Prediction model of brine evaporation rate based on back-propagation neural network
Brine evaporation rate is an important technical parameter in the production and management of salt pans.By set-ting up an outdoor brine evaporation experimental device,the relationship between irradiation intensity,wind speed,ambi-ent temperature,relative humidity,brine temperature,brine concentration,and brine evaporation rate was analyzed.The pre-diction model of brine evaporation rate was constructed by using back-propagation(BP)neural network and compared with the model constructed by traditional regression method.The results showed that the determination coefficients R2 of BP neu-ral network model and nonlinear regression model were 0.902 and 0.884,respectively,and the average relative error were 15.723%and 18.943%,respectively.It was indicated that the fitting effect and prediction ability of BP neural network model were better than nonlinear regression model.It was feasible to use BP neural network to construct the prediction model of brine evaporation rate,which could realize the rapid estimation of evaporation rate.
NETL
NSTL
万方数据
维普
