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The regression between the network output and the corresponding target is equal to 100% which means a high accuracy.
These computations are based on the minimization of the quadratic difference between the network output and Residence Time Distributions (RTDs) obtained through CFD simulations.
The results show that the average relative errors between the network output values and the calculated values of off-design condition are less than 1%, which verify the accuracy, feasibility and validity of this method.
This process is repeated until the error between the network output and desired output (PR measurements) meets the prescribed requirement.
This process is repeated until the error between the network output and desired output (radar measurements) meets the prescribed requirement.
The backpropagation algorithm works by computing the error between the network output and the corresponding target value and propagating this backward through the network to update the weights.
Similar(47)
The regression between the network outputs and the experimental data was more than 0.95.
From assessment of the ANN, it is found that the network including two hidden layers with 4 neurons in every layer results in the least difference between the network outputs and the experimental data, providing the best performance.
Fig. 10 Regression analysis between the network outputs and the optimization targets based on the MLPNN Fig. 11 Regression analysis between the network outputs and the optimization targets based on the RBFNN.
The neural network, trained by the 0.10 target error, presents a 0.086 error and a 0.850 correlation between the network outputs and the training sets.
Furthermore, as represented in Fig. 3, the distributions of the network errors, the difference between the network outputs and the training data sets, showed the decreases as the target errors decrease from 0.10 to 0.005.
More suggestions(17)
between the network simulator
between the process output
between the network throughput
between the detector output
between the network formation
between the sensor output
between the network address
between the analog output
between the network operator
between the inverter output
between the network orientation
between the network error
between the actuator output
between the index output
between the network chemical
between the network traffic
between the input output
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