A Novel Daily Runoff Probability Density Prediction Model Based on Simplified Minimal Gated Memory–Non-Crossing Quantile Regression and Kernel Density Estimation
Reliable and accurate daily runoff predictions are critical to water resource management and planning. Probability density predictions of daily runoff can provide decision-makers with comprehensive information by quantifying the uncertainty of forecasting. Models based on quantile regression (QR) ha...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Series: | Water |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4441/15/22/3947 |