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Deep neural network approach to estimation of power production for an organic Rankine cycle system
(Springer, 2020)
In this study, the possibility of using Stepwise multilinear regression and deep learning models to estimate the behaviour of the organic Rankine cycle (ORC) has been investigated. It was found that a number of parameters ...
Prediction of Leakage from an Axial Piston Pump Slipper with Circular Dimples Using Deep Neural Networks
(Springer, 2020)
Oil leakage between the slipper and swash plate of an axial piston pump has a significant effect on the efficiency of the pump. Therefore, it is extremely important that any leakage can be predicted. This study investigates ...
Deep Convolutional Generalized Classifier Neural Network
(Springer, 2020)
Up to date technological implementations of deep convolutional neural networks are at the forefront of many issues, such as autonomous device control, effective image and pattern recognition solutions. Deep neural networks ...
SecureDeepNet-IoT: A deep learning application for invasion detection in industrial Internet of Things sensing systems
(Wiley, 2021)
Deep learning (DL) is a special field of artificial intelligence that has increased its use in various fields and has proved its effectiveness in classification. The feasibility of using many hidden layers and many neurons ...
Deep Learning with ConvNet Predicts Imagery Tasks Through EEG
(Springer, 2021)
Deep learning with convolutional neural networks (ConvNets) has dramatically improved the learning capabilities of computer vision applications just through considering raw data without any prior feature extraction. Nowadays, ...
Analyze Performance of Embedded Systems with Machine Learning Algorithms
(Springer, 2021)
This article aims to analyze the performance of embedded systems using various machine learning algorithms on embedded systems. For this, data set were analyzed using Python programming language and related libraries. Using ...
A comparative study of estimating solar radiation using machine learning approaches: DL, SMGRT, and ANFIS
(Taylor and Francis Ltd., 2022)
Solar energy has a key role in producing clean and emissions-free power compare to conventional methods. However, sustainable development also requires a reliable and predictable energy source. It also needs methods to ...
Automatic segmentation of COVID-19 from computed tomography images using modified U-Net model-based majority voting approach
(Springer, 2022)
The coronavirus disease (COVID-19) is an important public health problem that has spread rapidly around the world and has caused the death of millions of people. Therefore, studies to determine the factors affecting the ...
Chronic obstructive pulmonary disease severity analysis using deep learning on multi-channel lung sounds
(Türkiye Klinikleri, 2020)
Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases which cannot be treated but can be kept under control in certain stages. COPD has five severities, including at-risk, mild, moderate, severe, ...
Deep Learning on Computerized Analysis of Chronic Obstructive Pulmonary Disease
(Institute of Electrical and Electronics Engineers Inc., 2020)
Goal: Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases in the world. Because COPD is an incurable disease and requires considerable time to be diagnosed even by an experienced specialist, it ...