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  1. 1
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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  2. 2
    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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  3. 3
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The adoption of DNN method into chatbot application produces a new generation chatbot that called as Generative-Based Chatbot. …”
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  4. 4
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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  5. 5
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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  6. 6
    Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform

    Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform by Abdul Rashid, Abdul Hadi

    Published 2014
    “…Overall, an algorithm showing the combination method of both GA and DCT was successfully developed. …”
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  7. 7
    ARTIFICIAL IMMUNE ALGORITHM BASED GRAVIMETRIC FLUID DISPENSING MACHINE

    ARTIFICIAL IMMUNE ALGORITHM BASED GRAVIMETRIC FLUID DISPENSING MACHINE by Yap, David F. W., Koh, S. P., Tiong, S. K., Sim, Edwin Y. S., Yaw, M. W.

    Published 2011
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  8. 8
    Performance optimization of simultaneous machine and automated guided vehicle scheduling using fuzzy logic controller based genetic algorithm.

    Performance optimization of simultaneous machine and automated guided vehicle scheduling using fuzzy logic controller based genetic algorithm. by Sulaiman, Shamsuddin, Mohd Ariffin, Mohd Khairol Anuar, Badakshian, Mostafa

    Published 2012
    “…Previously, genetic algorithm (GA) is considered as a heuristic method to solve AGVscheduling problem. …”
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  9. 9
    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems

    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…One of the more recent global optimization tools in the area of discrete optimization is known as the discrete filled function method. …”
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  10. 10
    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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  11. 11
    Direct Adaptive Predictive Control For Wastewater Treatment Plant

    Direct Adaptive Predictive Control For Wastewater Treatment Plant by Shair, Ezreen Farina, Abu Bakar, Norazhar, Mohd Nor, Arfah Syahida, Mohd Azam, Sazuan Nazrah, Mohd Sobran, Nur Maisarah, Zainal Abidin, Amar Faiz

    Published 2012
    “…The adaptive control structure is based on the linear model of the process and combined with numerical algorithm for subspace state space system identification (N4SID). …”
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  12. 12
    Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay

    Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Raja Mohd Taufika, Raja Ismail

    Published 2019
    “…This paper addresses a data-driven neuroendocrine-PID tuning for the control of a two-input-two-output (TITO) coupled tank system with sto-chastic input time delay based on safe experimentation dynamics (SED). The SED algorithm is an optimization method used as data-driven tools to find the optimal control parameters by using the input-output (I/O) data measurement in an actual system. …”
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  13. 13
    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob

    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

    Published 2022
    “…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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  14. 14
    Identification of dynamic linear models of automotive palm bio-diesel engine for real-time speed control applications

    Identification of dynamic linear models of automotive palm bio-diesel engine for real-time speed control applications by Azuwir, Mohd Nor, Mohd Zaki, Ab. Muin, Prof. Dr., Abdul Hamid, Adom, Prof. Madya Dr.

    Published 2011
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  15. 15
    Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System

    Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

    Published 2009
    “…The results demonstrate that the proposed optimal maintenance scheduling method yields much better system value rather than sequencing methods. …”
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  16. 16
    Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach

    Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

    Published 2025
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  17. 17
    Clarity-optimized wavelet with autoencoder-ReliefF ranking for enhanced UHF PD signal feature extraction

    Clarity-optimized wavelet with autoencoder-ReliefF ranking for enhanced UHF PD signal feature extraction by Azam, Kayser M.K., Othman, Mohamadariff, Hossain, A K M Zakir, Kumar, Dhruba, Wong, Jee Keen Raymond, Illias, Hazlee Azil, Abdul Latef, Tarik, Mat Ibrahim, Masrullizam

    Published 2025
    “…To address the challenge of identifying the most discriminative features, this work integrates advanced feature ranking algorithms, namely, auto-encoder-based ranking and the ReliefF method. …”
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  18. 18
    Development of optimized maintenance scheduling model for coal-fired power plant boiler

    Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

    Published 2023
    “…Literature revealed that mathematical methods and metaheuristic algorithms are common approaches in solving combinatorial optimization problems with a large search space in a reasonable computational run time. …”
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  19. 19
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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    Undergraduates Project Papers
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  20. 20
    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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