Abstract:There is a lag between the latest development of the heuristic algorithm and its application in environmental model calibration. Besides, heuristic algorithms are usually thought to be deterministic and can hardly account for the equifinality of different parameters. To fix these limitations, we proposed a novel elite opposition-modified moth-flame optimizer (EOMFO) and presented a scheme combining it with the frequency statistical method for auto-calibration and prediction uncertainty estimation. A case study… Show more
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