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  1. 1
    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
    “…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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  2. 2
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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  3. 3
    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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  4. 4
    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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  5. 5
    Optimization of perovskite solar cell with MoS2-based HTM layer using hybrid L27 Taguchi-GRA based genetic algorithm

    Optimization of perovskite solar cell with MoS2-based HTM layer using hybrid L27 Taguchi-GRA based genetic algorithm by Salehuddin, Fauziyah, Kaharudin, Khairil Ezwan, Ahmad Jalaludin, Nabilah, Mohd Zain, Anis Suhaila, Arith, Faiz, Md Junos@Yunus, Siti Aisah, Ahmad, Ibrahim

    Published 2025
    “…Numerical simulation of the device is carried out by employing one-dimensional solar cell capacitance simulator (SCAPS-1D) while the optimization procedures are developed based on combination of multiple methods; L27 Taguchi orthogonal array, GRA, multiple linear regression (MLR), and GA. …”
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  6. 6
    A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms

    A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms by Ghazvini, Anahita, Mohd Sharef, Nurfadhlina, Balasundram, Siva Kumar, Lee, Lai Soon

    Published 2024
    “…Crop digital twin is redefining traditional farming practices, offering unprecedented opportunities for real-time monitoring, predictive and simulation analysis, and optimization. This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and regression algorithms to create a digital twin for farmers to augment the concentration and composition prediction-based crop nutrient recovery. …”
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  7. 7
    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network

    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

    Published 2023
    “…The dataset development for both algorithms is carried out via simulations in Graphical Network Simulator 3 (GNS3). …”
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  8. 8
    A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms

    A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms by Mohd Sharef, Nurfadhlina, Balasundram, Siva Kumar, Lai, Soon Lee, Ghazvini, Anahita

    Published 2024
    “…Crop digital twin is redefining traditional farming practices, offering unprecedented opportunities for real-time monitoring, predictive and simulation analysis, and optimization. This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and re-gression algorithms to create a digital twin for farmers to augment the concentration and compo-sition prediction-based crop nutrient recovery. …”
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  9. 9
    Neural network algorithm-based fall detection modelling

    Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

    Published 2020
    “…This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. The algorithm is trained by network training function; LM, SCG and RP by collocation with threshold-based setting value. …”
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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
    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
    “…In the real data simulation, both methods obtained the same model structure whereas in simulated data modelling, only DMA was able to select the correct model structure. …”
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  13. 13
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar

    Published 2009
    “…Five cutpoint determination methods are developed based on regression of competing risks subdistribution. …”
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  14. 14
    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
    “…A PID controller incorporated with CFS optimization algorithm was employed to attenuate the unwanted vibration from the flexible beam system. …”
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  15. 15
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Ibrahim, Noor Akma, Kudus, Abdul, Daud, Isa, Abu Bakar, Mohd Rizam

    Published 2009
    “…Five cutpoint determination methods are developed based on regression of competing risks subdistribution. …”
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  16. 16
    Development of robust procedures for partial least square regression with application to near infrared spectral data

    Development of robust procedures for partial least square regression with application to near infrared spectral data by Silalahi, Divo Dharma

    Published 2021
    “…To fill-in the gap in the literature, a new robust procedure in wavelength selection based on input scaling method is developed using Filter-Wrapper method. …”
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  17. 17
    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data

    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

    Published 2016
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  18. 18
    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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  19. 19
    Artificial neural networks for water level prediction based on Z-score technique in Kelantan river / Khairah Jaafar ...[et al.]

    Artificial neural networks for water level prediction based on Z-score technique in Kelantan river / Khairah Jaafar ...[et al.] by Jaafar, Khairah, Ismail, Nurlaila, Tajjudin, Mazidah, Adnan, Ramli, Rahiman, Mohd Hezri Fazalul

    Published 2018
    “…The ANN model was formulated to simulate water level using feedforward algorithm. Readings from 6 stations from rainfall stations showed that S1, S2, S3 and S6 code station while S1 and S2 for water level station were significant value based on ZScore processing method. …”
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  20. 20
    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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