Search Results - (( parallel distribution methods algorithm ) OR ( feature selection method algorithm ))

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  1. 1

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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    Thesis
  2. 2

    Communication and computational cost on parallel algorithm of PDE elliptic type by Alias, Norma

    Published 2009
    “…The parallel algorithms of 2-dimensional Partial Differential Equation (PDE) elliptic type for the prediction will be executed using distributed memory of heterogeneous cluster platform on LINUX-based environment. …”
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    Book Section
  3. 3

    Simulating Electrohydrodynamic Ion-Drag Pumping on Distributed Parallel Computing Systems by Shakeel Ahmed, Kamboh, Zubair, Ahmed Kalhoro, Kashif, Ali Abro, Jane, Labadin

    Published 2017
    “…To implement the parallel algorithm a distributed parallel computing system using MATLAB Distributed Computing Server (MDCS) is configured. …”
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    Article
  4. 4

    Discretization of crack propagation on parallel computing : complexity and parallel algorithms with source code by Alias, Norma, Islam, Md. Rajibul

    Published 2010
    “…Parallel algorithm is used by Parallel Virtual Machine (PVM) software tool to capture the visualization of the overall extension and the stress distribution in a linearly tapered bar of circular section with an end load. …”
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    Book Section
  5. 5

    Discretization of crack propagation on parallel computing: complexity and parallel algorithms with source code by Alias, Norma, Islam, Md. Rajibul

    Published 2010
    “…Parallel algorithm is used by Parallel Virtual Machine (PVM) software tool to capture the visualization of the overall extension and the stress distribution in a linearly tapered bar of circular section with an end load. …”
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    Book
  6. 6

    The visualization of three dimensional brain tumors' growth on distributed parallel computer systems by Alias, Norma, Masseri, Mohd. Ikhwan Safa, Islam, Md. Rajibul, Khalid, Siti Nurhidayah

    Published 2009
    “…The main objective of this study is to visualize the brain tumors’ growth in three-dimensional and implement the algorithm on distributed parallel computer systems. …”
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    Article
  7. 7
  8. 8

    Parallel strategies on a distributed parallel computer system by Alias, Norma

    Published 2004
    “…The formulation of a new parallel iteration methods are created to solve the parabolic equations in one, two and three dimensions run on a distributed parallel computer systems on the homogeneous parallel machines with 20 PC Intel Pentium IV, speed 1.6MHz and with PVM application platform. …”
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    Monograph
  9. 9

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The classification of this type of dataset requires Feature Selection (FS) methods for the extraction of useful information. …”
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    Thesis
  10. 10

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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  13. 13

    Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2023
    “…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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    Article
  14. 14

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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    Conference or Workshop Item
  15. 15

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    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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    Thesis
  16. 16

    Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

    Published 2018
    “…For feature selection, the methods involved generally compares the feature appearance frequency in positive and negative documents and the methods that compares both feature presence and absence in documents of different classes produced better results. …”
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    Thesis
  17. 17

    Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

    Published 2023
    “…To reduce the computational time during the process of training the SVM, a combination of distributed and parallel computing method, CoDLib have been proposed. …”
    Conference paper
  18. 18

    High performance visualization of human tumor growth software by Alias, Norma, Mohd. Said, Norfarizan, Khalid, Siti Nur Hidayah, Sin, Dolly Tien Ching, Phang, Tau Ing

    Published 2008
    “…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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    Conference or Workshop Item
  19. 19

    Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

    Published 2013
    “…The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. …”
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    Article
  20. 20

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Evaluating the execution time of the proposed methods, utilizing different classifiers, and hybridizing proposed methods with other metaheuristic algorithms to solve feature selection problems would be future works worth exploring.…”
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    Article