Search Results - (( variable training learning algorithm ) OR ( java application system algorithm ))
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Provider independent cryptographic tools
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Monograph -
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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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Thesis -
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Real-time algorithmic music composition application.
Published 2022“…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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Final Year Project / Dissertation / Thesis -
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Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit
Published 2025“…The random forest algorithm was able to achieve 99.8% accuracy and 99.9% sensitivity in the training dataset. …”
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Machine learning classifications of multiple organ failures in a malaysian intensive care unit
Published 2024“…The random forest algorithm was able to achieve 99.8% accuracy and 99.9% sensitivity in the training dataset. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
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Final Year Project -
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…The model had an impressive performance during the training phase, with a R2 of 0.98, RMSE of 2.412 MPa, and MAE of 1.6249 MPa when using 8 input variables to predict the compressive strength of concrete. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning
Published 2022“…Third, the concept of multistage training based on the dynamic variables was proposed as an opposing concept to one-stage combinatory training. …”
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Thesis -
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
Published 2023“…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…Java Media Framework library and the RTP protocol for audio transmission were used as development tools.The developed system designed in this thesis together with experimental results proved that the system could be implemented successfully. …”
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Thesis -
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…In this project, an Artificial Neural Network (ANN) trained by the Invasive Weed Optimization (IWO) learning algorithm is proposed for short term load forecasting (STLF) model. …”
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Student Project -
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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Conference or Workshop Item -
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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine)
Published 2024“…Recursive Feature Elimination (RFE) was employed for feature selection, and we trained seven supervised classifiers. Grid Search was used to optimize the hyperparameters of each algorithm. …”
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