Three metrics, root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) used for the comparison of MLFF and GMDH results.
Figure 2 shows the short-term water demand forecasts of MLFF and GMDH for 2009.
The results of the MLFF are compared with the GMDH neural network model shown in Table 2.
Consistent with California Sportfishing, the Ninth Circuit found that BOR's yearly issuance of AOP is not an agency action because BOR fully complied with ESA consultation requirements prior to the Secretary choosing MLFF.
287) Using the MLFF regime means that water releases would "tend to be higher in summer and winter, corresponding with greater electricity demand, and lower in the spring and fall, corresponding with decreased electricity demand.
296) The Ninth Circuit found BOR's 2008 AOP purpose to be a description, which supports the idea that AOP is merely a tool that describes how BOR is meeting its preexisting obligations while implementing the MLFF.
It is left to the network itself to sort the input data into this number of categories, since it is not implied by the training data itself, as would be the case for a MLFF, in that a MLFF requires an example solution with its training data.
Note that the situation means that the Kohonen neural network grades a student population according to all the populations it has encountered since it is always learning, whereas a MLFF neural network always grades a population according to the population it was originally trained with.
Using regression analysis to interpolate between modeled alternatives, the PRC (1995) estimated that the annualized economic cost of changing from historical operations to MLFF was $36.
The fluid nature of MLFF operations suggest that short-run economic analyses are an appropriate use of resources.
Section 3 provides the non-parametric modeling approach adopted here as per MLFF neural network with back-propagation algorithm and GMDH neural network with genetic algorithms which are briefly discussed and describes a network with technical analysis rules as inputs.
Our approach is to construct GMDH and MLFF neural networks model using a technical analysis rule as an input.