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  1. 1
    Bayesian inference for the bivariate extreme model

    Bayesian inference for the bivariate extreme model by Mohd Amin, Nor Azrita, Adam, Mohd Bakri

    Published 2016
    “…The model is used in a Bayesian framework where no information of prior is available on unknown model parameters. …”
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  2. 2
    An intelligent framework for modelling and active vibration control of flexible structures

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…The first controller design is formulated so as to allow on-line modeling, controller design and implementation and thus, yield a self-tuning control algorithm. …”
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  3. 3
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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  4. 4
    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system

    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohammad Fadhil, Abas, Bayuaji, Luhur

    Published 2023
    “…This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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  5. 5
    Recommendation System Model For Decision Making in the E-Commerce Application

    Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

    Published 2024
    thesis::doctoral thesis
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  6. 6
    Using genetic algorithms to optimise land use suitability

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…Second task is to determine the fitness function for the genetic algorithms. The third objective is to optimize the land use map using economic benefits. …”
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  7. 7
    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system

    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Ayop Azmi, Nurnajmin Qasrina Ann, Pebrianti, Dwi, Abas, Mohammad Fadhil, Bayuaji, Luhur

    Published 2023
    “…This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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  8. 8
    Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids

    Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

    Published 2023
    “…Two of the most frequently applied algorithms to model species-habitat relationships are Generalised Linear Models (GLM) and Random Forest (RF). …”
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  9. 9
    Discrete-time system identification using genetic algorithm with single parent-based mating technique

    Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

    Published 2024
    “…The methodology encompasses data acquisition, GA program development, SPM technique implementation, and simulation using MATLAB. The study simulated single-input-single-output (SISO) models: ARX and NARX. …”
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  10. 10
    Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization

    Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization by Yap, Chui Ying

    Published 2016
    “…We also implement the Newton-type methods on trust region framework by using unit step length to adjust the radius of the region to obtain desired reduction in the objective function. …”
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  11. 11
    An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions

    An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions by Gerhana, Yana Aditia

    Published 2025
    “…KMS validation was carried out through expert assessment, and the user acceptance of the KMS was evaluated using a survey method, which adopted a questionnaire from the Technology Acceptance Model (TAM) framework. …”
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  12. 12
    Teaching students interdisciplinary knowledge through compilation of differential models within the framework of course projects / Duisebek Nurgabyl ... [et al.]

    Teaching students interdisciplinary knowledge through compilation of differential models within the framework of course projects / Duisebek Nurgabyl ... [et al.] by Nurgabyl, Duisebek, Zhailaubaeva, Nazgul, Abdoldinova, Gulsim, Kaidassov, Zhetkerbai

    Published 2023
    “…In 2020, an experimental study was conducted on the basis of two universities of the Republic of Kazakhstan. The study used empirical research methods: written work, questionnaires, conversations with teachers and future teachers. …”
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  13. 13
    Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan

    Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan by Ahmat Ruslan, Fazlina

    Published 2015
    “…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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  14. 14
    Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam

    Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam by Rustam, Ilham

    Published 2015
    “…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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  15. 15
    Smart final year project archive system using laravel framework with email notification (SFYPAS) / Abidah Mat Taib

    Smart final year project archive system using laravel framework with email notification (SFYPAS) / Abidah Mat Taib by Mat Taib, Abidah, Mohd Shukri, Noor Atirah, Ahmad Zukri, Nurul Hidayah, Ghazali, Norlizawati

    Published 2020
    “…SFYPAS is developed using Laravel framework and the methodology used throughout the project is using Software Development Life Cycle (SDLC). …”
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  16. 16
    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model

    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

    Published 2023
    “…The SSL framework trains the Transformer in two stages. In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. …”
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  17. 17
    Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC) manufacturing

    Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)... by Mohd Fazil, Azlan Faizal, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

    Published 2019
    “…This new framework will be able to provide range of possible recall rate from minimum to maximum, to identify which classifier algorithm performs the best for given dataset. …”
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  18. 18
    Rapid software framework for the implementation of machine learning classification models

    Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

    Published 2021
    “…The results indicated that although the software framework is easier than the programming platform for implementing the machine learning model, the results from the software framework were highly accurate and reliable. …”
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  19. 19
    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production

    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production by Abdul Sahli, Fakharudin, Md Nasir, Sulaiman, Jailani, Salihon, Norazwina, Zainol

    Published 2013
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  20. 20
    Edge assisted crime prediction and evaluation framework for machine learning algorithms

    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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