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  1. 1
    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
    “…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
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  2. 2
    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
    “…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
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  3. 3
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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  4. 4
    An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines

    An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines by Bala, A., Ismail, I., Ibrahim, R., Sait, S.M., Oliva, D.

    Published 2020
    “…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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  5. 5
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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  6. 6
    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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  7. 7
    Clustering of rainfall data using k-means algorithm

    Clustering of rainfall data using k-means algorithm by Mohd Sham, Mohamad, Yuhani, Yusof, Ku Muhammad Na’im, Ku Khalif, Mohd Khairul Bazli, Mohd Aziz

    Published 2019
    “…Clustering algorithms in data mining is the method for extracting useful information for a given data. …”
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  8. 8
    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm

    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

    Published 2013
    “…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. …”
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  9. 9
    A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation

    A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation by Rong, Li, Shari, Zalina, Ab Kadir, Mohd Zainal Abidin

    Published 2025
    “…This study systematically examined recent research trends in multi-objective optimization (MOO) for building performance from 2020 to 2024 and proposed a conceptual framework integrating intelligent algorithms, simulation tools, and climate adaptation strategies. …”
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  10. 10
    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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  11. 11
    Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm

    Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari

    Published 2024
    “…These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods.…”
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  12. 12
    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set

    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

    Published 2022
    “…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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  13. 13
    A decision support system for improving forecast using genetic algorithm and tabu search

    A decision support system for improving forecast using genetic algorithm and tabu search by Ismail, Zuhaimy

    Published 2008
    “…and their combinations using trial and error method is time consuming. Hence, a good optimization technique is required to select the best parameter value to minimize the fitness function. …”
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  14. 14
    Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review

    Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

    Published 2024
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  15. 15
    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Mohd Sharif, Zakaria, Mohammad Fadhil, Abas, Fatimah, Dg Jamil, Norhafidzah, Mohd Saad, Addie, Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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  16. 16
    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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  17. 17
    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Zakaria, Mohd Sharif, Abas, Mohammad Fadhil, Dg Jamil, Fatimah, Mohd Saad, Norhafidzah, Hashim, Addie Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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  18. 18
    The optimization of stepping stone detection : packet capturing steps

    The optimization of stepping stone detection : packet capturing steps by Omar, Mohd. Nizam, Maarof, Mohd. Aizaini, Zainal, Anazida

    Published 2006
    “…The proposed method is to use small size of user buffer and kernel buffer. …”
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  19. 19
    The optimization of stepping stone detection: packet capturing steps

    The optimization of stepping stone detection: packet capturing steps by Omar, Mohd. Nizam, Maarof, Mond. Aizaini, Zainal, Anazida

    Published 2006
    “…The proposed method is to use small size of user buffer and kernel buffer. …”
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  20. 20
    The optimization of stepping stone detection: Packet capturing steps

    The optimization of stepping stone detection: Packet capturing steps by Omar, Mohd Nizam, Maarof, Mohd Aizaini, Zainal, Anazida

    Published 2006
    “…From the result, it is proven that the proposed method (by using small size of buffer) gives better result.The research concludes that by using the proposed method, the response time can be improve.…”
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