Geology Reference
In-Depth Information
Fig. 7.28 ANN-LM modeled and observed evaporation data at the Chahnimeh reservoirs region:
(a) training data; (b) validation data
Fig. 7.29 ANN-BFGS modeled and observed evaporation data at the Chahnimeh reservoirs
region: (a) training data; (b) validation data
Fig. 7.30 ANN-CG modeled and observed evaporation data at the Chahnimeh reservoirs region:
(a) training data; (b) validation data
models during training and validation phases are shown in Fig.
7.28
. The corre-
sponding plots of ANN-BFGS and ANN-CG are shown in Figs.
7.29
and
7.30
.
For ANFIS, the number of membership functions for each input was set to three
and the input data were scaled between [0, 1]. The membership function type was
selected as Gauss bell shaped. The results in the training and testing of ANFIS are
listed in Table
7.9
, along with those of LLR methods. It can be observed that ANN-
LM and LLR have better performances than the ANFIS model. The best results
