Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes
Predictive performance is one of the most important issues for practical applications of
ensemble hydroclimatic forecasts. While different forecasting studies tend to use different …
ensemble hydroclimatic forecasts. While different forecasting studies tend to use different …
Decomposition of the mean absolute error (MAE) into systematic and unsystematic components
When evaluating the performance of quantitative models, dimensioned errors often are
characterized by sums-of-squares measures such as the mean squared error (MSE) or its …
characterized by sums-of-squares measures such as the mean squared error (MSE) or its …
[HTML][HTML] Export sales forecasting using artificial intelligence
Sales forecasting is important in production and supply chain management. It affects firms'
planning, strategy, marketing, logistics, warehousing and resource management. While …
planning, strategy, marketing, logistics, warehousing and resource management. While …
[HTML][HTML] A visualized hybrid intelligent model to delineate Swedish fine-grained soil layers using clay sensitivity
In the current paper, a hybrid model was developed to generate 3D delineated soil horizons
using clay sensitivity (S t) with 1 m depth intervals in a landslide prone area in the southwest …
using clay sensitivity (S t) with 1 m depth intervals in a landslide prone area in the southwest …
A rational performance criterion for hydrological model
D Liu - Journal of Hydrology, 2020 - Elsevier
Performance criteria are essential for hydrological model identification or its parameters
estimation. The Kling-Gupta efficiency (KGE), which combines the three components of …
estimation. The Kling-Gupta efficiency (KGE), which combines the three components of …
BK-SWMM flood simulation framework is being proposed for urban storm flood modeling based on uncertainty parameter crowdsourcing data from a single functional …
C Liu, W Li, C Zhao, T ** Tool: An open source web application for assessing groundwater sustainability
Decision makers need an accurate understanding of aquifer storage trends to effectively
manage groundwater resources. Groundwater is difficult to monitor and quantify since the …
manage groundwater resources. Groundwater is difficult to monitor and quantify since the …
Extending SC-PDSI-PM with neural network regression using GLDAS data and Permutation Feature Importance
Abstract The Palmer Drought Severity Index (PDSI) ranges from− 10 to 10 and is used for
monitoring drought extent and severity. PDSI is a monthly global gridded data set with partial …
monitoring drought extent and severity. PDSI is a monthly global gridded data set with partial …