Electricity theft detection in smart grids based on deep neural network
Electricity theft is a global problem that negatively affects both utility companies and
electricity users. It destabilizes the economic development of utility companies, causes …
electricity users. It destabilizes the economic development of utility companies, causes …
Cracking performance evaluation and modelling of RAP mixtures containing different recycled materials using deep neural network model
This study evaluates the cracking resistance of recycled asphalt pavement (RAP) mixtures
including waste engine oil (WEO), crumb rubber (CR), and steel slag aggregates using the …
including waste engine oil (WEO), crumb rubber (CR), and steel slag aggregates using the …
The Intelligent Design of Silicon Photonic Devices
Z Li, Z Zhou, C Qiu, Y Chen, B Liang… - Advanced Optical …, 2024 - Wiley Online Library
Photonic devices based on silicon waveguides are essential to versatile high‐performance
and low‐cost photonic integrated systems. Extremely complex silicon photonic devices with …
and low‐cost photonic integrated systems. Extremely complex silicon photonic devices with …
[PDF][PDF] A Hybrid Model for Anomalies Detection in AMI System Combining K-means Clustering and Deep Neural Network.
A Maamar, K Benahmed - Computers, Materials & Continua, 2019 - cdn.techscience.cn
Recently, the radical digital transformation has deeply affected the traditional electricity grid
and transformed it into an intelligent network (smart grid). This mutation is based on the …
and transformed it into an intelligent network (smart grid). This mutation is based on the …
Multiclass classification fault diagnosis of multirotor UAVs utilizing a deep neural network
A fault diagnosis algorithm using a deep neural network for an octocopter Unmanned Aerial
Vehicle (UAV) is proposed. All eight rotors are considered in the multiclass classification …
Vehicle (UAV) is proposed. All eight rotors are considered in the multiclass classification …
Intrusion detection systems for the internet of thing: a survey study
In recent years, networking systems have witnessed a breakthrough. Due to the advances in
network and communication technology, new concepts such as the Internet of Things (IoT) …
network and communication technology, new concepts such as the Internet of Things (IoT) …
Determination of clay-water contact angle via molecular dynamics and deep-learning enhanced methods
X Song, Z Zhang - Acta Geotechnica, 2021 - Springer
Molecular dynamics modeling is a useful tool to study the interface physics of the clay-water
system at the nanoscale. A key parameter to characterize the interface physics of …
system at the nanoscale. A key parameter to characterize the interface physics of …
A hybridized feature extraction for COVID-19 multi-class classification on computed tomography images
COVID-19 has killed more than 5 million individuals worldwide within a short time. It is
caused by SARS-CoV-2 which continuously mutates and produces more transmissible new …
caused by SARS-CoV-2 which continuously mutates and produces more transmissible new …
Comparison of deep learning models in carotid artery Intima-Media thickness ultrasound images: CAIMTUSNet
S Savaş, N Topaloğlu, Ö Kazcı… - Bilişim Teknolojileri Dergisi, 2022 - dergipark.org.tr
Deep learning is a machine learning technique that uses deep neural networks, which are
multilayer neural networks that contain two or more hidden layers. In recent years, deep …
multilayer neural networks that contain two or more hidden layers. In recent years, deep …
Sustainable planning of developing tourism destinations after COVID-19 outbreak: A deep learning approach
Tourist destinations across the globe have been hit by the worst of the crisis that ensued the
Covid-19 pandemic, and this concern is exponentially worse in developing countries …
Covid-19 pandemic, and this concern is exponentially worse in developing countries …