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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…This study also focuses on solving fractal-fractional differential equations in the Caputo sense with a power-law kernel (FFDEsCP) using FNN in two hidden layers with a vectorized algorithm alongside Adam (FNN2HLVA-Adam). …”
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Thesis -
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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications
Published 2020“…The solution provided by deep learning for a differential equation is in a closed analytical form which is differentiable and could be used in any subsequent computation. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…In this study, a machine learning approach based on the unsupervised version of wavelet neural networks (WNNs) is used to solve two-dimensional elliptic partial differential equations (PDEs). …”
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Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. …”
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Proceedings -
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Evaluating the performances of Dice, Jaccard, Overlap, and Cosine coefficients in automated marking of algebraic equations / Hasnah Yusof, Wan Rolini Wan Yusoff and Masita Jamal
Published 2006“…The algorithm used in the automated marking was adjusted to fit the DJOC coefficients. …”
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Research Reports -
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato...
Published 2025“…This technique uses the Adaptive Moment Estimation Method (Adam) as an optimization algorithm with feed-forward deep learning to minimize the error function and training the model using five layers with different activation functions. …”
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Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
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Extreme Learning Machines: A new approach for prediction of reference evapotranspiration
Published 2023Article -
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
Published 2013“…Forex prediction has become a challenging task in the Forex market since the late 1970s due to uncertainty movement of exchange rates.In this paper, we utilised linear regression equation to analyse the historical data and discover the trends patterns in Forex.These trends patterns are modeled and learned by Artificial Neural Network algorithm, and Dynamic Time Warping algorithm is used to predict the near future trends.Our experiment result shows a satisfactory result using the proposed approach.…”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions
Published 2025“…A hybrid technique, combining a polynomial neural network (PNN) with an extreme learning machine algorithm without using any activation functions, is developed. …”
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Applications of machine learning to friction stir welding process optimization
Published 2020“…A computational method used in machine learning to learn or get directly information from data without relying on a prearranged model equation. …”
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Predicting energy consumption pattern based on top trending videos YouTube 2021 using machine learning techniques
Published 2022“…In this project, several models will be presented and analysed, with the normal equation in Linear Regression will be the algorithm used to simulate it. …”
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Final Year Project / Dissertation / Thesis -
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Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus
Published 2022“…The simulated results and parametric analysis conclude that the proposed algorithm can decipher the non-Newtonian fluid mechanics from the governing equations. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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