Search Results - parallel distribution ((((graph algorithm) OR (mining algorithm))) OR (ant algorithm))

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  1. 1
    Random sampling method of large-scale graph data classification

    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…After that, we randomly select a subset of data blocks, each being a random sample of the graph dataset, and compute the different graph property distributions. …”
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  2. 2
    Parallel execution of distributed SVM using MPI (CoDLib)

    Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

    Published 2023
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  3. 3
    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing

    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

    Published 2013
    “…Although researches on the load management in the cloud systems is similar to that of traditional parallel and distributed systems in many aspects, essential differences exist between them. …”
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  4. 4
    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System

    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

    Published 2013
    “…A number of benchmark function processes were conducted to assess the performance of proposed FOA (Fly Optimisation Algorithm).…”
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  5. 5
    Generic DNA encoding design scheme to solve combinatorial problems

    Generic DNA encoding design scheme to solve combinatorial problems by Rofilde, Hasudungan

    Published 2015
    “…Currently, data encoding in DNA computing is tightly coupled with an algorithm that solves an instance of the problem. Solving another problem requires developing specific encoding and computations anew to prove DNA encoding and form the algorithm which is costly. …”
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  6. 6
    Host Based Intrusion Detection and Prevention Model Against DDoS Attack in Cloud Computing

    Host Based Intrusion Detection and Prevention Model Against DDoS Attack in Cloud Computing by Jaber, Aws Naser, Mohamad Fadli, Zolkipli, Shakir, Hasan Awni

    Published 2018
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  7. 7
    A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks

    A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks by Chien, Stephen Lim Een, Raja Maamor Shah, Raja Noor Farah Azura, Othman, Mohamed

    Published 2016
    “…The performance parameters and properties of chordal rings have been researched extensively as models for parallel and distributed interconnection topology models since their founding in 1981. …”
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  8. 8
    Solving the optimal reactive power dispatch problem based on moth-flame optimizer for power system operation and planning

    Solving the optimal reactive power dispatch problem based on moth-flame optimizer for power system operation and planning by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Muhammad Ikram, Mohd Rashid, Rebecca Ng, Shin Mei, Nidzamuddeen, Ishak, Hamdan, Daniyal

    Published 2018
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  9. 9
    P2P-Based Image Recognition for Component Tracking in a Large Engineering Domain

    P2P-Based Image Recognition for Component Tracking in a Large Engineering Domain by Amir, Amiza, Muhamad Amin , Anang Hudaya, Khan, Asad I.

    Published 2011
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  10. 10
    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata

    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

    Published 2018
    “…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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