Search Results - (( java implication based algorithm ) OR ( network application testing algorithm ))

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    Comparative analysis of sine cosine and social network search-based algorithm for software test redundancy reduction optimization by Mekeng, Ambros Magnus Rudolf, Kamal Z., Zamli, Muhammad Zarlis, .

    Published 2024
    “…More precisely, our work intents to investigate the algorithms' performance in terms of test reduction percentage and execution time. …”
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    Conference or Workshop Item
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    Automated surveillance in distributed, visual networks: an empirical comparison of recent algorithms by Ahmed, Tarem, Ahmed, Supriyo, Pathan, Al-Sakib Khan

    Published 2014
    “…This paper demonstrates the applicability of a selection of such algorithms to a distributed network of wireless sensors. …”
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    Article
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    Automated surveillance in distributed, wireless visual networks: a comparative study by Ahmed, Tarem, Ahmed, Supriyo, Pathan, Al-Sakib Khan

    Published 2013
    “…Past researchers have tested these algorithms on centralized networks where all images are transmitted to a central control room. …”
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    Proceeding Paper
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    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

    Published 2025
    “…SGA is used in the process of solving optimization test problems by neural networks. The problems are solved by the same neural network with and without SGA, computational results prove the efficiency of SGA in neural networks. …”
    Article
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    Simulation Of Token Bucket Algorithm For Network Traffic Performance by Yusof, Robiah, Mat Nawi, Nor Afifah

    Published 2020
    “…This algorithm has successfully reduced the delay in the network traffic and improve the response time when users request several applications concurrently.…”
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    Article
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    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…Results show that the reinforced network classifier with GA feature selection algorithm has successfully increased the classification accuracy of training process and testing process by 13.87% and 14.21% respectively compared to the conventional neural network classifier. …”
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    Thesis
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