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  1. 1

    A novel deadlock detection algorithm for neighbour replication on grid environment by Noriyani, Mohd Zin

    Published 2012
    “…The aim of this research is to handle the deadlock problem in NRG to preserve the consistency of data and increase the throughput. The NRGDD simulation model has been developed to test the algorithm on NRG. …”
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    Thesis
  2. 2

    Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman by Hamdan, Muhammad Halim, Abdul-Rahman, Shuzlina

    Published 2021
    “…Each technique was replicated, trained and tested accordingly. M4 competition dataset was used in this research, with 100,000 time series data and multiple data frequency, which is enough to replicate the real-world situation. …”
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    Article
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    Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

    Published 2024
    “…It also addresses the practicalities of implementing action recognition algorithms in real-world situations, which include tools like deep learning frameworks, pre-trained models, open-source libraries, cloud services, GPU acceleration, and evaluation metrics. …”
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    Article
  5. 5

    Finite element modeling and updating for dynamic study of exhaust structure by M. S. M., Fouzi, M. S. M., Sani

    Published 2020
    “…Hence, this paper is carried out to reduce the discrepancies between numerical prediction results with measured test data on FE model of exhaust structure by implementing FE model updating using SOL200 algorithm. …”
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    Conference or Workshop Item
  6. 6

    Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

    Published 2009
    “…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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    Book Chapter
  7. 7

    Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

    Published 2020
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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    Thesis
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    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

    Published 2019
    “…Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.…”
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    Article
  10. 10

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…Additionally, the Wilcoxon rank test was used to perform the significance analysis between the proposed SCSOKNN method and six other algorithms for a p-value less than 5.00E-02. …”
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    Article
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    Support vector machine in precision agriculture: a review by Kok, Zhi Hong, Mohamed Shariff, Abdul Rashid, M. Alfatni, Meftah Salem, Bejo, Siti Khairunniza

    Published 2021
    “…The Support Vector Machine (SVM) is a Machine Learning (ML) algorithm which may be used for acquiring solutions towards better crop management. …”
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    Article
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    Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A., Chong K.L., Huang Y.F., Ahmed A.N., Ng J.L., Koo C.H., Tan K.W., Sherif M., El-shafie A.

    Published 2024
    “…In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. …”
    Article
  15. 15

    Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A, Chong K.L, Huang Y.F, Ahmed A.N, Ng J.L, Koo C.H, Tan K.W, Sherif M, El-shafie A

    Published 2025
    “…In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. …”
    text::Article
  16. 16

    The Effects Of Segmenting And Computational Thinking In Digital Video Courseware On Knowledge Achievement, Self-Efficacy And Motivation Among Students With Different Thinking Style... by Ali, Wan Nor Ashiqin Wan

    Published 2023
    “…The researcher found significant main and interaction effects of the learner-paced predefined segment on all dependent variables. …”
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    Thesis
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    Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique by Yahaya, Noor Zaitun, Ghazali, Nurul Adyani, Ahmad, Sabri, Mohammad Asri, Mohammad Akmal, Ibrahim, Zul Fahdli, Ramli, Nor Azman

    Published 2017
    “…Sensitivity testing of the BRT model was conducted to determine the best parameters and good explanatory variables. Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. …”
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    Article
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    A self-adaptive agent-based simulation modelling framework for dynamic processes by Ling, Loo Yim, Dr.

    Published 2023
    “…Case studies for simulating dynamic processes of new student registration (administrative domain), transport request (transportation domain) and crime investigation (security domain) with real data collected through interview and document reviews to test the proposed idea. …”
    text::Thesis
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    Finger-Vein Biometric Identification Using Convolutional Neural Network by Syafeeza, Ahmad Radzi, Mohamed, Khalil-Hani, Rabia, Bakhteri

    Published 2016
    “…An identification rate of 100.00% is achieved, with an 80/20 percent ratio for separation of training and test samples, respectively. An additional number of subjects have also been tested, in which for 81 subjects an accuracy of 99.38% is achieved.…”
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    Article