Search Results - parallel solution ((modified algorithm) OR (mining algorithm))

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  1. 1

    Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour by Hadi , Naghavipour

    Published 2022
    “…As a result of this mapping study, five major hybridization strategies were identified in which two-third of solutions have been based on modifying algorithm operators or integration with another metaheuristic. …”
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    Thesis
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    Parallel computation of maass cusp forms using mathematica by Chan, Kar Tim

    Published 2013
    “…Our parallel programme comprises of two important parts namely the pullback algorithm and also the Maass cusp form algorithm. …”
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    Thesis
  6. 6

    A New Technique To Design Coating Structure For Energy Saving Glass Using The Genetic Algorithm by Azmin, Farah Ayuni

    Published 2017
    “…After modifying these shapes using the Genetic algorithm and Parallel Genetic algorithm, the outputs are simulated in the Computer Simulation Technology (CST) simulation software. …”
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    Thesis
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    Parallel multiple tabu search for multiobjective Urban Transit Scheduling Problem by Uvaraja, Vikneswary, Lai, Soon Lee, Abd Rahmin, Nor Aliza, Hsin, Vonn Seow

    Published 2020
    “…A set covering model was then adopted to minimize the number of buses and drivers simultaneously. A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. …”
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    Article
  9. 9

    Optimizing OLAP heterogeneous computing based on Rabin-Karp algorithm by Alzeini, Haytham I M, Hameed, Shihab A., Habaebi, Mohamed Hadi

    Published 2013
    “…In this paper, through experimental results and based on Rabin-Karp Algorithm; we propose an optimized heterogeneous solution that takes into account the benefits and the boundaries in order to achieve a better OLAP performance in terms of response time with three times gain. …”
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    Proceeding Paper
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    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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    Monograph
  12. 12

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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    Thesis
  13. 13

    Greedyzero-based scheduling algorithm to route in optical low stage interconnection networks by Moudi, Mehrnaz

    Published 2012
    “…Then the GreedyZero algorithm is developed to minimize the number of passes approximately 30% in compare with Zero algorithm to route all the inputs to outputs without any crosstalk. …”
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    Thesis
  14. 14

    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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    Article
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    Simulation of single-phase shunt active power filter with fuzzy logic controller for power quality improvement by Usman, Hamisu, Hizam, Hashim, Mohd Radzi, Mohd Amran

    Published 2013
    “…Traditional passive filter was the earliest solution for mitigating harmonics produced by non-linear loads, but passive filter have the disadvantages of series and parallel resonances with the supply source impedance and it's heavy in size. …”
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    Conference or Workshop Item