Search Results - (( java application optimisation algorithm ) OR ( parameter adaptation server algorithm ))

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  1. 1

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  2. 2

    Mitigating Slow Hypertext Transfer Protocol Distributed Denial of Service Attacks in Software Defined Networks by Akanji, Oluwatobi Shadrach, Abisoye, Opeyemi Aderiike, Iliyasu, Mohammed Awwal

    Published 2021
    “…Genetic algorithm was used to select the Netflow features which indicates the presence of an attack and also determine the appropriate regularization parameter, C, and gamma parameter for the Support Vector Machine classifier. …”
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  3. 3

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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  4. 4

    Smart energy meter based on a long-range wide-area network for a stand-alone photovoltaic system by Jabbar, Waheb A., Annathurai, Sanmathy, Tajul Ariffin, A. Rahim, M. Fitri, Mohd Fauzi

    Published 2022
    “…The AllThingsTalkMaker IoT server is integrated into the TTN to be accessed using Web/mobile application interfaces. …”
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  5. 5

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. Incremental learning has an ability to process large data in chunk and update the parameters after learning each chunk. …”
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