Results 81 to 90 of about 5,130 (182)

Vessel Trajectory Prediction at Inner Harbor Based on Deep Learning Using AIS Data

Journal of Marine Science and Engineering
This study aims to improve vessel trajectory prediction in the inner harbor of Busan Port using Automatic Identification System (AIS) data and deep-learning techniques.
Gil-Ho Shin, Hyun Yang
doaj   +1 more source

Forecasting Shifts in Europe's Renewable and Fossil Fuel Markets Using Deep Learning Methods

Energy Science & Engineering
Accurate forecasts of renewable and nonrenewable energy output are essential for meeting global energy needs and resolving environmental issues. Energy sources like the sun and wind are variable, making forecasting difficult.
Yonghong Liu, Muhammad S. Saleem, Javed Rashid, Sajjad Ahmad, Muhammad Faheem   +4 more
doaj   +1 more source

Cryptocurrency Price Prediction Model Using GRU, LSTM and Bi-LSTM Machine Learning Algorithms

Proceedings of the International Conference on Applied Innovations in IT
The rapid rise of cryptocurrencies has indeed created both investment opportunities and forecasting challenges. Accurate predictions of cryptocurrency prices are crucial for traders and financial planners to make informed decisions.
Laila Suwaid Said
doaj   +1 more source

Evaluation of Solar Radiation Prediction Models Using AI: A Performance Comparison in the High-Potential Region of Konya, Türkiye

Atmosphere
Solar radiation is one of the most abundant energy sources in the world and is a crucial parameter that must be researched and developed for the sustainable projects of future generations.
Vahdettin Demir
doaj   +1 more source

State of the art in energy consumption using deep learning models

AIP Advances
In the literature, it is well known that there is a bidirectional causality between economic growth and energy consumption. This is why it is crucial to forecast energy consumption.
Shikha Yadav, Nadjem Bailek, Prity Kumari, Alina Cristina Nuţă, Aynur Yonar, Thomas Plocoste, Soumik Ray, Binita Kumari, Mostafa Abotaleb, Amal H. Alharbi, Doaa Sami Khafaga, El-Sayed M. El-Kenawy   +11 more
doaj   +1 more source

Predicting Power Consumption Using Deep Learning with Stationary Wavelet

Forecasting
Power consumption in the home has grown in recent years as a consequence of the use of varied residential applications. On the other hand, many families are beginning to use renewable energy, such as energy production, energy storage devices, and ...
Majdi Frikha, Khaled Taouil, Ahmed Fakhfakh, Faouzi Derbel   +3 more
doaj   +1 more source

Retraction Notice: Deep Recurrent Architectures for EEG-Based Classification of Major Psychiatric Disorders: A Comparative Study of LSTM, BiLSTM, GRU, BiGRU, and Their Hybrids

IEEE Access
Bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SZ) are serious mental disorders that affect millions of people worldwide. Due to the overlapping clinical symptoms, early and accurate diagnosis of these disorders is difficult ...
Osman Cetin, Hamdi Melih Saraoglu
doaj   +1 more source

DAB-GRU: A Dynamic Attention-Based Bidirectional Network for Anomaly Detection of On-Board Time-Series Data in High-Speed Rail

IEEE Access
Time-series data from the Chinese Train Control System (CTCS) exhibits complex multidimensional correlations. Traditional statistical and machine learning methods are limited by local statistical features, failing to capture the underlying associative ...
Wenbing Zhu, Ming Xu, Zhiyang Yu, Yang Wang, Xinjun Gao, Xiaoming Chen   +5 more
doaj   +1 more source

Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels

Scientific Reports
To tackle the challenge of discrete and complex monitoring data generated during high-speed rail tunnel construction, this study proposes a hybrid deep learning model for deformation forecasting.
Zeping Yang, Zhikai Cheng, Da Wu
doaj   +1 more source

Prediction of aero engine remaining service life using a bidirectional GRU model with self attention mechanism. [PDF]

Sci Rep
Fu W, Wang H, Sun X, Song Z, Xu S, Xu M, Liu L, Razak NA.   +7 more
europepmc   +1 more source