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Support directional shifting vector: A direction based machine learning classifier
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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Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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Reliability fuzzy clustering algorithm for wellness of elderly people
Published 2019“…Thus, the objective of this paper is to propose a reliable fuzzy clustering algorithm using z-numbers. …”
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Conference or Workshop Item -
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…Then, a single hidden layer of FNN based on Chelyshkov polynomials with an extreme learning machine algorithm (SHLFNNCP-ELM) is constructed for solving FDEsC. …”
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NLP- based for providing mental health support in mobile application / Muhammad Amirul Roslan
Published 2025“…Future enhancements, such as advanced machine learning algorithms and user interface improvements, are proposed to further enhance functionality. …”
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Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali
Published 2017“…Thus, development of an SOM algorithm for high energy physics datasets was performed. …”
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SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration
Published 2021“…Data-driven models for predicting fire and explosion-related properties have been improved greatly in recent years using machine-learning algorithms. However, choosing the best machine learning approach is still a challenging task. …”
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Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah
Published 2020“…Existing researches on air pollution forecasting used a variety of machine learning algorithm. One of the popular algorithms used to forecast the air pollution is Artificial Neural Network (ANN). …”
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Car dealership web application
Published 2022“…In this project, a web application and a web service were proposed and implemented. …”
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Final Year Project / Dissertation / Thesis -
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids
Published 2023“…The latter is a machine learning non-parametric algorithm, more tolerant than other approaches in its assumptions, which has often been shown to outperform parametric algorithms. …”
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Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics
Published 2024“…In the reduction phase, the optimal features are selected with theaid of the developed Hybrid Flower Pollination Bumblebees Optimization Algorithm (HFPBOA). …”
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Mobile application for blood donation using geolocation and rule-based algorithm / Muhammad Firzan Azrai Nuzilan and Mohd Ali Mohd Isa
Published 2021“…Last but not least, the application can be improved by implementing the machine learning that can help to predict the blood donor behavior and also the timing of the blood shortage.…”
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Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli
Published 2023“…By leveraging image processing techniques, statistical analysis and machine learning algorithms, Python enables the extraction of relevant features and patterns from data. …”
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Student Project -
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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