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Figure 9 Flow chart summarising methods' performance for each parameter setting on NEMA IQ data.
The searching results are showed in Table 5 with mean values and standard deviations for each parameter setting respectively.
Due to the probabilistic nature of the algorithm, results may differ from another, thus the algorithm was run 30 times for each parameter setting where results for the 30 times running were average.
1000 simulations were conducted for each parameter setting.
For each parameter setting 50 replicated simulations were performed.
5,000 replicates were conducted for each parameter setting.
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For each parameter set up at least three samples were examined.
The results obtained are in excellent agreement with traditional coating methods using single chips for each parameter set.
For each parameter set, hindcasts are generated using initial conditions derived with and without the inclusion of a DA scheme that integrates snow water equivalent (SWE) observations.
Each simulation is run 20times using the same topology with a different seed, and for each parameter set 50 different topologies are generated.
These challenges are significantly complicated by thepossibility of multistability, as different initial conditions could lead todifferent solutions for each parameter set.
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