Search Results - (( initial selection based algorithm ) OR ( using classification using algorithm ))

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  1. 1

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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    Thesis
  2. 2

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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    Article
  3. 3
  4. 4

    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…The first improvement includes using Elite Opposition-Based Learning (EOBL) at initialization phase of WOA. …”
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    Article
  5. 5

    An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

    Published 2015
    “…A ensemble clustering is designed, used and evaluated to generate the final classification framework that will take all input generated from the GA based clustering with Feature Selection and Feature Construction algorithms and perform the classification task for the relational datasets. …”
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    Thesis
  6. 6

    A novel framework for identifying twitter spam data using machine learning algorithms by Maziku, Susana Boniphace, Abdul Rahiman, Amir Rizaan, Muhammed, Abdullah, Abdullah @ Selimun, Mohd Taufik

    Published 2020
    “…The feature selection is introduced to select the most important from the extracted high-dimensional best features and feed the selected features into the minimum Redundancy and Maximal Relevance algorithm and apply random forest for classification. …”
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    Article
  7. 7

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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  8. 8

    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

    Published 2012
    “…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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    Article
  9. 9

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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    Article
  10. 10

    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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    Thesis
  11. 11

    Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

    Published 2016
    “…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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  12. 12

    An improved genetic-fuzzy system for classification and data analysis by Lahsasna, A., Seng, W.C.

    Published 2017
    “…In the second variant classifier, we further improve the first variant classifier by enhancing the selection method of the antecedent conditions of the rules generated in the initial population of genetic algorithm. …”
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    Article
  13. 13

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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  14. 14

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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  15. 15

    Orientation and scale based weights initialization scheme for deep convolutional neural networks by Azizi Abdullah, Wong, En Ting

    Published 2020
    “…Recent work has shown that the convolutional neural network (CNN) paradigm is useful for obtaining more accurate image classification results. …”
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  16. 16

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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  17. 17

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…One of most used compound selection method is cluster-based compound selection, which involves subdividing a set of compounds into clusters and choosing one compound or a small number of compounds from each cluster. …”
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    Monograph
  18. 18

    A global k-means approach for autonomous cluster initialization of probabilistic neural network by Chang, R.K.Y., Loo, C.K., Rao, M.V.C.

    Published 2008
    “…This paper focuses on the statistical based Probabilistic Neural Network (PNN) for pattern classification problems with Expectation â�� Maximization (EM) chosen as the training algorithm. …”
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    Article
  19. 19

    A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah by Mansoor Abdullah, Hayat

    Published 2012
    “…The results indicated that MLP is sufficient, and optimal enough to be used for classification of the selected freshwater algae. …”
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    Thesis
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