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  1. 1
    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin

    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…A MySQL database was created to analyze the optimization results and speed up computations of the optimization algorithm. …”
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  2. 2
    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…A deterministic mutation-based algorithm is introduced to overcome this problem. …”
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  3. 3
    Hybrid Genetic Algorithm based Fuzzy Inference System for Data Regression

    Hybrid Genetic Algorithm based Fuzzy Inference System for Data Regression by Wong S.Y., Siah Yap K., Tan C.H.

    Published 2023
    Conference Paper
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  4. 4
    Active vibration control of a flexible beam structure using chaotic fractal search algorithm

    Active vibration control of a flexible beam structure using chaotic fractal search algorithm by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan

    Published 2017
    “…The objective of this work was to evaluate the performance of chaos-enhanced Stochastic Fractal Search (CFS) optimization algorithm in modeling and vibration control of flexible beam system. …”
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  5. 5
    Regression test case selection & prioritization using dependence graph and genetic algorithm

    Regression test case selection & prioritization using dependence graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…The goal is to identify changes in a method's body due to data dependence, control dependence and dependent due to object relation such as inheritance and polymorphism, select the test cases based on affected statements and ordered them based on their fitness by using GA.The number of affected statements determined how fit a test case is good for regression testing. …”
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  6. 6
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  7. 7
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  8. 8
    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique

    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

    Published 2022
    “…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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  9. 9
    A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm

    A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
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  10. 10
    Information Theoretic-based Feature Selection for Machine Learning

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

    Published 2018
    “…Besides, this thesis developed a hybrid filter method to enhance the performance of the IFS. IFS served as filter together with an Ant Colony Optimization System (ACO) as a metaheuristic form the hybrid system. …”
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  11. 11
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  12. 12
    A Novel Three Term Conjugate Gradient Method for Unconstrained Optimization via Shifted Variable Metric Approach with Application

    A Novel Three Term Conjugate Gradient Method for Unconstrained Optimization via Shifted Variable Metric Approach with Application by Yunus, R.B., Kamfa, K., Mohammed, S.I., Mamat, M.

    Published 2022
    “…In this chapter, we present a novel three term (CG) method based on the idea of the shifted variable metric approach. …”
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  13. 13
    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure

    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure by Md Fahmi, Abd Samad

    Published 2016
    “…A parsimonious model structure is desirable in enabling easy control design. Two methods of model structure selection are closely looked into and these are deterministic mutation algorithm (DMA) and forward selection procedure (FSP). …”
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  14. 14
    RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD

    RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD by Homod R.Z., Mohamed Sahari K.S., Almurib H.A.F., Nagi F.H.

    Published 2023
    “…This modeling is achieved using a Takagi-Sugeno (TS) fuzzy model and tuned by Gauss-Newton method for nonlinear regression (GNMNR) algorithm. …”
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  15. 15
    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction

    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction by Hammid, Ali Thaeer, M. H., Sulaiman, Awad, Omar I.

    Published 2018
    “…For this purpose, the suggested approach that makes a hybridizing the FA with the robust algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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  16. 16
    Hybrid optimisation electromagnetic interference shielding effectiveness:mechanical and physical performance of plaster mortar containing palm oil fuel ash using taguchi grey and taguchi-flower pollination algorithm methods

    Hybrid optimisation electromagnetic interference shielding effectiveness:mechanical and physical performance of plaster mortar containing palm oil fuel ash using taguchi grey and t... by Oh Lai Ching, Narong

    Published 2019
    “…Six factors namely POFA admixture percentage, topcoat powder /binder ratio (TP/B), water/binder ratio (W/B), latex agent content (LA), the particle size of POFA and curing condition are used to control the nine responses. Pre-experiment data is optimized based on Taguchi-grey and Flower Pollination Algorithm (FPA) methods. …”
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  17. 17
    Evaluation of optimal cooling control for seeded batch crystallization inclusive dissolution with uncertainties

    Evaluation of optimal cooling control for seeded batch crystallization inclusive dissolution with uncertainties by Siti Zubaidah, Adnan

    Published 2020
    “…Several other strategies pertaining to achieve desired CSD with minimum amount of fine crystals were deployed. The optimization algorithm was employed in order to determine the optimal set-point trajectory for closed-loop control. …”
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  18. 18
    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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  19. 19
    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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  20. 20
    Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework

    Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework by Aidil Zulkafli, Nadhirah, Elyca Anak Bundak, Caceja, Amiruddin Abd Rahman, Mohd, Chin Yap, Chi, Chong, Kok-Keong, Tee Tan, Sin

    Published 2024
    “…This novel study demonstrated that support vector regression (SVR) integrated with the particle swarm optimization (PSO) model is an alternative method to predict the device performance in future organic solar cells.…”
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