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Predicting usage for a marketable e-learning portal
Published 2014“…To date, existing e-learning portals focuses on providing various learning materials via online.Such an approach may provide huge benefit to the learners; nevertheless, less value can be obtained by the developers or owners.The knowledge transfer programme provides an insight on how existing e-learning portal can be upgraded.The academia has introduced the industry to a computational modelling that is built upon the behaviour of nature community (i.e bees)The utilization of Artificial Bee Colony algorithm in predicting learners' usage of an e-learning portal provides an indicator to the developers on the portals effectiveness.Such information is then useful in producing a marketable and valuable e-learning portal…”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency
Published 2024“…This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. …”
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Article -
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Music Recommender System Using Machine Learning Content-Based Filtering Technique
Published 2022“…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
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Undergraduates Project Papers -
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A New Mobile Botnet Classification based on Permission and API Calls
Published 2024“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”
Proceedings Paper -
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Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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Thesis -
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E-history Malaysian secondary school textbook using TF-IDF algorithm and text visualization / Nur Hafizah Mohd Ridzuan
Published 2020“…TF-IDF Algorithm technique is performed to develop system by calculating the most relevant pages in the textbook based on keyword that entered by user’s query. …”
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Thesis -
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Design of a pattern classification system using extreme learning machine
Published 2024text::Final Year Project -
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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Development of Technical Safety Dashboard Using Microsoft Power BI Integration with R
Published 2020“…Besides, this paper also enlightens on one of the Machine Learning tools used which is R, with the utilization of K Nearest Neighbor (KNN) algorithm as method of classification for data. …”
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Final Year Project -
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Design of a pattern classification system using extreme learning machine
Published 2023text::Final Year Project -
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Brain tumor image segmentation using deep learning approach
Published 2022“…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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Final Year Project / Dissertation / Thesis -
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Therefore, a fuzzy model based on machine learning and data mining is a vital solution. In this study, ten supervised machine learning algorithms namely the J48, Logistic, NaiveBayes Updateable, RandomTree, BayesNet, AdaBoostM1, Random Forest, Multilayer Perceptron, Bagging and Stacking are applied for a simulated diabetes fuzzy dataset, verified by medical experts. …”
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Jawi recognition system
Published 2010“…To improve the recognition of the character, the system uses neural network training algorithm called Supervised Learning to receive new character pattern in order to strengthen the weight of the pixels. …”
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Undergraduates Project Papers -
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Predicting motorcycle customization preferences using machine learning
Published 2025“…Recent developments in artificial intelligence have expanded the role of machine learning in analyzing human behavior across various domains. …”
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