Advances in Artificial Intelligence / 2011 / Article / Tab 1

Research Article

Development of Artificial Neural-Network-Based Models for the Simulation of Spring Discharge

Table 1

Selection of the best model from the batch backpropagation algorithm.

Model inputsNo. of inputsAlgorithmArchitectureNo. of hidden layerTrainingTestingValidation
RDCRDCRDC

Rt, Et, Tt3[3-4-1]One 0.671 −0.235 0.600 −0.133 0.594 −0.883
Qt−1, Rt, Rt−1, Et, Et 1 , Tt, Tt 1 7[7-2-1]One 0.979 0.956 0.979 0.941 0.986 0.961
Qt−1, Qt−2, Rt, Rt−1, Rt−2, Et, Et−1, Et−2, Tt, Tt−1, Tt−211[11-28-1]One 0.959 0.907 0.921 0.809 0.953 0.893
Qt−1, Qt−2, Qt-3, Rt, Rt−1, Rt−2, Rt−3, Et, Et−1, Et−2, Et−3, Tt, Tt−1, Tt−2, Tt−315[15-21-1]One 0.943 0.851 0.945 0.865 0.967 0.928
Qt−1, Qt−2, Qt−3, Qt−4, Rt, Rt−1, Rt−2, Rt−3, Rt−4, Et, Et−1, Et−2, Et−3, Et−4, Tt, Tt−1, Tt−2, Tt−3, Tt−419Batch backpropagation[ 19-10-1]One
Rt, Et, Tt3[3-2-2-1]Two 0.623 −0.575 0.623 −1.378 0.554 −1.322
Qt−1, Rt, Rt−1, Et, Et−1, Tt, Tt−17[7-6-5-1]Two 0.982 0.960 0.970 0.935 0.975 0.944
Qt−1, Qt−2, Rt, Rt−1, Rt−2, Et, Et−1, Et−2, Tt, Tt−1, Tt−211[11-4-3-1]Two 0.988 0.975 0.981 0.960 0.967 0.907
Qt−1, Qt−2, Qt−3, Rt, Rt−1, Rt−2, Rt−3, Et, Et−1, Et−2, Et−3, Tt, Tt−1, Tt−2, Tt−315[15-7-3-1]Two 0.980 0.958 0.960 0.901 0.985 0.963
Qt−1, Qt−2, Qt−3, Qt−4, Rt, Rt−1, Rt−2, Rt−3, Rt−4, Et, Et−1, Et−2, Et−3, Et−4, Tt, Tt−1, Tt−2, Tt−3, Tt−419[ 19-9-4-1]Two

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