Abstract:In this paper, wavelet neural network is used to forecast the gravity data of the unmeasurable zone. In the experiment, the forecast precision of gravity data in different landforms is analyzed, contrasting two dimensional inputs with longitude and latitude, and three dimensional inputs with longitude, latitude and altitude. It is found that the use of wavelet neural network can achieve high forecast precision of gravity data in the unmeasurable zone, especially with three dimensional inputs. This is conducive to process the high-precision gravity reference map using interpolation methods.
REN Qiangqiang,WANG Yuegang,TENG Honglei et al. The Gravity Data Forecast of Unmeasurable Zone Based on Wavelet Neural Network[J]. jgg, 2016, 36(4): 359-363.