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  1. 1
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  2. 2
    Base drag estimation in suddenly expanded supersonic flows using backpropagation genetic and recurrent neural networks

    Base drag estimation in suddenly expanded supersonic flows using backpropagation genetic and recurrent neural networks by Jaimon, Dennis Quadros, Prashanth, T., Khan, Sher Afghan

    Published 2022
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  3. 3
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  4. 4
    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation

    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

    Published 2020
    “…The predictions of BNN and RF exhibit the least mean absolute error of 3.2 and 2.57, respectively, and both can generalize the pressure loss calculation. The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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  5. 5
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  6. 6
    Estimation of optimal machining control parameters using artificial bee colony

    Estimation of optimal machining control parameters using artificial bee colony by Norfadzlan, Yusup, Arezoo, Sarkheyli, Azlan, Mohd Zain, Siti Zaiton, Mohd Hashim, Norafida, Ithnin

    Published 2013
    “…Five machining control parameters that are optimized using ABC algorithm include traverse speed (V), waterjet pressure (P), standoff distance (h), abrasive grit size (d) and abrasive flow rate (m). …”
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  7. 7
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  8. 8
    Sensitivity analysis and optimization of a cardiovascular lumped parameter model for patient-specific modelling

    Sensitivity analysis and optimization of a cardiovascular lumped parameter model for patient-specific modelling by Siti Munirah, Muhammad Ali, El-Bouri, Wahbi, Wan Naimah, Wan Ab Naim, Mohd Jamil, Mohamed Mokhtarudin

    Published 2025
    “…This study presents a framework that enhances parameter estimation in lumped parameter cardiovascular models by combining sensitivity analysis for parameter selection with multi-objective genetic algorithm optimization. …”
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  9. 9
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  10. 10
    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
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  11. 11
    Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat

    Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

    Published 2024
    “…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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  12. 12
    Artificial intelligence modelling approach for the prediction of CO-rich hydrogen production rate from methane dry reforming

    Artificial intelligence modelling approach for the prediction of CO-rich hydrogen production rate from methane dry reforming by Ayodele B.V., Mustapa S.I., Alsaffar M.A., Cheng C.K.

    Published 2023
    “…The dataset employed for the ANN modeling was obtained using a central composite experimental design. The input parameters consisted of CH4 partial pressure, CO2 partial pressure, and reaction temperature, while the target parameters included the rate of CO and H2 production. …”
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  13. 13
    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS

    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…It was found that (by the Group Method of Data Handling algorithm), length of the pipe, wellhead pressure, and angle of inclination have a pronounced effect on the pressure drop estimation under these conditions. …”
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  14. 14
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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  15. 15
    Artificial intelligence modelling approach for the prediction of CO-rich hydrogen production rate from methane dry reforming

    Artificial intelligence modelling approach for the prediction of CO-rich hydrogen production rate from methane dry reforming by Ayodele, Bamidele V., Siti Indati, Mustapa, Alsaffar, May Ali, Cheng, C. K.

    Published 2019
    “…The dataset employed for the ANN modeling was obtained using a central composite experimental design. The input parameters consisted of CH4 partial pressure, CO2 partial pressure, and reaction temperature, while the target parameters included the rate of CO and H2 production. …”
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  16. 16
    Environmental factors and spatial heterogeneity affect occupancy estimates of waterbirds in Peninsular Malaysia

    Environmental factors and spatial heterogeneity affect occupancy estimates of waterbirds in Peninsular Malaysia by Chukwuemeka, Onwuka Martins, Oluwatobi, Emmanuel Olaniyi, Hussin, Mohamed Zakaria

    Published 2021
    “…The maximum and minimum weights of the factors for waterbirds in PIW were water turbidity and electrical conductivity, while at PW they were atmospheric pressure and six water parameters. Large areas of Putrajaya Wetland were classified as more suitable for waterbirds than Paya Indah Wetland due to the favourable water pH, atmospheric pressure and land cover (forage availability). …”
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  17. 17
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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  18. 18
    Prediction of base pressure in a suddenly expanded flow process at supersonic mach number regimes using ANN and CFD

    Prediction of base pressure in a suddenly expanded flow process at supersonic mach number regimes using ANN and CFD by Quadros, Jaimon Dennis, Khan, Sher Afghan

    Published 2020
    “…The importance of input parameters influencing base pressure was estimated by using the ANN weight coefficients. …”
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  19. 19
    Prediction of base pressure in a suddenly expanded flow the processes at supersonic Mach Number Regimes using ANN and CFD

    Prediction of base pressure in a suddenly expanded flow the processes at supersonic Mach Number Regimes using ANN and CFD by Quadros, Jaimon Dennis, Khan, Sher Afghan

    Published 2020
    “…The importance of input parameters influencing base pressure was estimated by using the ANN weight coefficients. …”
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  20. 20
    The Modelling Of Tyre Rotation Behaviour With Tyre Pressure Monitoring System

    The Modelling Of Tyre Rotation Behaviour With Tyre Pressure Monitoring System by Goh, Yik Choong

    Published 2017
    “…For example, the important parameter such as pneumatic pressure captured from the tyre is not in real-time, thus it may become worst when there is air leakage. …”
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