the abstractPARALLEL IMPLEMENTATION OF EXPECTATION-MAXIMISATION ALGORITHM FOR THE TRAINING OF GAUSSIAN MIXTURE MODELSG. F. Araújo, H. T. Macedo, M. T. Chella et al.Most machine learning algorithms need to handle large data sets. This feature often leads to limitations on processing time and memory. The Expectation-Maximization (EM) is one of such algorithms, which is used to train one of the most commonly used parametric statistical models, the Gaussian Mixture Models (GMM). All steps of the algorithm are potentially parallelizable once they iterate over … …Journal of Computer Science, Vol. 10, Issue 10 · 9 Jul 2014 · 6,940 accessesView PDFCite
Research ArticleOpen accessIn the abstractA COMPARATIVE STUDY FOR RHODOPSIN PROTEIN FOLDING PROBLEMIman Ahmed Mahmoud, Amr Ahmed Badr, Mostafa Abdel AzimProteins are very important components in any living cells. A number of diseases such as Retinitis pigmentosa, Stargadt-like macular degeneration and Doyne Honeycomb Retinal Dystrophy (DHRD) diseases are shown to result from misfunctioning of proteins. Protein folding problem is a way to predict the best and optimal 3D molecular structure (tertiary structure) of a protein which is then considered to … …Journal of Computer Science, Vol. 10, Issue 10 · 6 May 2014 · 7,078 accessesView PDFCite
Research ArticleOpen accessIn the abstractLOW COMPLEXITY CONSTRAINTS FOR ENERGY AND PERFORMANCE MANAGEMENT OF HETEROGENEOUS MULTICORE PROCESSORS USING DYNAMIC OPTIMIZATIONA. S. Radhamani, E. BaburajOptimization in multicore processor environment is significant in real world dynamic applications, as it is crucial to find and track the change effectively over time, which requires an optimization algorithm. In massively parallel processing multicore processor architectures, like other population based metaheuristics Constraint based Bacterial Foraging Particle Swarm Optimization (CBFPSO) scheduling can be effectively implemented. In this study we discuss … …Journal of Computer Science, Vol. 10, Issue 8 · 3 Apr 2014 · 6,647 accessesView PDFCite
Research ArticleOpen accessIn the abstractOPTIMIZING MULTIPLE TRAVELLING SALESMAN PROBLEM CONSIDERING THE ROAD CAPACITYRanjana Ponraj, George AmalanathanThe Multiple Travelling Salesman Problems (MTSP) can be used in a wide range of discrete optimization problems. As the solution to this problem has wide applicability in many practical fields, this NP Hard problem highly raises the need for an efficient solution. The problem is determining a set of routes for the salesmen that jointly visit a set of given … …Journal of Computer Science, Vol. 10, Issue 4 · 23 Dec 2013 · 6,802 accessesView PDFCite