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  1. 1
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…This study constructs the flow of DNN based method with the K-Means algorithm. …”
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  2. 2
    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction

    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction by Hammid, Ali Thaeer, M. H., Sulaiman, Awad, Omar I.

    Published 2018
    “…Second, it is to construct on this method to improve an efficient process for prediction problems that can discover efficient solutions at a high speed of convergence. …”
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  3. 3
    Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty

    Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Tiong S.K., Hossain M.J.

    Published 2024
    “…The GSA algorithm optimizes the hyperparameters of the LSTM network to construct an optimal model. …”
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  4. 4
    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN

    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

    Published 2011
    “…The algorithm is utilized for predicting a huge set of unlabeled data, given a small number of labelled data. …”
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  5. 5
    A systematic review of machine learning techniques and applications in soil improvement using green materials

    A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

    Published 2023
    “…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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  6. 6
    Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao

    Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao by He , Biao

    Published 2024
    “…This thesis addresses the limitations of existing overbreak prediction methods by introducing a novel data-driven approach based on deep continual learning. …”
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  7. 7
    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach

    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

    Published 2023
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  8. 8
    Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers

    Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

    Published 2025
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  9. 9
    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique

    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

    Published 2016
    “…K-Nearest Neighbour (KNN) is a well-known incremental learning method which applies First-In-First-Out (FIFO) knowledge update strategy. …”
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  10. 10
    Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines

    Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

    Published 2019
    “…This creates a demand of utilizing machine learning in predicting corrosion occurrence. This paper discusses on the evaluation of machine learning algorithms in predicting CO 2 internal corrosion rate. …”
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  11. 11
    Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines

    Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

    Published 2019
    “…This creates a demand of utilizing machine learning in predicting corrosion occurrence. This paper discusses on the evaluation of machine learning algorithms in predicting CO2 internal corrosion rate. …”
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  12. 12
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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  13. 13
    An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms

    An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms by Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain

    Published 2022
    “…This fusion of data science, artificial intelligence, and electrical energy management has turned out to be the most precise and robust energy management solution. …”
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  14. 14
    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
    “…On the other hand, existing stream data learning models with limited labelling have many limitations. …”
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  15. 15
    Machine Learning Algorithms for Diabetes Prediction: A Review Paper

    Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

    Published 2023
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  16. 16
    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data

    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

    Published 2025
    “…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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  17. 17
    A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy

    A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy by Leow S.Y., Wong S.Y., Yap K.S., Yap H.J.

    Published 2023
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  18. 18
    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
    “…As for classification, researchers have used semi-supervised learning for extreme learning machine (ELM), where they have exploited both the labeled and unlabeled data in order to boost the learning performances. …”
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  19. 19
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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  20. 20
    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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