Search Results - (( java simulation optimization algorithm ) OR ( waste elimination based algorithm ))

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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
    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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  3. 3
    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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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    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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  8. 8
    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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  9. 9
    Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater

    Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater by Khan M.S.J., Sidek L.M., Kumar P., Alkhadher S.A.A., Basri H., Zawawi M.H., El-Shafie A., Ahmed A.N.

    Published 2025
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  10. 10
    SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment

    SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment by Murad, Saydul Akbar, Zafril Rizal, M. Azmi, Muzahid, Abu Jafar Md, Bhuiyan, Md Khairul Bashar, Saib, Md, Rahimi, Nick, Prottasha, Nusrat Jahan, Bairagi, Anupam Kumar

    Published 2024
    “…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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  11. 11
    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing

    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

    Published 2019
    “…To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. SecPath is evaluated with several variations using 400 nodes in WSN deployments as well as large-scale simulations. …”
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  12. 12
    Energy efficient path reconstruction in wireless sensor network using iPath

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. Energy efficient iPath (E-iPath) is evaluated with several variations of nodes in WSN deployments as well as large-scale simulations. …”
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  13. 13
    Modification and characterization of phytase for animal feed production

    Modification and characterization of phytase for animal feed production by Noorbatcha, Ibrahim Ali, Samsudin, Nurhusna, Mohd. Salleh, Hamzah

    Published 2009
    “…Multiple mutations of M216R/E219R/H17A, M216R/E219R/F254E and some other multiple mutations showed improvement in the binding strength, primarily due to the addition of hydrogen bond with the adjacent residues. Automated docking based on genetic algorithm is used to dock the phytate in the active site and Partial Mean Force (PMF) scoring is used to calculate the strength of the binding before and after mutation.…”
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  14. 14
    Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques

    Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques by Chong, Xiao Wei

    Published 2024
    “…By employing the state-of-the-art You Only Look Once (YOLO) v7 object detection algorithm, the project aims to develop a system capable of accurately detecting and classifying prawns based on their growth stages. …”
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  15. 15
    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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  16. 16
    Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC) manufacturing

    Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)... by Mohd Fazil, Azlan Faizal, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

    Published 2019
    “…The model evaluation flow will use 3 different non-overlapped datasets and comparison of classifiers will be based on recall rate and precision rate. This new framework will be able to provide range of possible recall rate from minimum to maximum, to identify which classifier algorithm performs the best for given dataset. …”
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