[HTML][HTML] Research on a hybrid model for cooling load prediction based on wavelet threshold denoising and deep learning: A study in China
F Wang, J Cen, Z Yu, S Deng, G Zhang - Energy Reports, 2022 - Elsevier
Aiming at the problems of insufficient feature extraction, low prediction accuracy and
sensitivity to noise in the cooling load prediction, a hybrid model named WTD–CNN–LSTM …
sensitivity to noise in the cooling load prediction, a hybrid model named WTD–CNN–LSTM …
Seismic damage identification of high arch dams based on an unsupervised deep learning approach
In actual engineering scenarios of arch dams, the incompleteness and nonstationarity of
dynamic monitoring signals limit the accurate cognition of the health state. The effectiveness …
dynamic monitoring signals limit the accurate cognition of the health state. The effectiveness …
Wave excitation force forecasting using neural networks
Many wave energy conversion applications require future knowledge or forecasting of the
wave excitation force values. Most wave energy converter (WEC) control strategies need to …
wave excitation force values. Most wave energy converter (WEC) control strategies need to …
Novel data-driven method for non-probabilistic uncertainty analysis of engineering structures based on ellipsoid model
For the various engineering structures with non-probabilistic uncertain parameters, the
ellipsoid modeling is a momentous analysis method considering parameter cross …
ellipsoid modeling is a momentous analysis method considering parameter cross …
[HTML][HTML] Improvement of road safety through appropriate cargo securing using outliers
M Vlkovský, J Neubauer, J Malíšek, J Michálek - Sustainability, 2021 - mdpi.com
The article focuses on evaluating a transportation experiment that intends to improve road
safety by analyzing transport shocks that significantly affect the system of securing the load …
safety by analyzing transport shocks that significantly affect the system of securing the load …
Rapid transient operation control method of natural gas pipeline networks based on user demand prediction
K Wen, J Jiao, K Zhao, X Yin, Y Liu, J Gong, C Li… - Energy, 2023 - Elsevier
The natural gas pipeline networks play a vital role in Integrated Energy System (IES).
Simultaneously, with the increase in the number and types of users, the operational model …
Simultaneously, with the increase in the number and types of users, the operational model …
Effect of T-shaped spur dike length on mean flow characteristics along a 180-degree sharp bend
An open channel flume with a central 180-degree bend with a rigid bed is designed to
obtain a better understanding of the complex flow pattern around a T-shaped spur dike …
obtain a better understanding of the complex flow pattern around a T-shaped spur dike …
Simulation of bridge pier scour depth base on geometric characteristics and field data using support vector machine algorithm
M Majedi-Asl, R Daneshfaraz… - Journal of Applied …, 2020 - arww.razi.ac.ir
In this paper, two groups of datasets including Froehlich (1988) and USGS were
implemented to simulate scour depth for bridge piers of three shapes (circular, sharp-nose …
implemented to simulate scour depth for bridge piers of three shapes (circular, sharp-nose …
[PDF][PDF] 数智流体力学的发展及油气渗流领域应用
宋洪庆, 都书一, 王九龙, 劳浚铭, 谢驰宇 - 力学学报, 2023 - lxxb.cstam.org.cn
大数据及人工智能技术的崛起推动了数智流体力学的快速发展. 数智流体力学是将流体力学,
大数据和人工智能相结合, 以流体力学场景需求为导向, 形成以“数” 为基础, 以“智” 为核心 …
大数据和人工智能相结合, 以流体力学场景需求为导向, 形成以“数” 为基础, 以“智” 为核心 …
Bridge backwater estimation: A comparison between artificial intelligence models and explicit equations
Estimation of bridge backwater has been one of practical challenges in hydraulic
engineering for decades. In this study, Genetic Programming (GP) has been applied for …
engineering for decades. In this study, Genetic Programming (GP) has been applied for …