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  1. 1
    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui

    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

    Published 2019
    “…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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  2. 2
    Smart phone sensor data: Comparative analysis of various classification methods for task of human activity recognition

    Smart phone sensor data: Comparative analysis of various classification methods for task of human activity recognition by Tanveer Abbas Gadehi, Faheem Yar Khuhawar, Ahmed Memon, Kashif Nisar

    Published 2018
    “…The results suggest that logistic regression has been an optimal choice based on experiments. Whereas, the Support Vector Machine (SVM) has shown to perform well with ninety-five percentage accuracy.…”
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  3. 3
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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  4. 4
    3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm

    3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm by Yong, Ericsson, Muhammad Aizzat, Zakaria, Mohamad Heerwan, Peeie, M. Izhar, Ishak

    Published 2024
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  5. 5
    Classification of Agarwood using ANN

    Classification of Agarwood using ANN by M. S., Najib, N. A., Mohd Ali, M. N., Mat Arip, M., Abd Jalil, M. N., Taib

    Published 2012
    “…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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  6. 6
    A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar

    A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar by Noorsal, Emilia, Osman, Muhammad Khusairi, Mokhtar, Norfadzilah

    Published 2007
    “…The optimum structure of the neural network was determined by trial and error method to obtain the optimized hidden neuron and weight values. …”
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  7. 7
    Classification of agarwood using ANN / Muhammad Sharfi Najib ...[et al.]

    Classification of agarwood using ANN / Muhammad Sharfi Najib ...[et al.] by Najib, Muhammad Sharfi, Md Ali, Nor Azah (Dr.), Mat Arip, Mohd Nasir, Jalil, Abd Majid, Taib, Mohd Nasir

    Published 2012
    “…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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  8. 8
    Drowsiness Detection Using Ocular Indices from EEG Signal

    Drowsiness Detection Using Ocular Indices from EEG Signal by Tarafder, S., Badruddin, N., Yahya, N., Nasution, A.H.

    Published 2022
    “…Different machine learning classification models, including the decision tree, the support vector machine (SVM), the K-nearest neighbor (KNN) method, and the bagged and boosted tree models, were trained based on the seven selected features. …”
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  9. 9
    Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification

    Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

    Published 2019
    “…Furthermore, the Support vector machine (SVM) and Linear discriminant analysis (LDA) machine learning for the hand posture classification based on the EMG signal pattern were investigated and compared in term of classification performance. …”
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  10. 10
    Radar - Acoustic Vehicle Classification System based on shallow Convolutional Neural Network

    Radar - Acoustic Vehicle Classification System based on shallow Convolutional Neural Network by Yasmin, Aida

    Published 2025
    “…Many also adopted standard machine learning with hand-crafted features, which are difficult to design and sub-optimal. …”
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  11. 11
    Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network

    Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network by Vincent Chung, Norah Tuah, Kit Guan Lim, Min Keng Tan, Ismail Saad, Kenneth Tze Kin Teo

    Published 2020
    “…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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  12. 12
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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  13. 13
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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  14. 14
    Grid base classifier in comparison to nonparametric methods in multiclass classification

    Grid base classifier in comparison to nonparametric methods in multiclass classification by Moheb Pour, Majid Reza, Jantan, Adznan, Saripan, M. Iqbal

    Published 2010
    “…This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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  15. 15
    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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  16. 16
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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  17. 17
    Chaotic Mapping Lion Optimization Algorithm-Based Node Localization Approach for Wireless Sensor Networks

    Chaotic Mapping Lion Optimization Algorithm-Based Node Localization Approach for Wireless Sensor Networks by Motwakel, Abdelwahed, Hassan Abdalla Hashim, Aisha, Alamro, Hayam, Alqahtani, Hamed, Alotaibi, Faiz Abdullah, Sayed, Ahmed

    Published 2023
    “…Keywords: anchor nodes; metaheuristic optimization algorithm; node localization; tent chaotic mapping; wireless sensor networks…”
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  18. 18
    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms

    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

    Published 2021
    “…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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    Final Year Project
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  19. 19
    The forecasting of poverty using the ensemble learning classification methods

    The forecasting of poverty using the ensemble learning classification methods by Zamzuri, Muhammad Haziq Adli, Nadilah, Sofian, Hassan, Raini

    Published 2023
    “…Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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  20. 20
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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