Zobrazeno 1 - 10
of 1 606
pro vyhledávání: '"lstm network"'
Publikováno v:
Journal of Rock Mechanics and Geotechnical Engineering, Vol 16, Iss 12, Pp 5179-5192 (2024)
The interpretation of the cone penetration test (CPT) still relies largely on empirical correlations that have been predominantly developed in resource-intensive and time-consuming calibration chambers. This paper presents a CPT virtual calibration c
Externí odkaz:
https://doaj.org/article/a34218855bf24b48a995093eacc026bd
Autor:
Dana Utebayeva, Lyazzat Ilipbayeva
Publikováno v:
Scientific Journal of Astana IT University, Pp 60-75 (2024)
In recent years, the potential risks posed by easily moving objects have highlighted the need for intelligent surveillance systems in protected areas, primarily to ensure the safety of human lives. Among the most common of these objects are unmanned
Externí odkaz:
https://doaj.org/article/71812ab3a60e4d4da4163318b3e4abe1
Publikováno v:
电力工程技术, Vol 43, Iss 5, Pp 189-198 (2024)
In severe convective weather, transmission lines are prone to lightning strikes, wind swings, rain flashes and other faults that threaten the safe operation of the power grids. To overcome the problem that the existing nowcasting cannot fully meet th
Externí odkaz:
https://doaj.org/article/c93b381ac4c0497ca85fae9ba64eb3e0
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Accurate and rapid prediction of water quality is crucial for the protection of aquatic ecosystems. This study aims to enhance the prediction of total phosphorus (TP) concentrations in the middle reaches of the Yangtze River by integrating a
Externí odkaz:
https://doaj.org/article/44ead545a90b45108b61bff7a3cc0a8f
Publikováno v:
Electronic Research Archive, Vol 32, Iss 7, Pp 4543-4562 (2024)
Wave height prediction is hampered by the volatility and unpredictability of ocean data. Traditional single predictors are inadequate in capturing this complexity, and weighted fusion methods fail to consider inter-model correlations, resulting in su
Externí odkaz:
https://doaj.org/article/951e4bf768ad428db1e7079cb5adfda6
Autor:
CHEN Jianrun, MAO Weining
Publikováno v:
Zhihui kongzhi yu fangzhen, Vol 46, Iss 3, Pp 95-101 (2024)
Two bearing-only maneuver detection methods based on deep learning are proposed to address the problems of long detection delay and low accuracy of existing bearing-only maneuver detection methods for underwater targets. The bearing observations of t
Externí odkaz:
https://doaj.org/article/96261739a642475d8b8fd9879fed7cdf
Publikováno v:
In Engineering Structures 15 January 2025 323 Part A
Autor:
Fan, Yuqian a, b, ⁎, Zhao, Jifei a, Li, Yi a, Wang, Jianping a, Yang, Fangfang c, Tan, Xiaojun b, c, ⁎⁎
Publikováno v:
In Energy 1 January 2025 314
Publikováno v:
Journal of Computer Science and Technology, Vol 24, Iss 2 (2024)
Stock market prediction is an interesting and complex problem that has recently been in the limelight, thanks to the significant accuracy achieved by deep learning models. However, a complete platform with prediction and risk analysis ability is unav
Externí odkaz:
https://doaj.org/article/8879b145253848a8b9606d51934d23c6
Publikováno v:
Franklin Open, Vol 8, Iss , Pp 100157- (2024)
The prediction of system responses for a given fatigue test bench drive signal is a challenging problem, since highly dynamic loads from measurement campaigns must be reproduced accurately. Linear frequency response function models are commonly used
Externí odkaz:
https://doaj.org/article/77670e0abdd14d7d88421191594d6827