Search Results - (( _ application ((bee algorithm) OR (means algorithm)) ) OR ( mobile application a 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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    A Mobile Application For Stock Price Prediction by Choy, Yi Tou

    Published 2021
    “…Novice investors are limited to specific investment knowledge and lack investment tools to gain wealth in the stocks’ markets. A mobile application for stock price prediction using time series algorithms is developed to tackle the problem mentioned. …”
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    Final Year Project / Dissertation / Thesis
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    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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    Thesis
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    Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail by Ismail, Muhammad Alif Fauzan

    Published 2021
    “…In conclusion this paper is to develop a product recommender in marketplace mobile application using Collaborative Filter and the accuracy of the algorithm is measured using Mean Absolute Error…”
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    Thesis
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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
    “…In a case where PABC is not at its optimal stage or its best performance, the experiments of a test case are effectively competitive. 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 Doppler Spread Estimation Algorithm Based on Zero Crossings of The Auto-correlation by Altag Ali, Gassan, Jeoti , Varun, Manzoor, Shahid

    Published 2010
    “…A comparison between our proposed algorithm and the algorithm proposed by Tevfik Yucek in term of the Normalized Mean Square Error has been shown.…”
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    Conference or Workshop Item
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    Multi objective bee colony optimization framework for grid job scheduling 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.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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    Conference or Workshop Item
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    Maximum-largest weighted delay first algorithm for heterogeneous traffic in 4G networks by Elsheikh, Elsheikh Mohamed Ahmed, Habaebi, Mohamed Hadi, Mohd Ramli, Huda Adibah, Arafa, Mohammed H. A., Ahmed, Kazi Istiaque

    Published 2018
    “…Packet Loss Ratio (PLR), and Mean User Throughput performance measures were used to validate the performance of M-LWDF algorithm against other algorithms using similar mobile environment. …”
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    Article
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    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

    Published 2021
    “…Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. However, real world applications commonly involved imbalanced class problem where the classes have different importance. …”
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    Article