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Depression prediction using machine learning: a review
Published 2022“…The aim of this study is to identify important variables used in depression prediction, recent depression screening tools adopted, and the latest machine learning algorithms used. …”
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Direct approach for mining association rules from structured XML data
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Thesis -
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…The prototypes will be developed using JAVA language united with a MySQL database. Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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Final Year Project -
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Group formation using genetic algorithm
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Monograph -
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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Thesis -
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Mortality prediction in critically ill patients using machine learning score
Published 2020“…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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Proceeding Paper -
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Mortality prediction in critically ill patients using machine learning score
Published 2020“…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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Conference or Workshop Item -
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Network game (Literati) / Chung Mei Kuen
Published 2003“…The possible applications of multimedia-networked system are endless, as the demand to support interactive communication among groups of users has increased significantly. …”
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Thesis -
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
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Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms
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A case study on quality of sleep and health using Bayesian networks
Published 2012“…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…The ML approach, which predicts optimal design parameters with a trained dataset, is more efficient with reduced duration than conventional finite element analysis (FEA) tools and stochastic methods. The learning algorithms consider variables such as core structure, cross-coupling effect, and coil flux pipe length. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…Hence, the need to develop automatic segmentation algorithms has rapidly increased along with the increased need of diagnostic tools for assisting medical practitioners, especially in the absence of radiologists. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…Hence, the need to develop automatic segmentation algorithms has rapidly increased along with the increased need of diagnostic tools for assisting medical practitioners, especially in the absence of radiologists. …”
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