Open Access. Powered by Scholars. Published by Universities.®
- Keyword
Articles 1 - 2 of 2
Full-Text Articles in Computational Engineering
Bibliometric Survey On Effects Of Climate Change On Incidences Of Infectious Diseases, Seema Harshad Patil, Yatharth Jain, Vedant Marathe
Bibliometric Survey On Effects Of Climate Change On Incidences Of Infectious Diseases, Seema Harshad Patil, Yatharth Jain, Vedant Marathe
Library Philosophy and Practice (e-journal)
For understanding the influx of Infectious Diseases, research of climate change and its effects pertaining to the diseases is important. The motive of this bibliometric survey is to understand the research which has been carried out regarding the aforementioned topics. This paper summarizes the research in the 21st Century from 2001 to present. We conducted this analysis using tools such as Gephi, Researchgate, Scopus, ScienceScape, Google Scholar and Mapchart. This Bibliometric Survey on “Effects of Climate Change on Infectious Diseases” showed that maximum publications are articles. These publications are from conferences and journals related to Environmental Science. The United States …
Sensitivity Analysis Of Data-Driven Groundwater Forecasts To Hydroclimatic Controls In Irrigated Croplands, Alessandro Amaranto, Francesca Pianosi, Dimitri Solomatine, Gerald Corzo-Perez, Francisco Munoz-Arriola
Sensitivity Analysis Of Data-Driven Groundwater Forecasts To Hydroclimatic Controls In Irrigated Croplands, Alessandro Amaranto, Francesca Pianosi, Dimitri Solomatine, Gerald Corzo-Perez, Francisco Munoz-Arriola
Biological Systems Engineering: Papers and Publications
In the last decades, advancements in computational science have greatly expanded the use of artificial neural networks (ANNs) in hydrogeology, including applications on groundwater forecast, variable selection, extended lead-times, and regime-specific analysis. However, ANN-model performance often omits the sensitivity to ob- servational uncertainties in hydroclimate forcings. The goal of this paper is to implement a data-driven modeling framework for assessing the sensitivity of ANN-based groundwater forecasts to the uncertainties in observational inputs across space, time, and hydrological regimes. The objectives are two-folded. The first objective is to couple an ANN model with the PAWN sensitivity analysis (SA). The second objective …