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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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    Thesis
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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
    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Predicting Reservoir Water Level

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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  7. 7
    Development Of Generative Computer-Aided Process Planning System For Lathe Machining

    Development Of Generative Computer-Aided Process Planning System For Lathe Machining by Zubair, Ahmad Faiz

    Published 2019
    “…To validate the generated tool-path, G-codes generated in media package file (MPF) file format and verified through CNC lathe machine. Indeed, the developed algorithm was able to determine the minimum unit production cost of lathe machining part model. …”
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  8. 8
    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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  9. 9
    A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant

    A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

    Published 2023
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  10. 10
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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  11. 11
    Open architecture pc-based CNC controller

    Open architecture pc-based CNC controller by Yusoff, Wan Azhar

    Published 2006
    “…The objectives of this project are two: developing CNC controller and developing a prototype machine to implement the controller. …”
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    Research Report
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  12. 12
    Support directional shifting vector: A direction based machine learning classifier

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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  13. 13
    Optimization machining parameters in pocket milling using genetic algorithm and mastercam

    Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

    Published 2023
    “…A fitness function of production time incorporated of roughing and finishing process has been developed in Matlab Software. …”
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  14. 14
    To study the multi-objective optimization of EDM using genetic algorithm

    To study the multi-objective optimization of EDM using genetic algorithm by Fairuz, Idris

    Published 2013
    “…EDM is one of the most accurate manufacturing processes for creating geometric shapes whether complex or simple in parts and assemblies. Development of EDM process has resulted in significant improvements in operating techniques, productivity and accuracy, which the result of this machining development has helped variability in EDM process. …”
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    Undergraduates Project Papers
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  15. 15
    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms

    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

    Published 2023
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  16. 16
    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems

    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

    Published 2010
    “…This thesis focuses on the development of a new stream of crossover within genetic algorithms, called Optimised Crossover Genetic Algorithm (OCGA) for solving combinatorial optimisation problems, which takes into account the objective function in finding the best ofspring solution among an exponentially large number of potential ofspring. …”
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  17. 17
    Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm

    Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

    Published 2023
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  18. 18
    Development of machine learning-based algorithm to determine the condition in transformer oil

    Development of machine learning-based algorithm to determine the condition in transformer oil by Mohsen Al-Katheri, Hussein Hasan

    Published 2021
    “…Machine Learning (ML) algorithm have been utilized to detect the fault more accurate. …”
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  19. 19
    A comparative analysis of machine learning algorithms for diabetes prediction

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…This study focuses on comparing the performance of three machine learning algorithms, namely Naive Bayes (NB), Support Vector Machines (SVM), and Random Forest (RF), in predicting diabetes using two datasets: Pima Indians Diabetes Dataset (PIDD) and the Diabetes 2019 Dataset (DD2019), and the need to identify the most accurate and effective algorithm for diabetes prediction. …”
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  20. 20
    AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm

    AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm by Salim, Nur Saadah, Saad, Shahadan

    Published 2025
    “…This research introduces a new approach to enhancing cybersecurity by integrating Support Vector Machine (SVM) algorithms with penetration testing to develop a recommendation system focused on Cross-Site Scripting (XSS) attack detection. …”
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