CAJ | 학술논문

针对中小型污水处理厂出水监测设备长期监测精度不稳定的实际情况,利用灰色理论和广义回归神经网络建立了灰色神经网络模型,根据采集到的污水处理厂进水参数对出水参数进行预测,并对灰色神经网络模型和广义灰色神经网络模型的预测结果进行了对比,对比结果表明:这种灰色神经网络模型的精度明显优于广义神经网络模型,适合应用.
침대중소형오수처리엄출수감측설비장기감측정도불은정적실제정황,이용회색이론화엄의회귀신경망락건립료회색신경망락모형,근거채집도적오수처리엄진수삼수대출수삼수진행예측,병대회색신경망락모형화엄의회색신경망락모형적예측결과진행료대비,대비결과표명:저충회색신경망락모형적정도명현우우엄의신경망락모형,괄합응용.
@@@@According to the unstable accuracy of long-term monitoring to the small and medium sewage treatment plant, grey neural network model is established by making use of grey theory and generalized regression neural network. In terms of bilging pa-rameter collected from the sewage treatment plant, we make a prediction to the effluent parameter and make a contrast to the result of the prediction between grey neural network and generalized regression neural network. It turns out that the accuracy of the former is extremely superior to the latter. It is suit for application.