Search Results - (( using selection method algorithm ) OR ( storage optimization parallel algorithm ))
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Cryptographic protection of block-oriented storage devices using AES-XTS in FPGA
Published 2013“…In recent years security has been a common concern for the data in-transit between communication networks as well as data at-rest in storage devices. Storage encryption (data at-rest) has now become an important aspect in today’s computing environment. …”
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Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing
Published 2013“…The choice of a scheduling strategy has significant impact on the runtime Central Processing Unit, memory consumption as well as the storage systems. Load balancing optimization techniques such as Ant Colony Optimization (ACO), First Come First Served (FCFS), Round Robin (RR) and Particle Swarm Optimization (PSO) are popular techniques being used for scheduling and load balancing. …”
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Toward heterogeneous computing to facilitate sequential OLAP real-time applications
Published 2016“…The optimized algorithm is dedicated to detect patterns over parallel data streams in Real-Time. …”
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Proceeding Paper -
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Speech compression using compressive sensing on a multicore system
Published 2011“…Finally, to speed up the process, the proposed algorithm will be implemented in a multicore system, i.e. six cores, using Single Program Multiple Data (SPMD) parallel paradigm.…”
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Proceeding Paper -
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Critical insight for MAPReduce optimization in Hadoop
Published 2014“…The predominant philosophy behind Hadoop optimization is the optimization of MapReduce, which is a dominant programming platform effective in bringing a=bout many functional enhancements as per scheduling algorithms developed and implemented. …”
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Article -
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Implementation of energy management system for a split-parallel hybrid electric vehicle with in-wheel motors
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Implementation of energy management system for a split-parallel hybrid electric vehicle with in-wheel motors
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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Article -
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Article -
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Comparison for selection technique in genetic algorithm
Published 2006“…The purpose of this project is to make a comparison for three selection techniques in Genetic Algorithm.The Genetic Algorithm has been implemented in the previous module for Chess Tournament Management System.Base on previous system the selection method only using randomize.By this project module,only three selections method were use for the comparison.They are Roulette Wheel, Steady-State and Rank selection.The result for this comparison has determined the appropriate selection for Genetic Algorithm implementation in Chess Tournament Management System.This will help Chess Tournament Management System to provide a better optimize schedule.…”
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Undergraduates Project Papers -
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A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa
Published 2007“…A key stage in the system process is the selection of features. This paper discuss about a decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for Bachelor in Multimedia. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. …”
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Article -
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Aco-based feature selection algorithm for classification
Published 2022“…The classification of this type of dataset requires Feature Selection (FS) methods for the extraction of useful information. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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Enhanced selection method for genetic algorithm to solve traveling salesman problem
Published 2017“…Stochastic Universal Selection (SUS) is one of the selection methods in GA which is considered fast but it leads to lower quality solution.Although using Rank Method Selection (RMS) may lead to high quality solution, it has long runtime.In this work, an enhanced selection method is presented which maintains both fast runtime and high solution quality.First, we present a framework to solve TSP using GA with the original selection method SUS. …”
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Conference or Workshop Item -
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Article -
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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