Search Results - (( development content evolutionary algorithm ) OR ( java evolution optimization algorithm ))

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  1. 1
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…The aim of this evolution is to reflect the unseen time overhead incurred by optimal real-time algorithm, represented by LRE-TL, which might hinder the claimed optimality of such algorithms when they are practically implemented. …”
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  2. 2
    Automatic generation of mobile content in entertainment applications using evolutionary computing

    Automatic generation of mobile content in entertainment applications using evolutionary computing by Teo, Jason Tze Wi, Chin, Kim On, Rayner Alfred, Ong Jia Hui

    Published 2010
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  3. 3
    An Ant Colony System for Solving DNA Sequence Design Problem in DNA Computing

    An Ant Colony System for Solving DNA Sequence Design Problem in DNA Computing by Farhaana, Yakop, Zuwairie, Ibrahim, Amar Faiz, Zainal Abidin, Zulkifli, Md. Yusof, Mohd Saberi, Mohamad, Khairunizam, Wan, Watada, Junzo

    Published 2013
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    Unified framework for spam detection and risk assessment in short message communication media / Adewole Kayode Sakariyah

    Unified framework for spam detection and risk assessment in short message communication media / Adewole Kayode Sakariyah by Adewole Kayode, Sakariyah

    Published 2018
    “…Bio-inspired evolutionary search method was studied to identify the discriminating features for spam account detection. …”
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  5. 5
    Design of intelligent control system and its application on fabricated conveyor belt grain dryer

    Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

    Published 2011
    “…This controller has several advantages over its conventional ANFIS counterpart, particularly the reduction in processing time. Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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