Results 1 to 10 of about 543,959 (260)

Enhancing electrical structure in magnetotelluric inversion by the constraint of minimum cross-gradient support coupling

Frontiers in Earth Science
The geophysical inversion problem is inherently underdetermined. Constrained inversion, by incorporating prior information, can effectively reduce the ambiguity in inversion results.
Luolei Zhang, Chongjin Zhao, Han Song
exaly   +4 more sources

Approximating the Gradient of Cross-Entropy Loss Function

IEEE Access, 2020
A loss function has two crucial roles in training a conventional discriminant deep neural network (DNN): (i) it measures the goodness of classification and (ii) generates the gradients that drive the training of the network. In this paper, we approximate
, Murray Loew
exaly   +3 more sources

Cross-Gradient Constrained Joint Inversion of Seismic Impedance and Resistivity

Applied Sciences
Individual geophysical inversions reflect only limited physical parameters of the subsurface and often suffer from non-uniqueness. Joint inversion of different geophysical datasets can mitigate this problem by integrating complementary information.
Deyong Wu, Chunchao Chen, Penglei Bo, Junfeng Ding, Xiao Zhang, Qiuzhao Zhang   +5 more
doaj   +2 more sources

Fast 3D joint inversion of gravity and magnetic data based on cross gradient constraint

Geodesy and Geodynamics, 2023
The gravity and magnetic data can be adopted to interpret the internal structure of the Earth. To improve the calculation efficiency during the inversion process and the accuracy and reliability of the reconstructed physical property models, the triple ...
Sheng Liu, Shuanggen Jin, Songbai Xuan   +2 more
exaly   +3 more sources

3-D cross-gradient joint inversion of seismic refraction and DC resistivity data [PDF]

Journal of Applied Geophysics, 2017
Abstract We present a 3-D cross-gradient joint inversion algorithm for seismic refraction and DC resistivity data. The structural similarity between seismic slowness and resistivity models is enforced by a cross-gradient term in the objective function that also includes misfit and regularization terms.
Richard Hobbs, Zhanjie Shi, Gang Tian
exaly   +3 more sources

High-Resolution Cooperate Density-Integrated Inversion Method of Airborne Gravity and Its Gradient Data

Remote Sensing, 2021
Airborne (or satellite) gravity measurement is a commonly used remote sensing method to obtain the underground density distribution. Airborne gravity gradiometry data have a higher horizontal resolution to shallower causative sources than airborne ...
Guoqing Ma, Tong Gao, Lili Li, Taihan Wang, Runxin Niu, Xinwei Li   +5 more
doaj   +1 more source

Cross-Gradient Aggregation for Decentralized Learning from Non-IID data

CoRR, 2021
ICML 2021 accepted ...
Esfandiari, Yasaman, Tan, Sin Yong, Jiang, Zhanhong, Balu, Aditya, Herron, Ethan, Hegde, Chinmay, Sarkar, Soumik   +6 more
openaire   +4 more sources

Improving the prediction of wind speed and power production of SCADA system with ensemble method and 10-fold cross-validation

Case Studies in Chemical and Environmental Engineering, 2023
This research used machine-learning-based forecasting models to estimate a Supervisory control and data acquisition system's wind speed and electricity production.
Seyed Matin Malakouti
doaj   +1 more source

Observation of cross phase modulation in cold atom gradient echo memory

New Journal of Physics, 2022
Strong nonlinear interactions between single photons have important applications in optical quantum information processing. Demonstrations of these interactions in cold atomic ensembles have largely been limited to exploiting slow light generated using ...
Anthony C Leung, K S Ida Melody, Aaron D Tranter, Karun V Paul, Geoff T Campbell, Ping Koy Lam, Ben C Buchler   +6 more
doaj   +1 more source

High-Precision Joint Magnetization Vector Inversion Method of Airborne Magnetic and Gradient Data with Structure and Data Double Constraints

Remote Sensing, 2022
Airborne magnetic and gradient measurements are commonly used geophysical remote sensing tools to obtain the distribution features of ore mineral bodies.
Guoqing Ma, Yanan Zhao, Bowen Xu, Lili Li, Taihan Wang   +4 more
doaj   +1 more source