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  1. 1
    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms

    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

    Published 2021
    “…Based on the ANOVA comparison test results, a 1.25 percent improvement on accuracy and 0.98 percent reduced makespan on task allocation system of VM in cloud computing is observed with the proposed HBAC algorithm.…”
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  2. 2
    Lévy mutation in artificial bee colony algorithm for gasoline price prediction

    Lévy mutation in artificial bee colony algorithm for gasoline price prediction by Mustaffa, Zuriani, Yusof, Yuhanis

    Published 2012
    “…In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. …”
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  3. 3
    Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi

    Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi by Mahmud Affandi, Muhamad Saifullah

    Published 2014
    “…The Artificial Bee Colony (ABC) algorithm technique for solving the problem of optimal location and sizing of DG on distributed systems is presented. …”
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  4. 4
    Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing

    Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

    Published 2018
    “…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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  5. 5
    A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems

    A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems by Tam, Jun Hui, Ong, Zhi Chao, Ismail, Zubaidah, Ang, Bee Chin, Khoo, Shin Yee

    Published 2019
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  6. 6
    Improved tree routing protocol in zigbee networks

    Improved tree routing protocol in zigbee networks by Al-Harbawi, Mostafa Kamil Abdulhusain

    Published 2010
    “…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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  7. 7
    ABC-PSO for vertical handover in heterogeneous wireless networks

    ABC-PSO for vertical handover in heterogeneous wireless networks by Goudarzi, Shidrokh, Hassan, Wan Haslina, Anisi, Mohammad Hossein, Soleymani, Seyed Ahmad, Sookhak, Mehdi, Khan, Muhammad Khurram, Hassan Abdalla Hashim, Aisha, Zareei, Mahdi

    Published 2017
    “…Cloud computing is currently emerging quickly as a client-server technology structure and, currently, providing distributed service applications. …”
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  8. 8
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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  9. 9
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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  10. 10
    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain

    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

    Published 2020
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  11. 11
    A krill herd behaviour inspired load balancing of tasks in cloud computing

    A krill herd behaviour inspired load balancing of tasks in cloud computing by Hasan, Raed Abdulkareem, Mohammed, Muamer N.

    Published 2017
    “…In the cloud computing environment, load balancing – a way of distributing workloads across numerous computing resources, is a vital aspect. …”
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  12. 12
    Enhanced ABC-LSSVM For Energy Fuel Price Prediction

    Enhanced ABC-LSSVM For Energy Fuel Price Prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2014
    “…This paper presents an enhanced Artifi cial Bee Colony (eABC) based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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  13. 13
    Optimize single line to ground fault detection in distribution grid power system using artificial bee colony

    Optimize single line to ground fault detection in distribution grid power system using artificial bee colony by Feryal Ibrahim Jabbar, Feryal Ibrahim Jabbar, Dur Muhammad Soomro, Dur Muhammad Soomro, Mohd Noor Abdullah, Mohd Noor Abdullah, Nur Hanis Mohammad Radzi, Nur Hanis Mohammad Radzi, Mazhar Hussain Baloch, Mazhar Hussain Baloch, Asif Ahmed Rahmoon, Asif Ahmed Rahmoon, Hassan Falah Fakhruldeen, Hassan Falah Fakhruldeen

    Published 2023
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  14. 14
    Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation

    Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation by Islam, Syed Zahurul, Othman, Mohammad Lutfi, Islam, Syed Zahidul

    Published 2021
    “…In this paper, we have analysed the performance of the ZigBeePRO network by applying the shortest path algorithm while delivering energy data from the solar DRG to the SG. …”
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  15. 15
    Power-efficient wireless coverage using minimum number of uavs

    Power-efficient wireless coverage using minimum number of uavs by Sawalmeh A., Othman N.S., Liu G., Khreishah A., Alenezi A., Alanazi A.

    Published 2023
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  16. 16
    Optimum tie switches allocation and DG placement based on maximisation of system loadability using discrete artificial bee colony algorithm

    Optimum tie switches allocation and DG placement based on maximisation of system loadability using discrete artificial bee colony algorithm by Aman, M.M., Jasmon, G.B., Mokhlis, Hazlie, Bakar, Ab Halim Abu

    Published 2016
    “…The proposed algorithm is tested on 16-Bus, 33-Bus and 69-Bus radial distribution test system. …”
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  17. 17
    Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm

    Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm by Mohamad Zunnurain Fauzi

    Published 2023
    “…Therefore, a method which is Artificial Bee Colony (ABC) algorithm is proposed in this project for the optimal location and size of DG used in minimizing power losses and improve voltage profile. …”
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  18. 18
    Artificial bee colony for inventory routing problem with backordering

    Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

    Published 2014
    “…This paper addresses the inventory routing problem with backordering (IRPB) with a one-tomany distribution network, consisting of a single depot and multiple customers for a specified planning horizon. …”
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  19. 19
    Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar

    Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar by Shivashankar , Sukumar

    Published 2017
    “…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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  20. 20
    Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices

    Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices by Ali Abdallah, Ali Emhemed

    Published 2021
    “…Another part of this work focuses on enhancing the stability of the power system using distributed generator (DG). The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
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