Search Results - (( mobile application bees algorithm ) OR ( its application means algorithm ))*

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    Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

    Published 2017
    “…This project used Artificial Bee Colony Algorithms (ABC) by adapting the food foraging behaviour of bee in honey bee and find a suitable house for home buyer based on their requirement. …”
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    Thesis
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    Biologically inspired mobile agent-based sensor network (BIMAS) by Ponnusamy, V., Low, T.J., Amin, A.H.M.

    Published 2014
    “…The research outcome is a biologically inspired mobile agent-based system (BIMAS) that provides a novel self-healing (bee pollination analogy for energy efficiency) protocol, leading to a longer WSNs lifetime. …”
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    Article
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    ABC-PSO for vertical handover in heterogeneous wireless networks by Goudarzi, Shidrokh, Hassan, Wan Haslina, Anisi, Mohammad Hossein, Soleymani, Seyed Ahmad, Sookhak, Mehdi, Khan, Muhammad Khurram, Hassan Abdalla Hashim, Aisha, Zareei, Mahdi

    Published 2017
    “…Nevertheless, attributes of mobile devices need algorithms that are quick and effective in order to select best available network near real-time. …”
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    Article
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    Gps solution for active queue management using android platform by Liu, Yu Yao

    Published 2021
    “…Four tickets management applications, namely QueueBee, powerQ, WaveTec and QLess are reviewed to understand both strengths and weaknesses of existing application on current market. …”
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    Final Year Project / Dissertation / Thesis
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    Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering by Hengda, Wang, Mohamad Mohsin, Mohamad Farhan, Mohd Pozi, Muhammad Syafiq

    Published 2024
    “…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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    Article
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    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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    Thesis
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    All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

    Published 2018
    “…The results also show that the proposed method outperforms other LMS algorithm without secondary path modelling. The proposed narrowband LMS algorithm would benefit in the design of efficient feedforward ANC system that can realize noise control in air intake duct applications.…”
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    Article
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    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
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    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
    Get full text
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    Final Year Project