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  1. 1
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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  2. 2
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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  3. 3
    A random search based effective algorithm for pairwise test data generation

    A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2011
    “…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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  4. 4
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
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  5. 5
    EasyA: Easy and effective way to generate pairwise test data

    EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2013
    “…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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  6. 6
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

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

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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  7. 7
    Non-invasive pathological voice classifications using linear and non-linear classifiers

    Non-invasive pathological voice classifications using linear and non-linear classifiers by Hariharan, Muthusamy

    Published 2010
    “…In this research work, three databases such as MEEI voice disorders database, MAPACI Speech Pathology database, and dataset-III (collected at Hospital Tuanku Fauziah, Kangar, Perlis) are used to test the independence of the algorithms to the databases and the proposed feature extraction algorithms are also tested in noisy condition at 30dB signal-to-noise ratio. …”
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  8. 8
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  9. 9
    Pairwise test suite generator tool based on harmony search algorithm (HS-PTSGT)

    Pairwise test suite generator tool based on harmony search algorithm (HS-PTSGT) by Lai, Yi Xiang

    Published 2014
    “…This thesis is about the research on developing a pairwise test suite generator tool based on Harmony Search Algorithm (HS-PTSGT) to generate optimum test suite. …”
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  10. 10
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…In order to make the normal people can cluster their data easily, this project aims is to develop a web-based clustering tool that can be used by all peoples. …”
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  11. 11
    Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak

    Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

    Published 2020
    “…Here, 19116 colour pixel-based images that comprised of both normal and anomalous behaviours acted as inputs to four samplings of CNN. …”
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  12. 12
    A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer

    A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

    Published 2019
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  13. 13
    Time normalization of LPC feature using warping method

    Time normalization of LPC feature using warping method by Sudirman, Rubita, Salleh, Sh. Hussain, Khalid, Puspa Inayat, Ahmad, Abd. Hamid

    Published 2005
    “…By doing frame fixing (time normalization), the test set and the training set is adjusted to the same number of frames. …”
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  14. 14
    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure

    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

    Published 2019
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  15. 15
    Multi-sources model and control algorithm of an energy management system

    Multi-sources model and control algorithm of an energy management system by Hannan, MA, Azidin, FA, Mohamed, Azah

    Published 2012
    “…The results show that the designed vehicle’s speed and load power closely match those of the ECE-47 test driving cycle under normal and heavy load conditions. …”
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  16. 16
    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
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  17. 17
    Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural

    Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

    Published 2006
    “…The optimum value of epoch and hidden nodes for each learning algorithm are determined based on the highest accuracy obtained during training phases. …”
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  18. 18
    DTWFF-pitch feature and faster neural network convergence for speech recognition

    DTWFF-pitch feature and faster neural network convergence for speech recognition by Sudirman, Rubita, Salleh, Sh. Hussain, Salleh, Shaharuddin

    Published 2007
    “…By doing time normalization, the test set and the training set are adjusted to the same number of frames. …”
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  19. 19
    Early detection and mitigation of DDoS attacks in software defined networks

    Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

    Published 2018
    “…To find the proper detection threshold a series of tests on different scenarios of normal and attack traffic were conducted. …”
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  20. 20
    An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms

    An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms by Zahid, Aafaq

    Published 2015
    “…It is concluded that the resultant hybrid techniques can perform well if the variables provided to normalization by neighborhood model (MF and CF) do not have big differences in order for the hybrid normalization model to outperform every algorithm in comparison.…”
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