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  1. 1
    Optimal placement of static VAR compensator using genetic algorithms

    Optimal placement of static VAR compensator using genetic algorithms by Mustafa, Mohd. Wazir, Wong, Yan Chiew

    Published 2008
    “…Genetic Algorithms (GAs) are stochastic searching algorithms that make the searching process jumps randomly from point to point, thus allowing escape from the local optimum, and search for many sub-optimum points in parallel.This paper presents an evolutionary computation algorithm for enhancing voltage stability. …”
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  2. 2
    Optimization of neural network through genetic algorithm searches for the prediction of international crude oil price based on energy products prices

    Optimization of neural network through genetic algorithm searches for the prediction of international crude oil price based on energy products prices by Chiroma, Haruna, Ya’u Gital, Abdulsalam, Abubakar, Adamu, Usman, Mohammed Joda, Waziri, Usman

    Published 2014
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  3. 3
    A variable-capacity-based fuzzy random facility location problem with VaR objective

    A variable-capacity-based fuzzy random facility location problem with VaR objective by Wang, Shuming, Watada, Junzo, Shamsul Bahar, Yaakob, Prof. Madya

    Published 2010
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  4. 4
    Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method

    Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

    Published 2023
    “…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
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  5. 5
    Optimal location and sizing of SVC using Particle Swarm Optimization technique

    Optimal location and sizing of SVC using Particle Swarm Optimization technique by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

    Published 2011
    “…Particle Swarm Optimization (PSO) is population-based stochastic search algorithms approaches as the potential techniques to solving such a problem. …”
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  6. 6
    Transmission loss minimization using SVC based on particle swarm optimization

    Transmission loss minimization using SVC based on particle swarm optimization by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

    Published 2011
    “…This paper describes optimal sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. …”
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  7. 7
    Development of multi-objective Chaotic Immune Symbiotic Organisms Search (CISOS) algorithm for facts device installation in voltage security control / Mohamad Khairuzzaman Mohamad Zamani

    Development of multi-objective Chaotic Immune Symbiotic Organisms Search (CISOS) algorithm for facts device installation in voltage security control / Mohamad Khairuzzaman Mohamad... by Mohamad Zamani, Mohamad Khairuzzaman

    Published 2019
    “…The CISOS integrates the element of Chaotic Local Search and cloning into the original SOS algorithm. …”
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  8. 8
    The study of ant colony optimization (ACO) parameters for STATCOM optimization / Melor Md Hodari

    The study of ant colony optimization (ACO) parameters for STATCOM optimization / Melor Md Hodari by Md Hodari, Melor

    Published 2010
    “…Past studies have reported several possible techniques such as optimal reactive power dispatch, optimal capacitor placement; transformer tap setting and static VAR compensator are solutions for reducing voltage collapse occurrences. …”
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  9. 9
    The study of ant colony optimization (ACO) parameters for STATCOM optimization: article / Melor Md Hodari

    The study of ant colony optimization (ACO) parameters for STATCOM optimization: article / Melor Md Hodari by Md Hodari, Melor

    Published 2010
    “…Past studies have reported several possible techniques such as optimal reactive power dispatch, optimal capacitor placement; transformer tap setting and static VAR compensator are solutions for reducing voltage collapse occurrences. …”
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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    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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  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
    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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  19. 19
    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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  20. 20
    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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