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  1. 1
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…So, the integration of Artificial Neural Network (ANN) with an Expert System for material classification was explored. The computational tool, Matlab was proposed for classification with Levenberg-Marquardt training algorithm, which provided faster rate of convergence for feed forward network. …”
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  2. 2
    Dual-head marking performance optimisation via evolutionary solutions

    Dual-head marking performance optimisation via evolutionary solutions by Koh J., Tiong S.K., Aris I.B., Mahmoud S.

    Published 2023
    “…This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. …”
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  3. 3
    Optimisation of vehicle routing problem with time windows using Harris Hawks optimiser

    Optimisation of vehicle routing problem with time windows using Harris Hawks optimiser by Chai, S. W., Kamaluddin, M. R., Ab Rashid, M. F. F.

    Published 2022
    “…This problem has been widely studied and optimised using different methods. Since the performance of algorithms in different problems is dissimilar, the study to optimise the VRPTW is ongoing. …”
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  4. 4
    Classification System for Heart Disease Using Bayesian Classifier

    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…This system was mainly developing using java programming. Apache Tom cat was used as a server in order to run the application smoothly. …”
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  5. 5
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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  6. 6
    An improvement of back propagation algorithm using halley third order optimisation method for classification problems

    An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

    Published 2020
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  7. 7
    Evaluating JA-ABC5 hyperparameter optimisation with classifiers

    Evaluating JA-ABC5 hyperparameter optimisation with classifiers by Ravindran, Nadarajan, Noorazliza, Sulaiman, Junita, Mohamad-Saleh

    Published 2024
    “…The Wisconsin dataset is used to evaluate the performance of these classifiers, and the hyperparameters are optimised using the JA-ABC5 algorithm. …”
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  8. 8
    Hybrid genetic algorithm for uncapacitated university examination timetabling problem

    Hybrid genetic algorithm for uncapacitated university examination timetabling problem by Ishak, Suhada

    Published 2015
    “…All proposed algorithms are coded in C using Microsoft Visual C++ 6.0 as the compiler. …”
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  9. 9
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  10. 10
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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  11. 11
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisa­tion Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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  12. 12
    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines

    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines by Ismail, Napsiah, Musharavati, Farayi, Hamouda, Abdel Magid Salem, Ramli, Abdul Rahman

    Published 2008
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  13. 13
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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  14. 14
    Hybrid genetic algorithm for university examination timetabling problem

    Hybrid genetic algorithm for university examination timetabling problem by Ishak, Suhada, Lee, Lai Soon, Ibragimov, Gafurjan

    Published 2016
    “…These new local optimisation techniques will arrange the timeslots and exams using new explicit equations, if and only if, the modification will reduce the penalty cost function. …”
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  15. 15
    Kernel and multi-class classifiers for multi-floor wlan localisation

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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  16. 16
    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin

    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin by Nasaruddin, Nor Intan Shafini

    Published 2012
    “…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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  17. 17
    Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II

    Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II by M. F. F., Ab Rashid, N. M. Zuki, N. M., A. N. M., Rose

    Published 2016
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  18. 18
    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam

    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

    Published 2023
    “…Consequently, seeking managing of reservoir optimisation operations had always been at the forefront and to improve managing, algorithms have had been presented over the past few decades, beginning with conventional algorithms, followed by heuristic algorithms, and finally, the meta-heuristic algorithms (MHAs). …”
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  19. 19
    Locust- inspired meta-heuristic algorithm for optimising cloud computing performance

    Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

    Published 2023
    “…This algorithm can also be used for task scheduling. The proposed algorithm efficiently maps and achieves the objective function for server consolidation, optimising energy consumption, VM migrations, and server utilisation. …”
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  20. 20
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The results reveal that the proposed hybrid algorithm is capable of achieving classification accuracy values of (95.82 % and 97.68 %), detection rates values of (95.8 % and 99.3 %) and false alarm rates values of (0.083 % and 0.045 %) on both KDD CUP 99 and NSL KDD. …”
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