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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
    “…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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  2. 2
    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources

    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

    Published 2023
    “…The single-based metaheuristics replaces the mutation in the genetic algorithm. …”
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  3. 3
    Surface roughness optimization based on hybrid harmony search and artificial bee colony algorithm in electric discharge machining process

    Surface roughness optimization based on hybrid harmony search and artificial bee colony algorithm in electric discharge machining process by Deris A.M., Solemon B.

    Published 2023
    Conference Paper
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  4. 4
    Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines

    Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

    Published 2019
    “…The selected algorithms for this paper are Artificial Neural Network, Support Vector Machine and Random Forest. …”
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  5. 5
    Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines

    Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

    Published 2019
    “…This paper discusses on the evaluation of machine learning algorithms in predicting CO2 internal corrosion rate. …”
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  6. 6
    Flexible job shop scheduling using priority heuristics and genetic algorithm

    Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

    Published 2010
    “…The relevant operation is processed by only one of the uniform machines in that stage. Due to Non-deterministic Polynomial-time hard (NP-hard) nature of problem, in order to generate good solution in a reasonable computation time two solution methodologies are proposed. …”
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  7. 7
    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim

    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

    Published 2008
    “…This paper concentrates on the design and implement of the grid system for study of adaptive job scheduling algorithm based on GridSim. The common problems of job scheduling in grid system like heterogeneous of jobs, resources and dynamic an arrival time of new jobs significantly changes, can be deal with this solution. …”
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  8. 8
    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes

    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
    “…A Pareto optimal set is a set of solutions that are non-dominated solutions frontier. …”
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    Book Chapter
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  9. 9
    Damping power system oscillation using elitist differential search algorithm in multi machine power system

    Damping power system oscillation using elitist differential search algorithm in multi machine power system by Niamul Islam N., Hannan M.A., Mohamed A., Hussain S.

    Published 2023
    “…In this paper, damping power system oscillations is presented using the Elitist differential search algorithm (Elitist-DSA) in a multi-machine system. …”
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  10. 10
    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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  11. 11
    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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  12. 12
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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  13. 13
    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
    “…EDI GmbH in collaboration with Karlsruhe Institute of Technology (KIT) are working on the solution (AI-based tool for predictive process optimization for chemical plants) for the above-mentioned problem. …”
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    Final Year Project
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  14. 14
    Application of the bees algorithm for constrained mechanical design optimisation problem

    Application of the bees algorithm for constrained mechanical design optimisation problem by Kamaruddin, Shafie, Abd Latif, Mohd Arif Hafizi

    Published 2019
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  15. 15
    Cost-based hybrid flow shop scheduling with uniform machine optimization using an improved tiki-taka algorithm

    Cost-based hybrid flow shop scheduling with uniform machine optimization using an improved tiki-taka algorithm by Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

    Published 2024
    “…The cost-based HFSS model and TTA algorithm have been tested using benchmark and case study problems. …”
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  16. 16
    A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network

    A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

    Published 2024
    “…The ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). …”
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  17. 17
    Voltage stability index prediction by using genetics algorithm-based machine learning (GBML) technique / Zainab Mohd Ghazali

    Voltage stability index prediction by using genetics algorithm-based machine learning (GBML) technique / Zainab Mohd Ghazali by Mohd Ghazali, Zainab

    Published 2007
    “…The proposed technique is using Genetic Algorithms-Based Machine Learning (GBML) to predict the voltage stability index. …”
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  18. 18
    Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems

    Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems by Ariafar, Shahram

    Published 2012
    “…Comparison of the results with an adapted algorithm from the literature, in terms of the quality of solutions (material handling cost) shows that the proposed algorithm produces better solutions with a maximum of 0.08% error compared to 0.12% error in the benchmarked algorithm. …”
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  19. 19
    Extreme learning machine for user location prediction in mobile environment

    Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media A., Abu Osman, Md. Tap

    Published 2011
    “…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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  20. 20
    A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction

    A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

    Published 2021
    “…Finally, a prospective architecture of machine learning-based palm oil yield prediction has been proposed based on the critical evaluation of existing related studies. …”
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