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  1. 1
    Flock optimization algorithm-based deep learning model for diabetic disease detection improvement

    Flock optimization algorithm-based deep learning model for diabetic disease detection improvement by Balasubramaniyan, Divager, Husin, Nor Azura, Mustapha, Norwati, Mohd Sharef, Nurfadhlina, Mohd Aris, Teh Noranis

    Published 2024
    “…Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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  2. 2
    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain

    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

    Published 2020
    “…Thus, a reliable optimization technique such as Nature Inspired Metaheuristic Algorithms (NIMA) is crucial to address this issue. …”
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  3. 3
    Estimation of transformers health index based on condition parameter factor and hidden Markov model

    Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

    Published 2018
    “…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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  4. 4
    Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture

    Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

    Published 2010
    “…The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. …”
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  5. 5
    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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  6. 6
    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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  7. 7
    A systematic review of recurrent neural network adoption in missing data imputation

    A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

    Published 2025
    “…Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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  8. 8
    A systematic review of recurrent neural network adoption in missing data imputation

    A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

    Published 2025
    “…Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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  9. 9
    Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

    Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA by Zahari, Taha, Farzad, Tahriri, Siti Zawiah, Md Dawal

    Published 2014
    “…An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
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  10. 10
    Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model

    Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model by Chan, Chin Tiong

    Published 2019
    “…The required memory of this algorithm is also time independent. In addition, the optimal state sequence obtained by the EVRA algorithm is the same as that obtained by the classical Viterbi algorithm for HHMM.…”
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  11. 11
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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  12. 12
    Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines

    Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines by Noroziroshan, Alireza

    Published 2009
    “…Due to NP-hard nature of sequencing problem in mixed model assembly line, a genetic algorithm is applied to cope with problem complexity and obtain a near optimal solution in a reasonable amount of time. …”
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  13. 13
    Optimization of Assembly Sequence Planning Using Soft Computing Approaches: A Review

    Optimization of Assembly Sequence Planning Using Soft Computing Approaches: A Review by Muhammad Arif, Abdullah, M. F. F., Ab Rashid, Z., Ghazalli

    Published 2019
    “…This review focused on ASP modeling approach, optimization algorithms and optimization objectives. …”
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  14. 14
    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
    “…An example of the DNN model is the Attentive Sequence-to-Sequence (Seq2Seq) model that was first created to tackle a problem setting in language processing. …”
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  15. 15
    Energy efficient modeling and optimization for assembly sequence planning using moth flame optimization

    Energy efficient modeling and optimization for assembly sequence planning using moth flame optimization by Abdullah, Arif, M. F. F., Ab Rashid, Ponnambalam, S. G., Zakri, Ghazalli

    Published 2019
    “…The problem was then optimized using moth flame optimization (MFO) and compared with well-established algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). …”
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  16. 16
    Modelling of Assembly Sequence Planning Problem using Base Part Concept

    Modelling of Assembly Sequence Planning Problem using Base Part Concept by Muhamad Arif, Abdullah, M. F. F., Ab. Rashid, Z., Ghazalli, N. M. Z., Nik Mohamed, A. N., Mohd Rose

    Published 2018
    “…Recently, various research works have been done to optimize the ASP problem using different optimization algorithms. …”
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  17. 17
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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  18. 18
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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  19. 19
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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  20. 20
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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