Search Results - (( java application optimized algorithm ) OR ( using using maximization algorithm ))

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

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
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    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    Improved expectation maximization algorithm for Gaussian mixed model using the kernel method by Mohd Yusoff, Mohd Izhan, Mohamed, Ibrahim, Abu Bakar, Mohd Rizam

    Published 2013
    “…We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. …”
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    Article
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    Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power by Mohd Ashraf, Ahmad, Jui, Julakha Jahan, Mohd Riduwan, Ghazali

    Published 2022
    “…The ASEDA-based technique is used to determine the ideal control parameter for each turbine to maximize a wind farm's total power generation. …”
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    The performance of expectation maximization (EM) algorithm in Gaussian Mixed Models (GMM) by Mohd Yusoff, Mohd Izhan, Abu Bakar, Mohd. Rizam, Mohd Nor, Abu Hassan Shaari

    Published 2009
    “…Expectation Maximization (EM) algorithm has experienced a significant increase in terms of usage in many fields of study. …”
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    Article
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    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
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    Using Spiral Dynamic Algorithm for Maximizing Power Production of Wind Farm by Mok, Ren Hao, Raja Mohd Taufika, Raja Ismail, Mohd Ashraf, Ahmad

    Published 2017
    “…This paper presents a preliminary study of a model-free approach based on spiral dynamic algorithm (SDA) for maximizing wind farms power production. …”
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    Conference or Workshop Item
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    Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

    Published 2021
    “…Expectation–Maximization algorithm is a novel method used by us for the first time for identifying renal stones. …”
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    Proceedings
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    Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power production by Mohd Ashraf, Ahmad, Jui, Julakha Jahan, Mohd Riduwan, Ghazali

    Published 2022
    “…The ASEDA-based technique is used to determine the ideal control parameter for each turbine to maximize a wind farm's total power generation. …”
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    Conference or Workshop Item
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    Visualization of dengue incidences using expectation maximization (EM) algorithm by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

    Published 2017
    “…Along with the prediction modeling on data using centroid model and distribution model based on K-means and Expectation Maximization (EM) algorithms respectively. …”
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    Article
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    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
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    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…However, SURE-Autometrics has not been estimated using maximum likelihood estimation (MLE). Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
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    Thesis