Search Results - (( using action method algorithm ) OR ( set optimization method algorithm ))

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  1. 1

    A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

    Published 2011
    “…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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    Monograph
  2. 2

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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    Thesis
  3. 3

    Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani by Abdul Ghani, Nur Syafiqah

    Published 2021
    “…Ant colony optimization has been inspired by the action of the actual ant colony and is used to solve discrete optimization issues. …”
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    Student Project
  4. 4

    Multi-Objectives Optimization Of Energy Consumption Of IKM Bintulu Buildings Towards Energy Saving by Othman, Muhamad Naim

    Published 2017
    “…The methods are differs by the setting parameter of temperature of24°C and lighting of 500 Lux for optimization method, while 18°C air conditioning temperature and 540 Lux for without optimization method. …”
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    Thesis
  5. 5

    Harris Hawk Optimization-Based Deep Neural Networks Architecture for Optimal Bidding in the Electricity Market by Kavita Jain, Muhammed Basheer Jasser, Muzaffar Hamzah, Akash Saxena, Ali Wagdy Mohamed

    Published 2022
    “…In this research, we provide HHO-NN (Harris Hawk Optimization-Neural network), a novel algorithm based on Harris Hawk Optimization (HHO) that is capable of fast convergence when compared to previous evolutionary algorithms for automatically searching for meaningful multilayered perceptron neural networks (MPNNs) topologies for optimal bidding. …”
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    Article
  6. 6

    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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    Thesis
  7. 7

    Modular motor driver with torque control for gripping mechanism by How D.N.T., Baharuddin M.Z., Mohideen S.S.K., Sahari K.S.M., Anuar A.

    Published 2023
    “…Using the same hardware configuration, the different algorithms produced different outcomes on the output of the controller. …”
    Conference paper
  8. 8

    A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Abbas, Kassim A.

    Published 2010
    “…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
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    Article
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  10. 10

    Existence and uniqueness for the evolutionary impulse control problem using an asynchronous algorithms by Haiour M., Bencheikh Le Hocine M.E.A., Jan R., Himadan A., Boulaaras S.

    Published 2025
    “…Ensuring both the existence and uniqueness of optimal control policies in such settings is paramount for practical implementation and theoretical understanding. …”
    Article
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  12. 12

    Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

    Published 2025
    “…The findings of this study have significant implications for National Oil Companies (NOCs) and operators, facilitating proactive intervention strategies, enhancing transparency in decision-making, and supporting the early monetization of resources. Ultimately, this method improves the protection of project schedules, optimizes infrastructure utilization, and maximizes economic returns and strategic alignment in Malaysia's energy industry.…”
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    Article
  13. 13

    HELM based Reinforcement Learning for Goal Localization by AlDahoul, Nouar, Htike@Muhammad Yusof, Zaw Zaw

    Published 2016
    “…In this paper, reinforcement learning method was utilized to find optimal series of actions to localize the goal region. …”
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    Proceeding Paper
  14. 14

    A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia by Azlan, Abdul Aziz, Zuriani, Mustaffa, Suzilah, Ismail, Nor Azriani, Mohamad Nor, Nurin Qistina, Mohamad Fozi

    Published 2025
    “…However, SES is seen to underperform compared to other models due to parameter selection and initial value setting. Therefore, this study aims to propose a new hybrid model, the Single Exponential Smoothing (SES)-Barnacles Mating Optimization (BMO) algorithm, to estimate the optimal smoothing parameter alpha and initial value that can improve the percentage of forecast accuracy. …”
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    Article
  15. 15

    Hierarchical extreme learning machine based reinforcement learning for goal localization by AlDahoul, Nouar, Htike, Zaw Zaw, Akmeliawati, Rini

    Published 2017
    “…In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. …”
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    Proceeding Paper
  16. 16

    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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    Thesis
  17. 17

    A genetically trained simplified ANFIS controller to control nonlinear MIMO systems by Lutfy, Omar F., Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce

    Published 2011
    “…Consequently, the necessity for the teaching signal required by other techniques has been eliminated. Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
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    Conference or Workshop Item
  18. 18

    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes by Nor Atiqah, Zolpakar, Lodhi, Swati Singh, Pathak, Sunil, Sharma, Mohita Anand

    Published 2020
    “…Multi-objectives Genetic Algorithm (MOGA) is one of many engineering optimization techniques, a guided random search method. …”
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    Book Chapter
  19. 19

    Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm by Ling, Kuok Fong, Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

    Published 2023
    “…This study concludes that the AOA optimization algorithm surpasses other methods in tuning the PID controller for closed-loop DC-DC buck converters.…”
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    Article
  20. 20

    Determining optimal location of static VAR compensator by means of genetic algorithm by Karami, Mahdi, Mariun, Norman, Ab Kadir, Mohd Zainal Abidin

    Published 2011
    “…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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    Conference or Workshop Item