Search Results - (( developing solving svm algorithm ) OR ( java application optimized algorithm ))

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  1. 1

    Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

    Published 2003
    “…The decomposition algorithm developed by Osuna et al. (1997a) reduces the training cost to an acceptable level. …”
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    Article
  2. 2

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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    Thesis
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    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…The Smooth Support Vector Machine (SSVM) is a further development of the SVM. Smoothing methods, extensively used for solving important mathematical programming problems and applications. …”
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    Thesis
  5. 5

    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…The Smooth Support Vector Machine (SSVM) is a further development of the SVM. Smoothing methods, extensively used for solving important mathematical programming problems and applications. …”
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    Undergraduates Project Papers
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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
  7. 7

    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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    Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig... by Harum, Norharyati, Khalil, Mohamad Kchouri, Obeid, Ali, Hazimeh, Hussein

    Published 2022
    “…One of the most commonly used algorithms is Support Vector Machine (SVM). However, classical SVM can neither use prior knowledge to process accurate classifications nor solve problems characterized by ambiguity. …”
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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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    Performance Measurement on Deep Spiking Neural Network (DSNN) Algorithm in Flood Prediction Environment by Roselind, Tei

    Published 2023
    “…There are several algorithms used to predict floods, including LSTM, BP, MLP, SARIMA, and SVM. …”
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    Thesis
  17. 17

    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
  18. 18

    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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    Thesis
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    Rain classification for autonomous vehicle navigation : A support vector machine approach by Abdul Haleem, Habeeb Mohamed, Muhammad Aizzat, Zakaria, Mohd Azraai, Mohd Razman, Anwar P. P., Abdul Majeed, Mohamad Heerwan, Peeie

    Published 2020
    “…The immerging of machine learning algorithms that have greatly impacted solving uncertainties and LIDAR's reliability in making judgments has proven a great success. …”
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    Article
  20. 20

    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…Results showed that the eABC-LSSVM possess lower prediction error rate as compared to eight hybridization models of LSSVM and Evolutionary Computation (EC) algorithms. In addition, the proposed algorithm is compared to single prediction techniques, namely, Support Vector Machines (SVM) and Back Propagation Neural Network (BPNN). …”
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    Thesis