CAJ | 학술논문

本文讨论了35通道地基微波辐射计反演温度、水汽廓线的BP神经网络反演方法,对神经网络的层次结构、样本选择、训练方法等进行了分析,并将反演结果与探空数据进行了比对,分析了误差产生的原因。结果表明,BP神经网络反演的廓线数据具有很好的精度,满足实际使用要求。
본문토론료35통도지기미파복사계반연온도、수기곽선적BP신경망락반연방법,대신경망락적층차결구、양본선택、훈련방법등진행료분석,병장반연결과여탐공수거진행료비대,분석료오차산생적원인。결과표명,BP신경망락반연적곽선수거구유흔호적정도,만족실제사용요구。
A method of BP neural network used for inversion of temperature and water vapor profiles with 35 -channel ground-based microwave radiometer is discussed; and its hierarchical structure, sample selection and training method is analyzed. The result of retrieval is compared with that observed with radiosonde and the cause of the error is analyzed. The result shows that the data of temperature and water vapor profiles retrieved by using BP neural network is accurate and using this method can meet the requirement of practical applications.