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Direct approach for mining association rules from structured XML data
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Thesis -
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Study and Implementation of Data Mining in Urban Gardening
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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Article -
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Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah
Published 2021“…The study has specifically developed four main objectives to achieve its aim, namely: (1) to identify camera internal geometry of UAV for DTM production under tree canopy conditions, (2) to identify appropriate methods for the tree height estimation based on tree crown delineation, (3) To formulate a new methodology for estimating DTM production under tree canopy conditions - (Under Oil Palm area), and (4) to validate the accuracy of DTM result based on in situ measurement. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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Conference or Workshop Item -
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A web-based implementation of k-means algorithms
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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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Features selection for intrusion detection system using hybridize PSO-SVM
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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Gateway placement optimisation problem for mobile multicast design in wireless mesh networks
Published 2012“…Furthermore, the paper develops the sketch of modeling and formulation of IGW placement problem with the objective of optimising IGW placement while cost of multicast tree and mobility are optimised. …”
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Proceeding Paper -
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…Information gain was used in the feature selection and four classification algorithms namely, Logistic Regression, Random Forest, Decision Tree, and Gradient Boosted, were implemented and tested with the incorporation of 10-fold cross-validation and splitting 70:30 in WEKA. …”
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Student Project -
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Optimal load management strategy for enhanced time of use (ETOU) electricity tariff in Peninsular Malaysia / Mohamad Fani Sulaima
Published 2020“…A novel method was developed by integrating a modified energy audit procedure with decision tree technique to determine the percentage of controlled loads available for LM, and the optimal LM weightage. …”
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Thesis -
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The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater
Published 2024“…A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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SRPTackle: a semi-automated requirements prioritisation technique for scalable requirements of software system projects
Published 2021“…Method: SRPTackle provides a semiautomated process based on a combination of a constructed requirement priority value formulation function using a multi-criteria decision-making method (i.e. weighted sum model), clustering algorithms (K-means and K-means++) and a binary search tree to minimise the need for expert involvement and increase efficiency. …”
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A semi-automated requirements prioritisation technique for scalable requirements with stakeholder quantification and prioritisation
Published 2019“…Furthermore, the proposed SRPTackle is based on the combination of the proposed StakeQP technique, the constructed requirement priority value formulation function and the employing of classifying algorithm (K-means and K-means++) and binary search tree. …”
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Thesis -
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Improved robust estimator and clustering procedures for multivariate outliers detection
Published 2023“…Firstly, an improved robust estimator based on the equality of covariance matrices that is less sensitive to the presence of outliers is proposed and named as Test on Covariance (TOC). TOC is developed by modified Concentration-Step (C-Step) in the Fast Minimum Covariance Determinant (FMCD) algorithm. …”
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