Machine learning was applied to predict the plant uptake and transport of engineered
nanoparticles (ENPs). A back propagation neural network (BPNN) was used to predict the …

Flooding is a natural hazard that poses considerable risks to the mountainous regions of
Taiwan. Accurate flood modeling can be used for flood prevention, but it requires detailed …

This study aimed to establish a machine learning (ML)-based rice blast predicting model to
decrease the appreciable losses based on short-term environment data. The average …

Rice growth rate prediction is crucial to achieve precision agriculture. In this study, growth
data from three different rice cultivars at two different climate regions in Taiwan were used to …

Accurate and simple prediction of farmland groundwater level (GWL) is an important aspect
of agricultural water management. A farmland GWL prediction model, GWPRE, was …

The correlations of the multiple time-series outputs of an original simulation model are
difficult to take into account using traditional surrogate model techniques. This study …

The field capacity (FC) and permanent wilting point (PWP) are fundamental hydrological
properties critical for assessing water availability within soils, rather than direct measures of …

A Poisson regression based on eigenvector spatial filtering (ESF) is proposed to evaluate
the flood risk in the middle reaches of the Yangtze River in China. Regression analysis is …

An efficient underground reservoir management requires reliable hydrogeological
parameters, such as infiltration coefficient, percolation rate and specific yield (S y) values …

Artificial intelligence has been widely applied to water depth retrieval across various
environments, deemed essential for habitat modeling, hydraulic structure design, and …