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  1. 1
    Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means

    Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means by Azam, M.H., Hasan, M.H., Hassan, S., Abdulkadir, S.J.

    Published 2020
    “…Though membership functions are determined through expert's opinion, however, the one estimated through heuristic algorithms is the preferable methods. …”
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  2. 2
    ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION

    ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION by MUBARAK MOHMMED, HUSSAM ALHAJ

    Published 2015
    “…Frequency and harmonics are two essential parameters for power system functions such as power quality monitoring, power system protection, economic dispatch and security assessment. …”
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  3. 3
    Power System State Estimation In Large-Scale Networks

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The quality of estimated results will depend on the measurements, the assumed network model and its parameters. …”
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  4. 4
    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques

    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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  5. 5
    Modeling and Prediction of the mechanical properties of feedstock by cooling-slope casting process using MOJaya algorithm

    Modeling and Prediction of the mechanical properties of feedstock by cooling-slope casting process using MOJaya algorithm by Mohd Said, Rahaini, Mohamad Kamal, Mohamad Ridzuan, Hussin, Nor Hafizah, Mohamad Suhaili, Sinarwati, Hairol Anuar, Siti Haryanti, Samsudin, Adam, Mohd Yussoff, Nurul Hajar, Winanto, Eko Arip

    Published 2024
    “…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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  6. 6
    Modeling and Prediction of The Mechanical Properties of Feedstock by Cooling-Slope Casting Process using MOJaya Algorithm

    Modeling and Prediction of The Mechanical Properties of Feedstock by Cooling-Slope Casting Process using MOJaya Algorithm by Rahaini, Mohd Said, Mohamad Ridzuan, Mohamad Kamal, Nor Hafizah, Hussin, Sinarwati, Mohamad Suhaili, Siti Haryanti, Hairol Anuar, Adam, Samsuddin, Nurul Hajar, Mohd Yussoff, Eko Arip, Winanto

    Published 2024
    “…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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  7. 7
    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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  8. 8
    Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD

    Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD by Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.

    Published 2014
    “…The method employs the ABC technique to learn the parameters of the adaptive thresholding function required for optimum enhancement. …”
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  9. 9
    Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models

    Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models by Khairudin K., Ul-Saufie A.Z., Senin S.F., Zainudin Z., Rashid A.M., Abu Bakar N.F., Anas Abd Wahid M.Z., Azha S.F., Abd-Wahab F., Wang L., Sahar F.N., Osman M.S.

    Published 2025
    “…Among the mathematical modelling methods employed are artificial neural networks with feed-forward backpropagation algorithms and radial basis functions. …”
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  10. 10
    Model-based hybrid variational level set method applied to object detection in grey scale images

    Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

    Published 2024
    “…In industrial inspection, segmentation algorithms detect product defects, cracks, or anomalies for quality control and safety. …”
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  11. 11
    Diagonalization of covariance matrix in simultaneous localization and mapping of mobile robot

    Diagonalization of covariance matrix in simultaneous localization and mapping of mobile robot by Maziatun, Mohamad Mazlan, Nur Aqilah, Othman, Hamzah, Ahmad

    Published 2019
    “…Therefore, improvement is needed to find better iagonalization method. In view of two contextual investigations, the practices of estimation and covariance are checked.…”
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  12. 12
    On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee

    On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee by Wong , Soo Mee

    Published 2021
    “…Second, it develops an adaptive structure selection method that removes detrimental structures and selects only useful information for point spread function (PSF) estimation. …”
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  13. 13
    Enhancing riverine load prediction of anthropogenic pollutants: harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models

    Enhancing riverine load prediction of anthropogenic pollutants: harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models by Khairudin, Khairunnisa, Ul-Saufie, Ahmad Zia, Senin, Syahrul Fithry, Zainudin, Zaki, Rashid, Ammar Mohd, Abu Bakar, Noor Fitrah, Anas Abd Wahid, Muhammad Zakwan, Azha, Syahida Farhan, Abd Wahab, Mohd Firdaus, Wang, Lei, Sahar, Farisha Nerina, Osman, Mohamed Syazwan

    Published 2024
    “…Among the mathematical modelling methods employed are artificial neural networks with feed-forward backpropagation algorithms and radial basis functions. …”
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  14. 14
    Enhancement of impact force determination with modal transformation method by using integration and data filtering /Khoo Shin Yee

    Enhancement of impact force determination with modal transformation method by using integration and data filtering /Khoo Shin Yee by Khoo, Shin Yee

    Published 2013
    “…The low quality of fitting a modal model by using modal parameters obtained from the polynomial curve fitting algorithm is highlighted. …”
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  15. 15
    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis

    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

    Published 2011
    “…Artificial Neural Network (ANN) method was also employed for the estimation of esterification yield in enzymatic synthesis of xylitol esters. …”
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  16. 16
    Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus

    Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus by Kumar, A., Ridha, S., Ilyas, S.U., Dzulkarnain, I., Pratama, A.

    Published 2022
    “…The algorithms also explain the effect of geometric and rheological parameters on the fluid flow attributes. …”
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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    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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