Fuzzy multi-objective function for rainfall-runoff model calibration

By Pao-Shan Yu, Tao‐Chang Yang. 2000

102 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Ocean Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/2a43ebf70018312e9166fb8b60a59683d88ee19c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

1. Kwok-Wing Chau
2. Chun-tian Cheng
3. Martijn J. Booij
4. Maarten S. Krol
5. Nanee Chahinian
6. Chunping Ou
7. Roger Moussa
8. Demetris Koutsoyiannis

In Ocean Engineering

1. Kwok-Wing Chau
2. Martijn J. Booij
3. Maarten S. Krol
4. Nanee Chahinian
5. Chunping Ou
6. Chun-tian Cheng
7. Roger Moussa
8. Demetris Koutsoyiannis

In Water Science and Technology

1. Kwok-Wing Chau
2. Chun-tian Cheng
3. Martijn J. Booij
4. Maarten S. Krol
5. Linda M. See
6. Nanee Chahinian
7. C. Dawson
8. Robert J. Abrahart

Citations in the corpus

• Balance between calibration objectives in a conceptual hydrological model (2010, methodology): “This is in contrast to themethods in which weights have to be assigned explicitly to different objectives, e.g. in a linear way (Madsen, 2003), or in a fuzzy way (Yu & Yang, 2000).”
• Comparison of different multi-objective calibration criteria using a conceptual rainfall-runoff model of flood events. (2007, background): “On the opposite, the mean absolute percent error tends to emphasize the low flows (Yu and Yang, 2000).”
• HydroTest: A web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts (2007, background): “…that is often expressed in percentage terms using different phrasing e.g. "Error in Volume" (Rajurkar et al., 2004); “Error of Total Runoff Volume” (EV; Lin and Chen, 2004); "Percent Bias" (PBIAS; Yapo et al., 1996; Yu and Yang, 2000); "Deviation of Runoff Volumes" (Dv; WMO, 1986; ASCE, 1993).”
• Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall–runoff model calibration (2002, methodology): “CRRS generally have a large number of parameters, which cannot be directly obtained from measurable quantities of catchment characteristics, and hence model calibration is entailed.”
• ANN and Fuzzy Logic Models for Simulating Event-Based Rainfall-Runoff (2006, unknown): “Yu and Yang 2000 presented a fuzzy multiobjective function FMOF to improve the performance of conventional objective functions of root-meansquare error RMSE and mean percentage error MPE that are used in calibrating rainfall-runoff conceptual models.”
• One decade of multi-objective calibration approaches in hydrological modelling: a review (2010, unknown): “Yu & Yang, 2000 ; Seibert & McDonnell, 2002 ; Cheng et al.”