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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
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    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
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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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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    Final Year Project / Dissertation / Thesis
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  6. 6
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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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
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  8. 8
    Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms

    Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms by Shaikh, Abdul Aabid, Raheman, Md Abdul, Hrairi, Meftah, Baig, Muneer

    Published 2024
    “…On the other hand, machine learning (ML) has made it possible to employ a variety of approaches for mechanical and aerospace problems and such significant approach is the repair mechanism and hence ML algorithms used to enhance in the present work. …”
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  9. 9
    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
    “…This study evaluates the damage progression on glass fiber reinforced polyester composite specimens using different approaches of machine learning. …”
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  10. 10
    Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam

    Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam by Toghroli, Ali, Suhatril, Meldi, Ibrahim, Zainah, Safa, Maryam, Shariati, Mahdi, Shamshirband, Shahaboddin

    Published 2018
    “…In comparison to the other widely used conventional learning algorithms, the ELM has a much faster learning ability.…”
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  11. 11
    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market

    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

    Published 2023
    “…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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  12. 12
    Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks

    Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks by Mahzan, Shahruddin, J. Staszewski, Wieslaw, Worden, Keith

    Published 2010
    “…The strain data are used for learning in the Neural Network approach. …”
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  13. 13
    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele B.V., Mustapa S.I., Kanthasamy R., Mohammad N., AlTurki A., Babu T.S.

    Published 2023
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  14. 14
    NN-Based FECG extraction from the composite abdominal ECG

    NN-Based FECG extraction from the composite abdominal ECG by Hasan, Muhammad Asraful, Ibrahimy, Muhammad Ibn, Reaz, Mamun Bin Ibne

    Published 2008
    “…According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. …”
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    Proceeding Paper
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  15. 15
    Producer gas composition prediction using artificial neural network algorithm / Mohd Mahadzir Mohammud ... [et al.]

    Producer gas composition prediction using artificial neural network algorithm / Mohd Mahadzir Mohammud ... [et al.] by Mohammud, Mohd Mahadzir, Mohamad Bakre, Muhammad Syaham, Mohd Fohimi, Nor Azirah, Rabilah, Rosniza, Ahmad, Muhammad Iqbal

    Published 2023
    “…It is then used to predict the output gas composition from the parameters of a gasification experiment that has been used before in UiTM’s laboratory. …”
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  16. 16
    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool

    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

    Published 2019
    “…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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  17. 17
    Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach

    Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach by Shabbir Ahmed, Omar, Syed Mohamed Ali, Jaffar, Aabid, Abdul, Hrairi, Meftah, Mohd Yatim, Norfazrina Hayati

    Published 2024
    “…In summary, this paper delves into the study of the stability of C-section thin-walled composite structures with holes under mechanical and thermal loading conditions using finite element analysis and machine learning studies.…”
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  18. 18
    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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  19. 19
    Modelling and optimization of microhardness of electroless Ni-P-TiO2composite coating based on machine learning approaches and RSM

    Modelling and optimization of microhardness of electroless Ni-P-TiO2composite coating based on machine learning approaches and RSM by Shozib, I.A., Ahmad, A., Rahaman, M.S.A., Abdul-Rani, A.M., Alam, M.A., Beheshti, M., Taufiqurrahman, I.

    Published 2021
    “…The microhardness of the electroless Ni-P-TiO2 coated composite was measured and predicted by various machine learning algorithms. …”
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  20. 20
    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction

    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

    Published 2017
    “…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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