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  1. 1
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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  2. 2
    A hybridisation of adaptive variable neighbourhood search and large neighbourhood search: Application to the vehicle routing problem

    A hybridisation of adaptive variable neighbourhood search and large neighbourhood search: Application to the vehicle routing problem by Sze, Jeeu Fong, Salhi, S., Wassan, N.

    Published 2016
    “…In this paper, an adaptive variable neighbourhood search (AVNS) algorithm that incorporates large neighbourhood search (LNS) as a diversification strategy is proposed and applied to the capacitated vehicle routing problem. …”
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  3. 3
    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning

    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning by Ahmed Abo Mosali, Najm Addin Mohammed

    Published 2022
    “…In this thesis, the Twin Delayed Deep Deterministic Policy Gradient Algorithm (TD3), as one recent and composite architecture of reinforcement learning (RL), has been explored as a tracking agent for the problem of UAV-based target tracking. …”
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  4. 4
    Antidepressant Treatment Response Prediction With Early Assessment of Functional Near-Infrared Spectroscopy and Micro-RNA

    Antidepressant Treatment Response Prediction With Early Assessment of Functional Near-Infrared Spectroscopy and Micro-RNA by Lee, Lok Hua, Ho, Cyrus Su Hui, Chan, Yee Ling, Tay, Gabrielle Wann Nii, Lu, Cheng-Kai, Tang, Tong Boon

    Published 2025
    “…To address this, the aim of the current study is to investigate MDD ATR at three response levels using fNIRS and micro-ribonucleic acids (miRNAs). Our proposed algorithm includes a custom inter-subject variability reduction based on the principal component analysis (PCA). …”
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  5. 5
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Derisf, Mustafa, Aqil Burney, S.M.

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  6. 6
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Burney, S.M.Aqil

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  7. 7
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Aqil Burney, S.M.

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  8. 8
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Riswan Efendi, Riswan Efendi, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Aqil Burney, S.M.

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  9. 9
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Riswan Efendi, Riswan Efendi, Nazri Mohd. Nawi, Nazri Mohd. Nawi, Mustafa Mat Deris, Mustafa Mat Deris, S.M.Aqil Burney, S.M.Aqil Burney

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  10. 10
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  11. 11
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  12. 12
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efend, Riswan, Mohd. Nawi, Nazri, Mat Derisf, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  13. 13
    Cleansing of inconsistent sample in linear regression model based on rough sets theory

    Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

    Published 2023
    “…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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  14. 14
    Twin delayed deep deterministic policy gradient-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage training

    Twin delayed deep deterministic policy gradient-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage training by Abo Mosali, Najmaddin, Shamsudin, Syariful Syafiq, Alfandi, Omar, Omar, Rosli, AL-Fadhali, Najib

    Published 2022
    “…In addition, the concept of multistage training based on the dynamic variables was proposed as an opposing concept to one-stage combinatory training. …”
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  15. 15
    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…A novel feature extraction algorithm was developed to extract the feature vectors. …”
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  16. 16
    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail

    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

    Published 2015
    “…Through rank selection technique, the chromosomes are sorted based on the fitness function to learn about the population of current generation. …”
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  17. 17
    Predictive Framework for Imbalance Dataset

    Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

    Published 2012
    “…This research was conducted based on limited number of datasets, test sets and variables. …”
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  18. 18
    A simulation-metaheuristic approach for finding the optimal allocation of the battery energy storage system problem in distribution networks

    A simulation-metaheuristic approach for finding the optimal allocation of the battery energy storage system problem in distribution networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Mohd Shawal, Jadin

    Published 2023
    “…This study will use Teaching Learning-Based Optimization (TLBO) as the main optimizer for the problem simulation. …”
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  19. 19
    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data

    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

    Published 2016
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  20. 20
    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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