Search Results - parallel decision new algorithm

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  1. 1
    Exact parallel plurality voting algorithm for totally ordered object space fault-tolerant systems

    Exact parallel plurality voting algorithm for totally ordered object space fault-tolerant systems by Karimi, Abbas, Zarafshan, Faraneh, Jantan, Adznan, Ramli, Abdul Rahman, Saripan, M. Iqbal, Syed Mohamed, Syed Abdul Rahman Al-Haddad

    Published 2012
    “…Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, they are therefore used to achieve a new parallel plurality voting algorithm by using (n/log n) processors on EREW shared-memory PRAM. …”
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  2. 2
    Parallel strategies on a distributed parallel computer system

    Parallel strategies on a distributed parallel computer system by Alias, Norma

    Published 2004
    “…The formulation of a new parallel iteration methods are created to solve the parabolic equations in one, two and three dimensions run on a distributed parallel computer systems on the homogeneous parallel machines with 20 PC Intel Pentium IV, speed 1.6MHz and with PVM application platform. …”
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  3. 3
    Mapreduce algorithm for weather dataset

    Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

    Published 2017
    “…Big Data analytics is a new concept to process the Big Data. For weather data, this new concept will help to organise the data into structure data. …”
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  4. 4
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  5. 5
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    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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  6. 6
    MapReduce algorithm for weather dataset

    MapReduce algorithm for weather dataset by Majid, Mazlina A., Romli, Awanis, Ahmad, Noraziah, Hammad, Khalid Adam Ismail

    Published 2018
    “…Big Data analytics is a new concept to process the Big Data. For weather data, this new concept will help to organise the data into structure data. …”
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    Research Report
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  7. 7
    The Algorithm of Fear: Unpacking Prejudice Against AI and the Mistrust of Technology

    The Algorithm of Fear: Unpacking Prejudice Against AI and the Mistrust of Technology by Hutson, James, Plate, Daniel

    Published 2024
    “…This review investigates the origins of this prejudice, focusing on the parallels between current attitudes toward AI and historical resistance to new technologies. …”
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  8. 8
    Adaptive resource allocation for reliable performance in heterogeneous distributed systems.

    Adaptive resource allocation for reliable performance in heterogeneous distributed systems. by Hussin, Masnida, Abdullah, Azizol, K. Subramaniam, Shamala

    Published 2013
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  9. 9
    Adaptive genetic algorithm to improve negotiation process by agents e-commerce

    Adaptive genetic algorithm to improve negotiation process by agents e-commerce by Ebadi, Sahar

    Published 2011
    “…This improved genetic algorithm considers an economic encounter where both parties (sellers and buyer) preferences are considered when generating new offers. …”
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  10. 10
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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