Search Results - (( web application matching algorithm ) OR ( some applications bees algorithm ))

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    Web application vulnerabilities detection model by Buja, Alya Geogiana, Abd. Jalil, Kamarularifin, Mohd Ali, Fakariah, Abdul Rahman, Teh Faradilla

    Published 2016
    “…The algorithm is used in order to match the defined criteria of each web vulnerability with the input information about web application. …”
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    Research Reports
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    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

    Published 2017
    “…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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    Article
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    Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

    Published 2017
    “…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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    Article
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    A new split based searching for exact pattern matching for natural texts by Hakak, Saqib Iqbal, Kamsin, Amirrudin, Shivakumara, Palaiahnakote, Idris, Mohd Yamani Idna, Gilkar, Gulshan Amin

    Published 2018
    “…Exact pattern matching algorithms are popular and used widely in several applications, such as molecular biology, text processing, image processing, web search engines, network intrusion detection systems and operating systems. …”
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    Article
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    ScholarsAid: a personalized scholarship web application based on web scraping/ Muhammad Nur Haqeem Sulaiman and Norhasliza Ahmad by Sulaiman, Muhammad Nur Haqeem, Ahmad, Norhasliza

    Published 2023
    “…The web application offers functionality for students to search and filter scholarships to suit their preferences or needs and the most relevant scholarships are provided based on matching algorithm. …”
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    Article
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    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

    Published 2017
    “…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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    Article
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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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    Web-based volunteer management system by Chang, Wei Hang

    Published 2025
    “…Key innovations include a weighted skill-matching algorithm that evaluates both skills importance level required and volunteer proficiencies, a distance-based matching algorithm using Google Maps Distance Matrix API, and leaderboard gamification elements for volunteer contribution recognition. …”
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    Final Year Project / Dissertation / Thesis
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    Bee foraging behaviour techniques for grid scheduling problem by Alyaseri, Sana, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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    Article
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