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  1. 1
    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
    “…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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  2. 2
    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
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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  3. 3
    Fast mode decision algorithm

    Fast mode decision algorithm by Maarif, Haris Al Qodri, Gunawan, Teddy Surya, Khalifa, Othman Omran

    Published 2011
    “…Fast mode decision is the developed algorithm intended for selectively choosing the mode decision used by the encoder. …”
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  4. 4
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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  5. 5
    An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel

    An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel by Jaafar, N.S.M., Aziz, I.A., Jaafar, J., Mahmood, A.K.

    Published 2019
    “…Using four datasets, analysis parameters of the Ensemble Empirical Mode Decomposition (EEMD) algorithm has been conducted. …”
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  6. 6
    An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel

    An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel by Jaafar, N.S.M., Aziz, I.A., Jaafar, J., Mahmood, A.K.

    Published 2019
    “…Using four datasets, analysis parameters of the Ensemble Empirical Mode Decomposition (EEMD) algorithm has been conducted. …”
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  7. 7
    An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel

    An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel by Mohd Jaafar, N.S., Aziz, I.A., Jaafar, J., Mahmood, A.K., Gilal, A.R.

    Published 2019
    “…This study has used two datasets to compare the parameters analysis of the Ensemble Empirical Mode Decomposition (EEMD) algorithm for constructing the signal signature. …”
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  8. 8
    An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel

    An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel by Mohd Jaafar, N.S., Aziz, I.A., Jaafar, J., Mahmood, A.K., Gilal, A.R.

    Published 2019
    “…This study has used two datasets to compare the parameters analysis of the Ensemble Empirical Mode Decomposition (EEMD) algorithm for constructing the signal signature. …”
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  9. 9
    Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition

    Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition by Al Jawarneh, Abdullah Suleiman Saleh

    Published 2021
    “…Those methods are combined with the first part of the Hilbert–Huang transformation, namely, the empirical mode decomposition (EMD) algorithm. The EMD algorithm is employed to decompose the nonstationary and nonlinear time series dataset into a finite set of orthogonal decomposition components, which includes a set of intrinsic mode function and residual components. …”
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  10. 10
    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman

    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…For the overall performances which were based on the six data sets, the &-AMH algorithm recorded the highest mean accuracy scores of 0.93 as compared to the other algorithms: the ^-Population (0.91), the &-Modes-RVF (0.81), the New Fuzzy &-Modes (0.80), A:-Modes (0.76), &-Modes-HI (0.76), £-Modes- HII (0.75), Fuzzy £-Modes (0.74) and £-Modes-UAVM (0.70). …”
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  11. 11
    Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints

    Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints by Lee, Wee Chuen

    Published 2017
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  12. 12
    Mode selection mechanism to enable effective device-to-device communication system over different environments

    Mode selection mechanism to enable effective device-to-device communication system over different environments by Zenalden, Feras, Hassan, Suhaidi, Habbal, Adib M. Monzer

    Published 2019
    “…The mode selection mechanism is proposed using multi-criteria for decision-making technique, the mode selection mechanism based on Simple Additive Weighting (SAW) algorithm is used to wisely connect and switch between the available modes. …”
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  13. 13
    Mode selection mechanism to enable effective device-to-device communication system over different environments

    Mode selection mechanism to enable effective device-to-device communication system over different environments by Alden, Feras Zen, Hassan, Suhaidi, Habbal, Adib M. Monzer

    Published 2019
    “…The mode selection mechanism is proposed using multi-criteria for decision-making technique, the mode selection mechanism based on Simple Additive Weighting (SAW) algorithm is used to wisely connect and switch between the available modes. …”
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  14. 14
    Dynamic smart grid communication parameters based cognitive radio network

    Dynamic smart grid communication parameters based cognitive radio network by Haider H.T., Muhsen D.H., Shahadi H.I., See O.H., Elmenreich W.

    Published 2023
    “…The proposed system helps to drive optimal communication parameters to realize power saving, maximum throughput and minimum bit error rate communication modes. A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
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  15. 15
    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE)

    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE) by Tijani, Ismaila Bayo, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2015
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  16. 16
    The Use of Transmission Line Modelling to Test the Effectiveness of I-kaz as Autonomous Selection of Intrinsic Mode Function

    The Use of Transmission Line Modelling to Test the Effectiveness of I-kaz as Autonomous Selection of Intrinsic Mode Function by Hanafi, M. Yusop, M. F., Ghazali, M. F. M., Yusof, Remli, M. A. Pi, Karollah, B., Rusman, .

    Published 2017
    “…This paper proposed the implementation of Integrated Kurtosis-based Algorithm for z-filter Technique (I-kaz) to kurtosis ratio (I-kaz-Kurtosis) for that allows automatic selection of intrinsic mode function (IMF) that's should be used. …”
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  17. 17
    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection

    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection by Ambark, Ali Saleh Al-Massri

    Published 2024
    “…Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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  18. 18
    Load shedding scheme for islanded distribution network with flexible load selection and power changes / Ja’far Saifeddin Abdelhafiz Jallad

    Load shedding scheme for islanded distribution network with flexible load selection and power changes / Ja’far Saifeddin Abdelhafiz Jallad by Ja’far Saifeddin , Abdelhafiz Jallad

    Published 2018
    “…A metaheuristic algorithm in the UFLS scheme can be used to select the best load combination in real time. …”
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  19. 19
    Design and analysis of super twisting sliding mode control for machine tools

    Design and analysis of super twisting sliding mode control for machine tools by Chiew, Tsung Heng, Jamaludin, Zamberi, Bani Hashim, Ahmad Yusairi, Rafan, Nur Aidawaty, Abdullah, Lokman, Salleh, Mohd Rizal, Arep @ Ariff, Hambali

    Published 2016
    “…The performance of tuned super twisting sliding mode controller was compared with a traditional sliding mode controller using sigmoidlike function. …”
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  20. 20
    Holographic mode-selective launch for bandwidth enhancement in multimode fiber

    Holographic mode-selective launch for bandwidth enhancement in multimode fiber by Amphawan, Angela

    Published 2011
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