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Equivalent mechanical parameters and representative elementary volume of rock masses material using a modified fabric tensor
期刊论文
OAI收割
COMPUTERS AND GEOTECHNICS, 2025, 卷号: 183, 页码: 13
作者:
Yin, Jinghan
;
Cui, Zhen
;
Sheng, Qian
;
Sun, Xin
;
Zhang, Maochu
  |  
收藏
  |  
浏览/下载:0/0
  |  
提交时间:2025/06/27
Rock masses
Discrete fracture network
Fabric tensor
Equivalent mechanical parameters
Representative elementary volume
Surface brightness-color relations for red giant branch stars using asteroseismic radii and Gaia distances (the ARD method)
期刊论文
OAI收割
ASTRONOMY & ASTROPHYSICS, 2025, 卷号: 697
作者:
Xiong JP(熊建萍)
;
Cheng QY(程其原)
;
Chen, Xiaodian
;
Li J(李蛟)
;
Zhang, Xiaobin
  |  
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2025/05/13
asteroseismology
parallaxes
stars: distances
stars: fundamental parameters
stars: late-type
Interpretable data-driven chemometric approach for predicting non-optically active water quality parameters using ultraviolet-visible-near infrared absorption spectroscopy and physical-chemical measurements
期刊论文
OAI收割
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2025, 卷号: 331, 页码: 125768
作者:
Zhao, Yubo
;
Zhang, Zhou
;
Hu, Bingliang
;
Liu, Jiacheng
;
Wang, Xueji
  |  
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2025/03/18
Non-optically active water quality parameters
Ultraviolet-visible-near infrared absorption spectroscopy
Physical-chemical measurements
Yangtze River Basin
eXtreme Gradient Boosting
SHapley Additive exPlanations
Performance of the Stellar Abundances and atmospheric Parameters Pipeline adapted for M dwarfs I. Atmospheric parameters from the spectroscopic module
期刊论文
OAI收割
ASTRONOMY & ASTROPHYSICS, 2025, 卷号: 696
作者:
Olander, Terese
;
Gent, Matthew R.
;
Heiter, Ulrike
;
Kochukhov, Oleg
;
Bergemann, Maria
  |  
收藏
  |  
浏览/下载:171/0
  |  
提交时间:2025/04/15
techniques: miscellaneous
stars: fundamental parameters
stars: late-type
stars: low-mass
Multi-source data-driven conjugate Bayesian inference of the distributions of soil shear strength parameter moments
期刊论文
OAI收割
PROBABILISTIC ENGINEERING MECHANICS, 2025, 卷号: 80, 页码: 24
作者:
Liu, Yibiao
;
Ren, Weizhong
  |  
收藏
  |  
浏览/下载:0/0
  |  
提交时间:2025/06/27
Data-driven
Bayesian inference
Shear strength parameters
Statistics
Back analysis of geomechanical parameters based on a data augmentation algorithm and machine learning technique
期刊论文
OAI收割
UNDERGROUND SPACE, 2025, 卷号: 21, 页码: 215-231
作者:
Li, Hui
;
Chen, Weizhong
;
Tan, Xianjun
  |  
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2025/06/27
Back analysis
Machine learning
Data augmentation
Geomechanical parameters
Prediction of Root-Zone Soil Moisture and Evapotranspiration in Cropland Using HYDRUS-1D Model with Different Soil Hydrodynamic Parameter Schemes
期刊论文
OAI收割
WATER, 2025, 卷号: 17, 期号: 5, 页码: 730
作者:
Liao, Qian-Yu
;
Leng, Pei
;
Li, Zhao-Liang
;
Labed, Jelila
  |  
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2025/04/21
evapotranspiration
root-zone soil moisture
simulation
soil hydrodynamic parameters
AmeriFlux
Transverse Velocity Field Measurement of Solar High-resolution Images Based on Unsupervised Deep Learning
期刊论文
OAI收割
RESEARCH IN ASTRONOMY AND ASTROPHYSICS, 2025, 卷号: 25, 期号: 3
作者:
Shang, Zhen-Hong
;
Chen, Long
;
Qiang, Zhen-Ping
;
Bi Y(毕以)
;
Li, Run-Xin
  |  
收藏
  |  
浏览/下载:62/0
  |  
提交时间:2025/04/07
methods: data analysis
techniques: image processing
Sun: fundamental parameters
Monitoring water quality parameters in urban rivers using multi-source data and machine learning approach
期刊论文
OAI收割
JOURNAL OF HYDROLOGY, 2025, 卷号: 648, 页码: 132394
作者:
Liang, Yongchun
;
Ding, Fangyu
;
Liu, Lei
;
Yin, Fang
;
Hao, Mengmeng
  |  
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2025/02/24
Urban rivers
Water quality parameters
Multispectral imagery
Meteorological elements
Land use
Machine learning
Sink-Source Characteristics of Carbon and Nitrogen in Four Typical Urban Water Bodies Within a Medium-Sized City of East China
期刊论文
OAI收割
APPLIED SCIENCES-BASEL, 2025, 卷号: 15, 期号: 3, 页码: 1434
作者:
Xie, Shaowen
;
Yang, Shengnan
;
Deng, Yanghui
;
Xu, Haofan
;
Zhou, Yanbo
  |  
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2025/03/18
urban water environment
water quality parameters
water chemical indicators
sedimentary organic matter
carbon and nitrogen isotope
source quantification