CAJ | 학술논문

为了提高车辆动态称重测量系统的精度，在对误差分析的基础上，本文引入了神经网络算法。通过确定神经网络的输入输出变量，建立了神经网络模型。然后在MATLAB软件上进行网络训练，建立函数关系，最终通过实验验证用神经网络算法提高车辆动态称重精度是确实可行的。
위료제고차량동태칭중측량계통적정도，재대오차분석적기출상，본문인입료신경망락산법。통과학정신경망락적수입수출변량，건립료신경망락모형。연후재MATLAB연건상진행망락훈련，건립함수관계，최종통과실험험증용신경망락산법제고차량동태칭중정도시학실가행적。
In order to improve the Vehicle Weigh in Motion System with precision, the paper introduces Nerve Net Algorithm on error analysis. The article sets up a neural network mod,el by determining the neural network input and output variables. Then, the function is defined by net training on MATLAB software. Finally through the experimental validation of Nerve Net Algorithm improving Weigh in Motion System accuracy is feasible.