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    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…By employing these methods, organizations can effectively allocate resources and exercise control over costs. Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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    Article
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    Mortality prediction in critically ill patients using machine learning score by Dzaharudin, Fatimah, Md Ralib, Azrina, Jamaludin, Ummu Kulthum, Mat Nor, Mohd Basri, Tumian, Afidalina, Har, Lim Chiew, Ceng, T C

    Published 2020
    “…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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    Proceeding Paper
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    Mortality prediction in critically ill patients using machine learning score by Fatimah, Dzaharudin, Azrina, Md Ralib, Ummu Kulthum, Jamaludin, Mohd Basri, Mat Nor, Afidalina, Tumian, Har, Lim Chiew, Ceng, T. C.

    Published 2020
    “…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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    Conference or Workshop Item
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    Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

    Published 2021
    “…Meanwhile, experiments using five common algorithms, Random Forest Regressor Model outperforms four (4) other algorithms in predicting the price of green building condominium, by training and validating the data-set using Split approach. …”
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    Thesis
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    Enhancing river health monitoring: Developing a reliable predictive model and mitigation plan by Azha S.F., Sidek L.M., Ahmad Z., Zhang J., Basri H., Zawawi M.H., Noh N.M., Ahmed A.N.

    Published 2024
    “…The dynamic and non-linear characteristics of water quality parameters pose significant challenges for conventional machine learning algorithms like multi-linear regression, as they struggle to capture these complexities. …”
    Article
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    Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

    Published 2022
    “…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
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    Final Year Project / Dissertation / Thesis
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    Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region by Anees, Shoaib Ahmad, Mehmood, Kaleem, Khan, Waseem Razzaq, Sajjad, Muhammad, Alahmadi, Tahani Awad, Alharbi, Sulaiman Ali, Luo, Mi

    Published 2024
    “…Secondly, the research systematically assesses the effectiveness of different algorithms to identify the most precise method for establishing any potential relationship between field-measured AGB and predictor variables. …”
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    Article
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    Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0 by Chong, Agnes Wen Lin

    Published 2023
    “…Thus, the secondary objective is to learn about the model including innovation, enterprise, and Ecological. …”
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    Final Year Project / Dissertation / Thesis
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    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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    Conference or Workshop Item
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    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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    Conference or Workshop Item
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    Forecasting of meteorological drought using ensemble and machine learning models by Pande C.B., Sidek L.M., Varade A.M., Elkhrachy I., Radwan N., Tolche A.D., Elbeltagi A.

    Published 2025
    “…Therefore, the Matern GPR model was identified as the finest ML algorithm for predicting SPI-3 and SPI-6 associated with other algorithms. …”
    Article
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    Strategic capabilities, innovation strategy and the performance of food and beverage small and medium enterprises by Salisu, Yakubu

    Published 2019
    “…Consequently, the significant positive impacts of top management, technological, learning and relational capabilities postulate that these variables are valuable in influencing performance directly and indirectly through innovation strategy. …”
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    Thesis
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    Short lead time standard precipitation index forecasting: Extreme learning machine and variational mode decomposition by Ladouali S., Katipo?lu O.M., Bahrami M., Kartal V., Sakaa B., Elshaboury N., Keblouti M., Chaffai H., Ali S., Pande C.B., Elbeltagi A.

    Published 2025
    “…Study focus: This study focused on creating a novel hybrid VMD-ELM approach, established by combining the Variational Mode Decomposition (VMD) technique and the Extreme Learning Machine (ELM) algorithm as a preprocessing technique for predicting future droughts. …”
    Article