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  1. 1
    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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  2. 2
    Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm

    Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

    Published 2024
    “…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”
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  3. 3
    Predictive modelling of machining parameters of S45C mild steel

    Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

    Published 2016
    “…The artificial neural network type Network Fitting Tool (NFTOOL) is used as a modeling technique for manipulating the ideal algorithm parameters. …”
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  4. 4
    Optimization of power system stabilizers using participation factor and genetic algorithm

    Optimization of power system stabilizers using participation factor and genetic algorithm by Hassan, L.H., Moghavvemi, M., Almurib, H.A.F., Muttaqi, K.M., Ganapathy, V.G.

    Published 2014
    “…This paper describes a method to determine the optimal location and the number of multi-machine power system stabilizers (PSSs) using participation factor (PF) and genetic algorithm (GA). …”
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  5. 5
    Modification Of Regression Models To Solve Heterogeneity Problem Using Seaweed Drying Data

    Modification Of Regression Models To Solve Heterogeneity Problem Using Seaweed Drying Data by Joshua, Ibidoja Olayemi

    Published 2023
    “…The proposed method used the variance inflation factor to identify the heterogeneity parameters. …”
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  6. 6
    Parametric coefficient genetic algorithm for domestic water consumption / Nurul Nadia Hani

    Parametric coefficient genetic algorithm for domestic water consumption / Nurul Nadia Hani by Hani, Nurul Nadia

    Published 2019
    “…This research therefore proposes the employment of Genetic Algorithm (GA) to optimize the coefficient of micro-components of water consumption (CMWC) values to determine high influential household routine parameters. …”
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  7. 7
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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  8. 8
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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  9. 9
    Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam

    Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam by Toghroli, Ali, Suhatril, Meldi, Ibrahim, Zainah, Safa, Maryam, Shariati, Mahdi, Shamshirband, Shahaboddin

    Published 2018
    “…Evaluation of the parameters affecting the shear strength and ductility of steel–concrete composite beam is the goal of this study. …”
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  10. 10
    A comparative study of supervised machine learning approaches for slope failure production

    A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

    Published 2023
    “…Generally, slope failure can be estimated based on traditional methods such as limit equilibrium method (LEM) or finite equilibrium method (FEM). …”
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  11. 11
    Application of Decision Tree Algorithm for Predicting Monthly Pan Evaporation Rate

    Application of Decision Tree Algorithm for Predicting Monthly Pan Evaporation Rate by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

    Published 2023
    Conference Paper
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  12. 12
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  13. 13
    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field

    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

    Published 2018
    “…Theoretically,β and α is parameters that used to vary the NMF2D algorithm in order to yield high SDR value. …”
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  14. 14
    A new method for decreasing cell-load variation in dynamic cellular manufacturing systems

    A new method for decreasing cell-load variation in dynamic cellular manufacturing systems by Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol, Baharudin, Btht Hang Tuah, Leman, Zulkiflle

    Published 2016
    “…The Taguchi method (an L_9 orthogonal optimization) is used to estimate parameters of GA in order to solve experiments derived from literature. …”
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  15. 15
    Semiparametric inference procedure for the accelarated failure time model with interval-censored data

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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  16. 16
    An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems

    An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems by Muhammad Akmal, Remli, Mohd Saberi, Mohamad, Safaai, Deris, Sinnott, Richard O., Suhaimi, Napis

    Published 2019
    “…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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  17. 17
    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems

    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems by Remli, Muhammad Akmal, Mohamad, Mohd Saberi, Deris, Safaai, Sinnott, Richard, Napis, Suhaimi

    Published 2019
    “…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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  18. 18
    The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm

    The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

    Published 2020
    “…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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  19. 19
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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  20. 20
    Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm

    Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm by Roslina, Rashid, Hishamuddin, Jamaluddin, Nor Aishah, Saidina Amin

    Published 2011
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