An Empirical Study on the Rate of Regional Production Insurance: A Case of Wheat in Shandong Province

摘要

the comprehensive utilization of wavelet analysis (WT), NAR neural network and kernel density estimation (KDE) method is used to determine the regional production insurance premium in Shandong province. The empirical results show that the NAR neural network has better effect on the trend yield, and it can effectively improve the accuracy of crop rate determination. The wheat insurance premium calculated under the level of 85%-95% protection is lower than the current rate in Shandong.