Search Results - (( pattern optimization svm algorithm ) OR ( java application optimized algorithm ))

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  1. 1

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  2. 2

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…The first two algorithms, ACOR-SVM and IACOR-SVM, tune the SVM parameters while the second two algorithms, ACOMV-R-SVM and IACOMV-R-SVM, tune the SVM parameters and select the feature subset simultaneously. …”
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    Thesis
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    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
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    Article
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    Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

    Published 2003
    “…Numerical problems will cause the training to give non- optimal decision boundaries. Using a conventional optimizer to train SVM is not the ideal solution. …”
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    Article
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    Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context by Nanna Suryana, Herman, Burairah, Hussin

    Published 2012
    “…In this study, the discriminative approach in particular support vector machines (SVM) is employed to recognize the studied TIS patterns. …”
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    Article
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    Prediction of COVID-19 outbbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

    Published 2024
    “…Looking ahead, future works may explore refining the SVM model and incorporating additional features for improved accuracy, and the ongoing iterative process involves continuous validation and adaptation of the model to evolving data patterns and emerging challenges in pandemic management. …”
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    Thesis
  10. 10

    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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    A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

    Published 2020
    “…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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    Article
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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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    Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

    Published 2019
    “…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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    Thesis
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    Optimized multi-level elongated quinary patterns for the assessment of thyroid nodules in ultrasound images by Raghavendra, U., Gudigar, Anjan, Maithri, Mangalore, Gertych, Arkadiusz, Meiburger, Kristen Mariko, Yeong, Chai Hong, Madla, Chakri, Kongmebhol, Pailin, Molinari, Filippo, Ng, Kwan Hoong, Acharya, U. Rajendra

    Published 2018
    “…This paper proposes a new CAD system to characterize thyroid nodules using optimized multi-level elongated quinary patterns. In this study, higher order spectral (HOS) entropy features extracted from these patterns appropriately distinguished benign and malignant nodules under particle swarm optimization (PSO) and support vector machine (SVM) frameworks. …”
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    Article
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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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    Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

    Published 2024
    “…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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    Thesis
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    Condition monitoring of deep drilling process for cooling channel making in hot press die by Muhamad Aslam, Abdul Raub

    Published 2016
    “…The fault is then being produced as the pattern and SVM will recognize thus classify this pattern corresponding to the fault. …”
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    Undergraduates Project Papers
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    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

    Published 2022
    “…The proposed chewing detection classifies the chewing activity with an overall accuracy of 96.4% using a medium Gaussian support vector machine (SVM). In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). …”
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    Article