CAJ | 학술논문

针对红枣红外辐射干燥含水率的变化具有非线性和时变性、很难利用现有的模型构造一个数学模型来描述其变化规律的问题，利用MatLab 神经网络工具箱和红枣红外辐射干燥特性试验数据建立了神经网络预测模型。通过对实测值和模型预测值进行分析研究，得出利用 BP神经网络可以较快速、准确地建立模型来描述含水率的变化规律，且模型的预测值与试验测试值误差较小，能很好地实现在线预测的效果。
침대홍조홍외복사간조함수솔적변화구유비선성화시변성、흔난이용현유적모형구조일개수학모형래묘술기변화규률적문제，이용MatLab 신경망락공구상화홍조홍외복사간조특성시험수거건립료신경망락예측모형。통과대실측치화모형예측치진행분석연구，득출이용 BP신경망락가이교쾌속、준학지건립모형래묘술함수솔적변화규률，차모형적예측치여시험측시치오차교소，능흔호지실현재선예측적효과。
Changes in dates for infrared radiation drying moisture nonlinear and time -varying , difficult to use existing models used to construct a mathematical model to describe the variation .Articles using MATLAB neural network toolbox and dates infrared radiation drying characteristics of test data to establish a neural network prediction model .Through the measured and predicted values were analyzed studies that illustrate the use of BP neural network can be more rapid ,accu-rate modeling is used to describe the variation of moisture content ,and the predictive value of the model with experimental test error is small , well implementation of online prediction results .