Browsing by Subject "Machine learning"
Now showing items 1-6 of 6
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ANN-based estimation of MEMS diaphragm response: An application for three leaf clover diaphragm based Fabry-Perot interferometer
(Elsevier B.V., 2022)In this study, an artificial neural network (ANN) based model is developed for MEMS diaphragm analysis, which does not require difficult and time-consuming FEM processes. ANN-based estimator is generated for static pressure ... -
Diagnosis of Attention Deficit Hyperactivity Disorder with combined time and frequency features
(Elsevier Sp. z o.o., 2020)The aim of this study was to build a machine learning model to discriminate Attention Deficit Hyperactivity Disorder (ADHD) patients and healthy controls using information from both time and frequency analysis of Event ... -
Early prediction of COVID-19 infection using data mining and multi machine learning algorithms
(Institute of Advanced Engineering and Science, 2024)The fields of artificial intelligence (AI) and machine learning (ML) have attracted significant interest and investment from a diverse range of industries, especially during the last several years. Despite the fact that ... -
Educational data mining: prediction of students’ academic performance using machine learning algorithms
(Springer Open, 2022)Educational data mining has become an efective tool for exploring the hidden relationships in educational data and predicting students’ academic achievements. This study proposes a new model based on machine learning ... -
Ensemble residual network-based gender and activity recognition method with signals
(Springer, 2020)Nowadays, deep learning is one of the popular research areas of the computer sciences, and many deep networks have been proposed to solve artificial intelligence and machine learning problems. Residual networks (ResNet) ... -
A Tunable-Q wavelet transform and quadruple symmetric pattern based EEG signal classification method
(Churchill Livingstone, 2020)Electroencephalography (EEG) signals have been widely used to diagnose brain diseases for instance epilepsy, Parkinson's Disease (PD), Multiple Skleroz (MS), and many machine learning methods have been proposed to develop ...
