Search Results - (( parallel evaluation method algorithm ) OR ( features selection method algorithm ))

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  1. 1

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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    Thesis
  2. 2

    Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

    Published 2019
    “…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). …”
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    Article
  3. 3

    Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

    Published 2019
    “…Then, the two types of features importance computed from RF algorithm are utilized for the attributes explanation. …”
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    Thesis
  4. 4

    Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations by Siri, Zailan

    Published 2004
    “…The method used here is actually have been tailored made for the purpose of parallel machine where the subsequent functions evaluations do not depend on the previous function evaluations. …”
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    Thesis
  5. 5

    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
  6. 6

    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
  7. 7
  8. 8

    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
  9. 9

    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
  10. 10

    Enhancing performance of XTS cryptography mode of operation using parallel design by Ahmed Alomari, Mohammad

    Published 2009
    “…In addition, the parallel XTS mode was also simulated using Twofish and RC6 encryption algorithms. …”
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    Thesis
  11. 11

    Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs. by Ismail, Fudziah, Siri, Zailan, Othman, Mohamad, Suleiman, Mohamed

    Published 2009
    “…Diagonally Implicit Runge-Kutta (DIRK) methods are amongst the most useful and cost-effective methods for solving initial value problems but the dependency of the functions evaluations on the previous functions evaluations makes DIRK method not so favourable for parallel computers. …”
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    Article
  12. 12

    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
  13. 13

    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
  14. 14

    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
  15. 15

    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
  16. 16

    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
  17. 17

    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. …”
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    Book Section
  18. 18

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

    Published 2009
    “…Due to this needs, this paper presents the parallel performance evaluations of algorithms that will be discussed in term of communication and computational cost.…”
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    Book Section
  19. 19

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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    Thesis
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