Search Results - (( evolution classification _ algorithm ) OR ( simulation computing based algorithm ))

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    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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    Thesis
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    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…Hence, the numerical simulations take unacceptably more execution time on sequential computers to run the simulation packages. …”
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    Thesis
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    Incorporating the range-based method into GridSim for modeling task and resource heterogeneity by Eng, Kailun, Muhammed, Abdullah, Mohamed, Mohamad Afendee, Hasan, Sazlinah

    Published 2017
    “…As heterogeneity is one of the unique characteristics of Grid computing, which induces additional challenges in designing heuristic-based scheduling algorithms, the main concern when performing simulation experiments for evaluating the performance of scheduling algorithms is how to model and simulate different Grid scheduling scenarios or cases that capture the inherent nature of heterogeneity of Grid computing environment. …”
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    Article
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    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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    Article
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    Image Template Matching Based on Simulated Kalman Filter (SKF) Algorithm by Nurnajmin Qasrina, Ann, Pebrianti, Dwi, Zuwairie, Ibrahim, Luhur, Bayuaji, Mohd Falfazli, Mat Jusof

    Published 2018
    “…A novel approach to the image matching based on Simulated Kalman Filter (SKF) algorithm has been proposed in this paper. …”
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    Article
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    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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    Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

    Published 2016
    “…We simulate our proposed algorithms using a Java based simulator that is purposedly built for Grid computing simulations. …”
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    Thesis
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    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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    Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing by Kamal Z., Zamli, Norasyikin, Safieny, Fakhrud, Din

    Published 2018
    “…Given such prospects, this research explores a hybrid test redundancy reduction strategy based on Global Neighborhood Algorithm and Simulated Annealing, called GNA_SA. …”
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    Conference or Workshop Item
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    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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    Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Job scheduling algorithm has a significant influence on grid computing performance. …”
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    Conference or Workshop Item
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    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems by Tan, Joe Yee

    Published 2022
    “…This research also provided some results in combining the rule-based simulation with optimization: first, a feasible schedule was computed and then fine-tuned with the rule-based simulation system, then tested with RMS which is the reactive part. …”
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    Adaptive DNA computing algorithm by using PCR and restriction enzyme by Watanabe, Shinpei, Tsuboi, Yusei, Ibrahim, Zuwairie, Yamamoto, Tsuneto, Ono, Osamu

    Published 2004
    “…The adaptive algorithm is designed based on Adleman-Lipton [3I paradigm of DNA computing, However, unlike the Adleman- Lipton architecture, a cutting operation has been introduced to the algorithm and the mechanism in which the molecules used by computation were feedback to the next cyclc was devised. …”
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    Book Section
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    Simulated annealing approach to cost-based multi- quality of service job scheduling in cloud computing enviroment by Abdullah, Monir, Othman, Mohamed

    Published 2014
    “…The main disadvantage of GA algorithm is time consuming problem. In this study, a novel Simulated Annealing (SA) algorithm is proposed for scheduling task in cloud environment. …”
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    Article
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    A discrete event simulation framework for utility accrual scheduling algorithm in uniprocessor environment by Ahmad, Idawaty, K. Subramaniam, Shamala, Othman, Mohamed, Ahmad Zukarnain, Zuriati

    Published 2011
    “…Approach: The study focused on the proposed and the development of an event based discrete event simulator for the existing General Utility Scheduling (GUS) to facilitate the reuse of the algorithm under a common simulation environment. …”
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    Article