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  1. 1
    Machine learning algorithms in context of intrusion detection

    Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

    Published 2016
    “…These machine learning algorithms develop a detection model in a training phase. …”
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  2. 2
    Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective

    Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective by Abubakar, Adamu, Ya’u Gital, Abdulsalam, Chiroma, Haruna, Rana, Nadim, Abdulhamid, Shafi’i, Muhammad, Amina Nuhu, Umar, Aishatu Yahaya

    Published 2019
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  3. 3
    A Novel Hybrid Unet-RBF and CNN-RBF Algorithm for Autism Spectrum Disorder Classification

    A Novel Hybrid Unet-RBF and CNN-RBF Algorithm for Autism Spectrum Disorder Classification by Lim, Huey Chern, Abdulrazak Yahya, Saleh

    Published 2024
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  4. 4
    A novel navigation algorithm for collaborative multi robots

    A novel navigation algorithm for collaborative multi robots by Ahmed, Mohiuddin, Khan, Md. Raisuddin, Billah, Md. Masum, Farhana, Soheli

    Published 2010
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  5. 5
    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2018
    “…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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  6. 6
    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
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  7. 7
    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System

    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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  8. 8
    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm

    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

    Published 2021
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  9. 9
    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering

    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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  10. 10
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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  11. 11
    DNA enhancer prediction using machine learning techniques with novel feature representation

    DNA enhancer prediction using machine learning techniques with novel feature representation by Fong, Pui Kwan

    Published 2016
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  12. 12
    A novel neuroscience-inspired architecture: for computer vision applications

    A novel neuroscience-inspired architecture: for computer vision applications by Hassan, Marwa Yousif, Khalifa, Othman Omran, Abu Talib, Azhar, Olanrewaju, Rashidah Funke, Hassan Abdalla Hashim, Aisha

    Published 2016
    “…Our finding is that there are neuroscience theories that are not utilized in deep learning. Therefore, in this work, a novel model utilizing some of those theories is developed. …”
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  13. 13
    A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection

    A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection by Basheer G.S., Ahmad M.S., Tang A.Y.C.

    Published 2023
    “…We propose a new dimension to detect learning styles, which involves the individuals of learners' social surrounding such as friends, parents, and teachers in developing a novel agent-based framework. …”
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  14. 14
    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making

    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making by Zun, Liang Chuan, Nursultan Japashov, Soon, Kien Yuan, Tan, Wei Qing, Noriszura Ismail

    Published 2024
    “…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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  15. 15
    Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index

    Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index by Verayiah R., Mohamed A., Shareef H., Abidin I.H.Z.

    Published 2023
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  16. 16
    A novel approach based on machine learning and public engagement to predict water-scarcity risk in urban areas

    A novel approach based on machine learning and public engagement to predict water-scarcity risk in urban areas by Hanoon, Sadeq Khaleefah, Abdullah, Ahmad Fikri, M. Shafri, Helmi Z., Wayayok, Aimrun

    Published 2022
    “…This study aims to develop a novel approach based on public participation (PP) with a geographic information system coupled with machine learning (ML) in the urban water domain. …”
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  17. 17
    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
    “…The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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  18. 18
    A novel hybrid evolutionary mating algorithm for Covid19 confirmed cases prediction based on vaccination

    A novel hybrid evolutionary mating algorithm for Covid19 confirmed cases prediction based on vaccination by Ahmed, Marzia, Ahmad Johari, Mohamad, Rahman, Mostafijur, Mohd Herwan, Sulaiman, Abul Kashem, Mohammod

    Published 2023
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  19. 19
    Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network

    Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network by Md. Ali, Mohd. Adli, Abidin, Mohd Radhwan, Nik Muhamad Affendi, Nik Arsyad, Abdullah, Hafidzul, Rosman, Daaniyal Reesha, Badrud'din, Nu'man, Kemi, Faiz, Hayati, Farid

    Published 2021
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  20. 20
    Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making

    Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making by Chuan, Zun Liang, Japashov, Nursultan, Yuan, Soon Kien, Tan, Wei Qing, Noriszura, Ismail

    Published 2024
    “…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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