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    Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables by Che Dom, Nazri, Mohd Hardy Abdullah, Nur Athen, Dapari, Rahmat, Salleh, Siti Aekbal

    Published 2025
    “…However, current models often rely on coarse regional data and fail to account for microclimatic variations, limiting their predictive accuracy in dengue hotspots. This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
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    Article
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    Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

    Published 2018
    “…The verification results indicate that all the structural defects were predicted with high accuracy by the developed hybrid algorithm in cases of healthy and damaged structures. …”
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    Thesis
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    Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok by Bachok, Mohd Fatruz

    Published 2019
    “…Local conditions wind multiplier map, hazard threshold, and damage scales are three supporting tools that were developed to compliment the predictive model. …”
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    Thesis
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    Performance Measurement on Deep Spiking Neural Network (DSNN) Algorithm in Flood Prediction Environment by Roselind, Tei

    Published 2023
    “…There are several algorithms used to predict floods, including LSTM, BP, MLP, SARIMA, and SVM. …”
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    Thesis
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    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
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    Monograph
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    Can the future really be predicted? by Htike@Muhammad Yusof, Zaw Zaw

    Published 2013
    “…Therefore, it is computationally infeasible to develop full-scale models with the present computing technology. …”
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    Proceeding Paper
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    Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

    Published 2011
    “…The next objective of the current study was to compare the performance of aforementioned algorithms with regard to predicting ability. The investigation of TEA-based esterquat cationic surfactant synthesis was started in a 50 ml scale. …”
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    Thesis
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    Intelligent technique for grading tropical fruit using magnetic resonance imaging by A. Balogun, Wasiu, Salami, Momoh Jimoh Emiyoka, J. McCarthy, Michael, Mohd Mustafah, Yasir, Aibinu, Abiodun Musa

    Published 2013
    “…Our purpose, in this study, is to develop a non-destructive method to predict the status of orange fruits, based on internal quality. …”
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    Article
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    Hybrid DE-PEM algorithm for identification of UAV helicopter by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus, Abdul Muthalif, Asan Gani

    Published 2014
    “…Purpose – The purpose of this paper is to develop a hybrid algorithm using differential evolution (DE) and prediction error modeling (PEM) for identification of small-scale autonomous helicopter state-space model. …”
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    Article
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    Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

    Published 2024
    “…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
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    Thesis
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    Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem by Bahri, Susila

    Published 2004
    “…To process the data collected from British Atmospheric Data Centre (BADC), the sequential programs in row and columnwise fashions are developed and implemented. Then the parallel algorithms are constructed and run using the Beowulf Cluster machine. …”
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    Thesis
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    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

    Published 2023
    “…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. The research is divided into three parts, which are (1) dataset development, (2) algorithm development, and (3) algorithm performance evaluation. …”
    text::Thesis
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    The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

    Published 2024
    “…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”
    Conference Paper
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    Stochastic type-2 fuzzy modelling on GHG emission prediction for gas-fired power plant by Zakaria, Sazalina, R. Ahmad, Radin Diana, Abbas, Ahmad Rosly, Mohideen Batcha, Mohd Faizal, Zanil, Mohd Fauzi

    Published 2021
    “…A novel Karnik-Mendel (KM) algorithm had been proposed with the Genetic Algorithm (GA) model optimization to achieve high performance and accuracy for the respective predictive model. …”
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    Other
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    Prediction analysis of COVID-19 in Selangor by using Backpropagation Algorithm with Conjugate Gradient Method by Noor Amirah Ajmal Khan, Siti Mahani Marjugi

    Published 2024
    “…As a result, using previous COVID-19 data in Selangor, an artificial neural network (ANN) is used as an effective future prediction method. Backpropagation is a form of artificial neural network (ANN) algorithm that may be used to resolve issues in prediction analysis. …”
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    Article
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    Prediction analysis of COVID-19 in Selangor by using backpropagation algorithm with conjugate gradient method by Ajmal Khan, Noor Amirah, Marjugi, Siti Mahani

    Published 2024
    “…As a result, using previous COVID-19 data in Selangor, an artificial neural network (ANN) is used as an effective future prediction method. Backpropagation is a form of artificial neural network (ANN) algorithm that may be used to resolve issues in prediction analysis. …”
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    Article