Zobrazeno 1 - 10
of 11 400
pro vyhledávání: '"rnn."'
Autor:
Wei Chen
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract This study establishes a deep learning model for personalized travel recommendations based on factors that affect tourists’ purchases to provide users with more accurate and personalized travel recommendations. Firstly, Natural Language Pr
Externí odkaz:
https://doaj.org/article/2c2dfc75f2ff4049bf1594c343b7e919
Publikováno v:
Alexandria Engineering Journal, Vol 109, Iss , Pp 229-238 (2024)
The interface morphology significantly impact the service life of wet clutches friction components in heavy tracked vehicle transmission systems. This paper designs a sliding test and utilizes a recurrent neural network (RNN) model to construct the t
Externí odkaz:
https://doaj.org/article/8d33a001094249e3962a4f08a750176b
Investment risk forecasting model using extreme value theory approach combined with machine learning
Publikováno v:
AIMS Mathematics, Vol 9, Iss 11, Pp 33314-33352 (2024)
Investment risk forecasting is challenging when the stock market is characterized by non-linearity and extremes. Under these conditions, VaR estimation based on the assumption of distribution normality becomes less accurate. Combining extreme value t
Externí odkaz:
https://doaj.org/article/c339ddb779234f078597c2076df76f81
Autor:
Rezky Yuranda, Edi Surya Negara
Publikováno v:
Jurnal Sisfokom, Vol 13, Iss 3, Pp 330-336 (2024)
A web shell is a script executed on a web server, often used by hackers to gain control over an infected server. Detecting web shells is challenging due to their complex behavior patterns. This research focuses on using a deep learning approach to de
Externí odkaz:
https://doaj.org/article/02f9be332f2044069ffab1904143c151
Publikováno v:
Jurnal Saintekom, Vol 14, Iss 2, Pp 195-207 (2024)
This study aims to evaluate the effectiveness and efficiency of various deep learning models in recognizing patterns within diverse biomedical datasets. The methods involved the collection of biomedical data from various public and synthetic sources,
Externí odkaz:
https://doaj.org/article/ff2140175c7540d182f97643b8cb4589
Publikováno v:
Egyptian Informatics Journal, Vol 28, Iss , Pp 100582- (2024)
Urban traffic congestion presents a range of vital difficulties requiring precise prediction models in order to facilitate traffic management for Autonomous Vehicles. This work introduces a novel framework that regulates a Long Short-Term Memory (LST
Externí odkaz:
https://doaj.org/article/c9bc6108d3c44cf891b1dad9991a8d90
Autor:
Silvia Sifath, Tania Islam, Md Erfan, Samrat Kumar Dey, MD. Minhaj Ul Islam, Md Samsuddoha, Tazizur Rahman
Publikováno v:
Natural Language Processing Journal, Vol 9, Iss , Pp 100111- (2024)
Cyberbullying is one of the crimes that arise rapidly through the daily use of technology by different types of people and, most notably, by sharing one’s opinions or feelings on social media in a harmful manner. It has several negative effects on
Externí odkaz:
https://doaj.org/article/1482e1fbd8d846f49d6bff27ea7fc6e1
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Reconstructing high-quality Normalized Difference Vegetation Index time series data is essential for ecological and agricultural applications but remains challenging in heavily cloudy areas. Fusing Sentinel SAR and optical data with deep learning cou
Externí odkaz:
https://doaj.org/article/f5c9af088f254272a3f6bb04a9da38d8
Publikováno v:
MethodsX, Vol 13, Iss , Pp 102946- (2024)
The rapid advancement in Artificial Intelligence (AI) and big data has developed significance in the water sector, particularly in hydrological time-series predictions. Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks have
Externí odkaz:
https://doaj.org/article/c05a4bdb72214b818d40a20cc6992331
Autor:
Ihar Lobach, Michael Borland
Publikováno v:
Machine Learning with Applications, Vol 18, Iss , Pp 100585- (2024)
This research illustrates how time-series forecasting employing recurrent neural networks (RNNs) can be used for anomaly detection in particle accelerators—complex machines that accelerate elementary particles to high speeds for various scientific
Externí odkaz:
https://doaj.org/article/7028d477cc4744e6abf749fa72bd5c22