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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems
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Working Paper -
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Prediction of MUET result based on KNN algorithm / Siti Fatimah Azzahra Hamrizan
Published 2021“…The machine learning technique used to develop the prediction prototype is the KNN algorithm. …”
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Thesis -
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Development of an intelligent prediction tool for rice yield based on machine learning techniques
Published 2006“…Support vector machine algorithm is developed for classification of rice plantation data. …”
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Model Predictive Control Design for f Nonlinear Four-Tank System
Published 2008“…In this thesis, besides good performance, the algorithm enjoys from relative simplicity and faster response in compare with the algorithms developed in other previous works. …”
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Thesis -
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Development of a new method of crack modeling and prediction algorithm
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Proceeding Paper -
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Cancer Prediction Based On Data Mining Using Decision Tree Algorithm
Published 2022“…Each work has some shortcomings like lack of intelligent prediction and an inefficient structure which eventually prompted me to take on this subject and develop a cancer prediction system. …”
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Undergraduates Project Papers -
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Developing Bus Tracking System that predicts the arrival times of public buses at Universiti Teknologi PETRONAS (UTP) bus stops.
Published 2004“…By collecting all the dataneeded such as speed and location, an algorithm can be developed to predict when the transport will reach a certain checkpoint. …”
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Final Year Project -
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. …”
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Article -
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. The research is divided into three parts, which are (1) dataset development, (2) algorithm development, and (3) algorithm performance evaluation. …”
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. …”
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Article -
15
A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market
Published 2023“…Three deep learning algorithms, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), are used to develop the prediction model. …”
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Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm
Published 2018“…The main goal of this research work is to propose the novel practical models to predict the BI through particle swarm optimization (PSO) and imperialism competitive algorithm (ICA). …”
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Prediction of blood-brain barrier permeability of compounds by machine learning algorithms
Published 2024“…In this work, using the KNIME Analytics platform, 4 predictive models were developed with 4 ML algorithms followed by a ten-fold cross-validation approach to predict the external validation set. …”
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Article -
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A quick gbest guided artificial bee colony algorithm for stock market prices prediction
Published 2018“…The objective of this work is to present a Quick Gbest Guided artificial bee colony (ABC) learning algorithm to train the feedforward neural network (QGGABC-FFNN) model for the prediction of the trends in the stock markets. …”
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Stock indicator scanner customization tool
Published 2022“…Since stock prediction problem is considered a time-series problem, long short-term memory (LSTM) will be used as the algorithm in the proposed model, and LSTM has been proven to be good stock prediction model in previous works. …”
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Final Year Project / Dissertation / Thesis -
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Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub...
Published 2014“…In doing so, Multi-Parametric Programming technique is used to develop the computer algorithm; whereas Model-Based Predictive Control (MPC) is adopted for the design of the controller. …”
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Monograph
