Zobrazeno 1 - 10
of 113
pro vyhledávání: '"Duc-Hai Nguyen"'
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 57, Iss , Pp 102095- (2025)
Study region: The transboundary Imjin River basin, Korea. Study focus: The primary aim is to propose and validate a novel framework for assessing the uncertainty in hydrological models, particularly rainfall–runoff models (RRMs), considering transb
Externí odkaz:
https://doaj.org/article/3e2e7a97354c4c19b53280d696e8088a
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Landslides are a major natural hazard that can significantly damage infrastructure and cause loss of life. In South Korea, the current landslide susceptibility mapping (LSM) approach is mainly based on statistical techniques (logistic regression (LR)
Externí odkaz:
https://doaj.org/article/7644444193d942919b7bb0d435310297
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 46, Iss , Pp 101328- (2023)
Study region: The Ca River basin is located in the North Central Coast area of Vietnam Study focus: This study aims to develop a deep learning framework that is both effective and straightforward in order to forecast water levels in the Ca River basi
Externí odkaz:
https://doaj.org/article/7263cb6f07914197a05a01acfa87fe7b
Publikováno v:
Accounting, Vol 8, Iss 3, Pp 303-314 (2022)
According to the Ministry of Finance's roadmap for applying IFRS in Vietnam, listed enterprises on the stock market and state-owned enterprises holding the dominant power are the first group of enterprises to alter the preparation of financial statem
Externí odkaz:
https://doaj.org/article/daff88e17db14f6bbdee3cc1ea5d387d
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 116, Iss , Pp 103177- (2023)
Despite satellite-based precipitation products (SPPs) providing a worldwide span with a high spatial and temporal resolution, their efficiency in disaster risk forecasting, hydrological, and watershed management remains a challenge due to the signifi
Externí odkaz:
https://doaj.org/article/d63cdb2bae9e4fdd80ce9f85958f83d1
Publikováno v:
IEEE Access, Vol 9, Pp 71805-71820 (2021)
Recently, deep learning (DL) models, especially those based on long short-term memory (LSTM), have demonstrated their superior ability in resolving sequential data problems. This study investigated the performance of six models that belong to the sup
Externí odkaz:
https://doaj.org/article/9e85309437e74a9e9ff047694645bcd4
Publikováno v:
IEEE Access, Vol 9, Pp 125853-125867 (2021)
The establishment of reliable water level prediction models is vital for urban flood control and planning. In this paper, we develop hybrid models (GA-XGBoost and DE-XGBoost) that couple two evolutionary models, a genetic algorithm (GA) and a differe
Externí odkaz:
https://doaj.org/article/87f19dcee7f84ee7a949288427afc324
Autor:
Barbara McPake, Katherine Gilbert, Sreytouch Vong, Bandeth Ros, Phalmony Has, Anh Tuan Khuong, Pham-Duc Phuc, Quoc Cuong Hoang, Duc Hai Nguyen, Latsamy Siengsounthone, Chanthaly Luangphaxay, Peter Annear, Justin McKinley
Publikováno v:
One Health, Vol 14, Iss , Pp 100369- (2022)
We conducted a policy situation analysis in three Mekong region countries, focused on how the animal and human health systems interact to control avian influenza (AI). The study used scoping literature reviews aimed at establishing existing knowledge
Externí odkaz:
https://doaj.org/article/e96a1a90c23246fb88db3d1f18ef4bfb
Publikováno v:
Remote Sensing, Vol 15, Iss 3, p 630 (2023)
Satellite-based precipitation (SP) data are gaining scientific interest due to their advantage in producing high-resolution products with quasi-global coverage. However, since the major reliance of precipitation data is on the distinctive geographica
Externí odkaz:
https://doaj.org/article/0cf81d3d43914043b1362f2165cf7275
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 37:2035-2051