Search Results - (( cost selection method algorithm ) OR ( java simulation optimization 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
    Optimizing Ram Testing Method For Test Time Saving Using Automatic Test Equipment

    Optimizing Ram Testing Method For Test Time Saving Using Automatic Test Equipment by Kesavan Prabagaran, Premkumar

    Published 2017
    “…A memory Build-in Self-test (BIST) design with capability of algorithm failing sequence capture have been developed to implement in the Automate Test Equipment (ATE) flow for production screen. 3 selected algorithm have been tested on the 8 detect units in ATE flow to prove the concept of this method. …”
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  10. 10
    Multi-objective selection and structural optimization of the gantry in a gantry machine tool for improving static, dynamic, and weight and cost performance

    Multi-objective selection and structural optimization of the gantry in a gantry machine tool for improving static, dynamic, and weight and cost performance by Besharati, S.R., Dabbagh, V., Amini, H., Sarhan, Ahmed Aly Diaa Mohammed, Akbari, J., Abd Shukor, Mohd Hamdi, Ong, Zhi Chao

    Published 2016
    “…In this investigation, the multi-objective selection and optimization of a gantry machine tool is achieved by analytic hierarchy process, multi-objective genetic algorithm, and Pareto-Edgeworth-Grierson-multi-criteria decision-making method. …”
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  11. 11
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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  12. 12
    Selection of access network using cost function method in heterogeneous wireless network

    Selection of access network using cost function method in heterogeneous wireless network by Mohamad Tahir, Hatim, Al-Ghushami, Abdullah Hussein, Yahya, Zainor Ridzuan

    Published 2014
    “…This method covers the weight distribution and cost factor techniques.The weight distribution is used to measure different weights for existing wireless network based on the user's preference and mobile terminal power.The cost factor technique is also used to identify the cost for performing handover target by considering every network parameters and its weight.Results obtained showed that the algorithm has the ability to increase user's satisfaction compared to other algorithms, which consistently choose one accessible network.…”
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  13. 13
    Performance-aware cost-effective brokering and load balancing algorithms for data center in large scale cloud computing

    Performance-aware cost-effective brokering and load balancing algorithms for data center in large scale cloud computing by Naha, Ranesh Kumar

    Published 2015
    “…In order to make our proposed method cost efficient, we developed Load Aware Over Cost algorithm which is 8% cost effective comparing with Load Aware algorithm. …”
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  14. 14
    Improved stereo matching algorithm based on census transform and dynamic histogram cost computation

    Improved stereo matching algorithm based on census transform and dynamic histogram cost computation by Kadmin, Ahmad Fauzan, Hamzah, Rostam Affendi, Abd Manap, Nurulfajar, Hamid, Mohd Saad, Abd Gani, Shamsul Fakhar

    Published 2021
    “…This method utilised modified dynamic cost computation in the matching cost stage. …”
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  15. 15
    Optimization of Turning Parameters to Minimize Production Cost using Genetic Algorithm

    Optimization of Turning Parameters to Minimize Production Cost using Genetic Algorithm by M. F. F., Ab Rashid, Shah, Izwandi

    Published 2009
    “…Therefore, the optimum parameter setting is required because it related to certain quality characteristics such as the unit production cost. This paper presents the study to minimize production cost for CNC turning process by using genetic algorithm (GA) method with some modification. …”
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  16. 16
    Proportional-integral control optimization using imperialist competitive algorithm

    Proportional-integral control optimization using imperialist competitive algorithm by Soheilirad, Mohammadsoroush

    Published 2012
    “…In this dissertation, an attempt has been made to design and implement the PID Controllers by employing the Imperialist Competitive Algorithm (ICA) technique as well as the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm, for a selected plant. …”
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  17. 17
    Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction

    Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction by Abd Razak, Siti Safwana

    Published 2019
    “…Then for matching cost, the proposed SMA combine one of matching cost method with some threshold adjustment to reduces the radiometric distortions. …”
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  18. 18
    Software defect prediction framework based on hybrid metaheuristic optimization methods

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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  19. 19
    The development of deformable bodies collision response algorithm for interactive virtual environment

    The development of deformable bodies collision response algorithm for interactive virtual environment by Mohd. Shuaib, Norhaida, Bade, Abdullah, Daman, Daut, Sunar, Mohd. Shahrizal

    Published 2006
    “…It is an optimization algorithm that selects small areas for deformation processing based on equilibrium state. …”
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  20. 20
    An Improved Evolutionary Algorithm in Formulating a Diet for Grouper

    An Improved Evolutionary Algorithm in Formulating a Diet for Grouper by Cai-Juan, Soong, Abd Rahman, Rosshairy, Ramli, Razamin

    Published 2023
    “…Hence, in this paper, an improved EA method known as the SR-SD-EA is proposed highlighting three important EA operators, which are initialization, selection and mutation. …”
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