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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  7. 7
    Features selection for intrusion detection system using hybridize PSO-SVM

    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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  8. 8
    Images composition using chroma key techniques / Nurulazura Jawahir

    Images composition using chroma key techniques / Nurulazura Jawahir by Jawahir, Nurulazura

    Published 2014
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  9. 9
    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction

    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction by Hammid, Ali Thaeer, M. H., Sulaiman, Awad, Omar I.

    Published 2018
    “…The results display that the regression coefficient, root-mean-square error, mean absolute error, and mean bias error values of the suggested model are 99.86%, 1.87%, 0.91%, and 0.31%, respectively. …”
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  10. 10
    Statistical modeling of the electromechanical behaviour of BI-2223 composite wires

    Statistical modeling of the electromechanical behaviour of BI-2223 composite wires by Muhammad Faris Fuaad

    Published 2024
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  11. 11
    State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission

    State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission by Gholizadeh, S., Leman, Z., Baharudin, B.T.H.T.

    Published 2023
    “…Three different ensemble learning methods namely, XGboost, LightGBM, and CatBoost were chosen to predict damages and AE parameters. SHAP values were used to select AE key features and K-means algorithms were employed to classify damage severity. …”
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  12. 12
    Prediction of optimum compositions of parenteral nanoemulsion system loaded with low solubility drug for treatment of schizophrenia by artificial neural network

    Prediction of optimum compositions of parenteral nanoemulsion system loaded with low solubility drug for treatment of schizophrenia by artificial neural network by Samiun, Wan Sarah, Basri, Mahiran, Masoumi, Hamid Reza Fard, Khairudin, Nurshafira

    Published 2016
    “…The particle size of samples in various compositions was measured as output. To obtain the optimum topologies, ANNs were trained by Incremental Back Propagation (IBP), Genetic Algorithm (GA), Batch Back Propagation (BBP), Quick Propagation (QP), and Levenberg-Marquardt (LM) algorithms for testing data set. …”
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  13. 13
    Improving robustness of artificial neural networks model using genetic algorithm

    Improving robustness of artificial neural networks model using genetic algorithm by Ahmad, Arshad, Chen, Wah Sit

    Published 2003
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  14. 14
    Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network model

    Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo... by Che Sulaiman, Intan Soraya, Basri, Mahiran, Masoumi, Hamid Reza Fard, Ashari, Siti Efliza, Basri, Hamidon, Ismail, Maznah

    Published 2017
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  15. 15
    Seed disperser ant algorithm for optimization / Chang Wen Liang

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…The classical benchmark problems and composite benchmark functions from Congress on Evolutionary Computation (CEC) 2005 special session is used for validate SDAA. …”
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  16. 16
    Development of a novel natural frequencies prediction tool for laminated composite plates using integrated artificial neural network (ANN) - simulink MATLAB / Mohd Arif Mat Norman

    Development of a novel natural frequencies prediction tool for laminated composite plates using integrated artificial neural network (ANN) - simulink MATLAB / Mohd Arif Mat Norman by Mat Norman, Mohd Arif

    Published 2024
    “…The prediction tool utilises an Artificial Neural Network (ANN) with a two-layer feed-forward algorithm and ten hidden layers, using Levenberg-Marquardt as the training algorithm. …”
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  17. 17
    An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum

    An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

    Published 2023
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  18. 18
    Pemodelan data indeks komposit Kuala Lumpur menggunakan neurofuzzy

    Pemodelan data indeks komposit Kuala Lumpur menggunakan neurofuzzy by Mohd. Yunos, Zuriahati

    Published 2006
    “…Root Mean Square Error (RMSE) and Mean Absolute Percentage of Error (MAPE) are chosen to measure the prediction accuracy. …”
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  19. 19
    Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility

    Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility by Al Haqyan, Mohammed Kamel Mohammed

    Published 2018
    “…All parameters involved in the developed model are estimated by using innovation algorithm. A simulation study is then conducted to determine the performance of the new model. …”
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  20. 20
    Empirical analysis of parallel-NARX recurrent network for long-term chaotic financial forecasting

    Empirical analysis of parallel-NARX recurrent network for long-term chaotic financial forecasting by Abdulkadir, S.J., Yong, S.-P.

    Published 2014
    “…The experimental results based on mean absolute percentage error (MAPE) and other forecasting error metrics shows that P-NARX network trained with Bayesian regulation slightly outperforms Levenberg-marquardt, Resilient back-propagation and one-step-secant training algorithm in forecasting daily Kuala Lumpur Composite Indices. …”
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