Search Results - (( developing function based algorithm ) OR ( java optimization technique algorithm ))

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    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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    Thesis
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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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    Hybrid genetic algorithm for improving fault localization by Mahamad Zakaria, Muhammad Luqman, Sharif, Khaironi Yatim, Abd Ghani, Abdul Azim, Koh, Tieng Wei, Zulzalil, Hazura

    Published 2018
    “…Genetic algorithm (GA) is well known in finding an optimal solution to a problem while local search is capable of removing duplication. …”
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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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    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Recently, various techniques based on different algorithms have been developed. …”
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    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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    A block cipher based on genetic algorithm by Zakaria, Nur Hafiza

    Published 2016
    “…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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    A genetic algorithm based approach for economic dispatch in power system / Mohd Rozely Kalil by Kalil, Mohd Rozely

    Published 1998
    “…The Genetic Algorithm developed in the project was tested on two objective functions for optimizing the economic dispatch problem, which are the total generation cost and the incremental cost function. …”
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    Computation of cryptosystem based on Lucas functions using addition chain by Md Ali, Zulkarnain, Othman, Mohamed, Md. Said, Mohamad Rushdan, Sulaiman, Md. Nasir

    Published 2010
    “…In this paper, an efficient computation algorithm for LUC Cryptosystem is developed. It is based on Addition Chain. …”
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    Conference or Workshop Item
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    A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

    Published 2022
    “…These basic indicators can comprehensively and effectively reflect a country’s or region’s future economic development. The center of radial basis function neural network and smoothing factor to take a uniform distribution of the random radial basis function artificial neural network will be the focus of this study. …”
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    Article
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    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…Finally, surface defects are segmented from an anomaly heat map which is generated based on histogram distance functions. Results show that the proposed algorithm required a learning dataset size as small as 5 samples and was resistant to learning labelling error up to 50%.…”
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    Thesis