Frank Young, a laconic Sixth District detective sergeant who shuttled people to the Convention Center on the night of the flood, pointed to the slogan on the fender of a patrol car on loan to the N.O.P.D. from another city — "Excellence in Policing" — and said, "Obviously not ours".
In this point of view, we used 70% flood points for flood map development and 30% (70 30) for the validation process.
The FR model output was validated with remaining 43 (30%) flood points, where 42 points were marked as correct predictions which evinced an accuracy of 97.7% in prediction.
Susceptibility class Verification (30% flood points) Accurate (high to very high class) Prediction accuracy Training (70% flood points) Success (high to very high class) Success rate 1 Very low 0 42 0.977 or 97.7% 0 94 0.94 or 94.0% 2 Low 0 0 3 Medium 1 6 4 High 20 45 5 Very high 22 49 Total 43 100.
FR model requires a large number of flood points as training like 70% (or 100 points) to generate Frequency Ratio, whereas a less number of input data do not fall under all classes of every parameter.
Open image in new window Fig. 4 Output map through FR model: (a) flood susceptibility index with all flood points and (b) overlay of villages and road on flood susceptibility zones Table 3 Spatial distribution (statistics) of flood vulnerability classes in the study area Sl. no.
Seventy percent (70%) of total, i.e. 100 flood points, were selected randomly as the training data set for flood modelling and the rest 30% or 43 points were used for validating the flood model (Rahmati et al. 2016b) (Fig. 1b).
Sibley, 32, a seamstress who lost fabric and other supplies in the flood, pointed to the high water mark on her house, about two feet high, and at the vacant brick ranch houses surrounding her, some with doors open, still airing out.
"We don't manage our storm drainage properly, from a flooding point of view.
A slight influence of viscosity on pressure drop and flooding point was found.
