Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Haojing Shen"'
Publikováno v:
Hydrology, Vol 11, Iss 11, p 177 (2024)
Similarity to reality is a necessary property of models in earth sciences. Similarity information can thus possess a large potential in advancing geophysical modeling and data assimilation. We present a formalism for utilizing similarity within the e
Externí odkaz:
https://doaj.org/article/f096203b352e4fb3bafa7ec46fdccce3
Publikováno v:
Forecasting, Vol 2, Iss 4, Pp 526-548 (2020)
When there exist catchment-wide biases in the distributed hydrologic model states, state updating based on streamflow assimilation at the catchment outlet tends to over- and under-adjust model states close to and away from the outlet, respectively. T
Externí odkaz:
https://doaj.org/article/32d969ccd76044d3a51b2381ef04db4b
Publikováno v:
Hydrology, Vol 9, Iss 5, p 84 (2022)
This paper presents a comparative geometric analysis of the conditional bias (CB)-informed Kalman filter (KF) with the Kalman filter (KF) in the Euclidean space. The CB-informed KFs considered include the CB-penalized KF (CBPKF) and its ensemble exte
Externí odkaz:
https://doaj.org/article/9ae0d1d621ae4e5a9ae9bab29c5b364f
Publikováno v:
Hydrology, Vol 9, Iss 2, p 35 (2022)
Kalman filter (KF) and its variants and extensions are wildly used for hydrologic prediction in environmental science and engineering. In many data assimilation applications of Kalman filter (KF) and its variants and extensions, accurate estimation o
Externí odkaz:
https://doaj.org/article/3c4731dc77d14813b1c6c964bb6d6bc9
Publikováno v:
Land, Vol 10, Iss 12, p 1363 (2021)
This study examined the influence of political capital on the migration behavior of peasant households in China’s equitable urbanization. While existing research has proven that political capital can increase the wages of migrant workers, leading t
Externí odkaz:
https://doaj.org/article/bc80559a1c9e483d97db0b6b3f0046d5
Publikováno v:
Neural networks : the official journal of the International Neural Network Society. 150
Adversarial examples are usually generated by adding adversarial perturbations on clean samples, designed to deceive the model to make wrong classifications. Adversarial robustness refers to the ability of a model to resist adversarial attacks. And c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f4baf3c076d5682889ee035802afda2
https://pubmed.ncbi.nlm.nih.gov/35279625
https://pubmed.ncbi.nlm.nih.gov/35279625
Publikováno v:
Journal of Hydrology. 575:596-611
We present a novel ensemble extension of the conditional bias-penalized Kalman filter, referred to herein as the conditional bias-penalized ensemble Kalman filter (CBEnKF), and apply it to flood forecasting. The CBEnKF differs from most data assimila
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2426c80a9480bff8be269bdaa949271
https://doi.org/10.1016/j.jhydrol.2019.05.072
https://doi.org/10.1016/j.jhydrol.2019.05.072
Autor:
Brenda Philips, Seong Jin Noh, Sunghee Kim, Albrecht Weerts, Eric Lyons, Erik Pelgrim, Edwin Welles, Haojing Shen, Dong Jun Seo
Publikováno v:
Journal of Hydrology, 598
Journal of Hydrology 598 (2021)
Journal of Hydrology 598 (2021)
We assess the impact of increasing the resolution of hydrologic modeling, calibration of selected model parameters and assimilation of streamflow observation toward event-based urban flood modeling and prediction using WRF-Hydro in the Dallas-Fort Wo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9929080c2e0ef749bb658b8203a47296
https://doi.org/10.1016/j.jhydrol.2021.126236
https://doi.org/10.1016/j.jhydrol.2021.126236
It is necessary to improve the performance of some special classes or to particularly protect them from attacks in adversarial learning. This paper proposes a framework combining cost-sensitive classification and adversarial learning together to trai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f755325d5d7fe20e70326c4ae0fb995
This paper shows a Min-Max property existing in the connection weights of the convolutional layers in a neural network structure, i.e., the LeNet. Specifically, the Min-Max property means that, during the back propagation-based training for LeNet, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee6dd54e0f8474a93a3077c2024fb7d0