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  1. 1
    Development of cell formation algorithm and model for cellular manufacturing system

    Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

    Published 2011
    “…In addition, one of the main challenges has been development of efficient algorithm for solving aforementioned model to find exact feasible optimal solution. …”
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  2. 2
    Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm

    Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm by Mimi Muzlina, Mukri

    Published 2024
    “…In the second optimization process, machining parameters such as cutting speed, feed rate, and depth of cut are optimized using a multi-objective genetic algorithm to concurrently lower temperature rise and surface roughness. …”
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  3. 3
    An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system

    An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system by Islam N.N., Hannan M.A., Shareef H., Mohamed A.

    Published 2023
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  4. 4
    Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm

    Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm by W., Safiei, Rahman, M. M., M.Y., Ali

    Published 2024
    “…For future study, other methods or algorithms can be applied in other machining processes to obtain optimum machining parameters.…”
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  5. 5
    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool

    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

    Published 2019
    “…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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  6. 6
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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  7. 7
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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  8. 8
    Route Planning Analysis In Holes Drilling Process Using Magnetic Optimization Algorithm For Electronic Manufacturing Sector

    Route Planning Analysis In Holes Drilling Process Using Magnetic Optimization Algorithm For Electronic Manufacturing Sector by Ismail, Mohd Muzafar, Othman, Mohd Azlishah, Sulaiman, Hamzah Asyrani, Meor Said, Maizatul Alice, Misran, Mohamad Harris, Ramlee, Ridza Azri, Sinnappa, Mohan, Zakaria, Zahriladha, Ahmad, Badrul Hisham, Abd Aziz, Mohamad Zoinol Abidin, Osman, Khairuddin, Sulaiman, Siti Fatimah, Jaafar, Hazriq Izzuan, Jusoff, Kamaruzaman, Nordin, Nur Anis, Othman, Mohd Hafiz, Saealal, Muhammad Salihin, Adam, Asrul, Amer, Hafizah, Zainal Abidin, Amar Faiz, Khalid, Nurul Syahirah, Tunnur, Masturah, Abdul Majid, Masmaria, Suhaimi, Shadia

    Published 2013
    “…Based on this motivation, this paper proposes an approach which is based on the experimentation of Magnetic Optimization Algorithm. …”
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  9. 9
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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  10. 10
    Lévy mutation in artificial bee colony algorithm for gasoline price prediction

    Lévy mutation in artificial bee colony algorithm for gasoline price prediction by Mustaffa, Zuriani, Yusof, Yuhanis

    Published 2012
    “…The purpose is to better exploit promising solutions found by the bees.Such an approach is used to improve the performance of the original ABC in optimizing Least Squares Support Vector Machine hyper parameters.From the conducted experiment, the proposed lvABC shows encouraging results in optimizing parameters of interest.The proposed.lvABC-LSSVM has outperformed existing prediction model, Backpropogation Neural Network (BPNN), in predicting gasoline price.…”
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  11. 11
    Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach

    Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach by Najiha, M. S., M. M., Rahman, K., Kadirgama

    Published 2016
    “…In this paper a genetic algorithm based multi-objective optimization approach is applied in order to predict the optimal machining parameters for the end milling process of aluminium alloy 6061 T6 combined with minimum quantity lubrication (MQL) conditions using waterbased TiO2 nanofluid as cutting fluid. …”
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  12. 12
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…The mMVO based method is then used for identifying the parameters of linear and nonlinear subsystems in the Hammerstein model using the given input and output data. …”
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  13. 13
    Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications

    Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

    Published 2025
    “…This proposal discusses the techniques of optimizing and deploying machine learning algorithms on embedded devices for manufacturing applications; We investigate problems of printed circuit board (PCB) defects and artificial intelligence in embedded system. …”
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  14. 14
    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)

    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…Optimization algorithms can be used to solve Non-deterministic Polynomial (NP) hard problem like system management. …”
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  15. 15
    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol

    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

    Published 2023
    “…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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  16. 16
    Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm

    Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi, Mohd Jaffar, Mai Zurwatul Ahlam, Beiranvand, Hamzeh

    Published 2020
    “…Moreover, at the end of the analysis, the FFA based PSSs design was found to converge faster with low computational cost and produces enhanced optimal PSSs parameters as compared to the other existing algorithms. …”
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  17. 17
    Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales

    Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales by Julirose , Gonzales

    Published 2018
    “…The results using the proposed methodology yields 50 pareto optimal design solutions for every run, allowing the designers the freedom to choose the suitable design. …”
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  18. 18
    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
    “…Hence, in this work, we design an improved Grasshopper Optimization Algorithm (GOA) based ESN. The proposed technique uses a new solution representation with a simplified attraction and repulsion mechanisms to enhance performance. …”
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  19. 19
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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  20. 20
    An enhanced soft set data reduction using decision partition order technique

    An enhanced soft set data reduction using decision partition order technique by Mohammed, Mohammed Adam Taheir

    Published 2017
    “…Also, the accuracy of original soft-set optimal and sub-optimal results have been improved using an intelligent SSR-BPSO-BBO algorithm. …”
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