首先，以我国2002—2012年的605件专利侵权诉讼案件为样本，采用多元回归方法，对我国专利侵权赔偿额的影响因素进行了定量研究，结果显示：侵权时间、侵权人数等12个变量对赔偿额有显著影响。其次，根据回归结果，选取以上12个变量，建立了BP神经网络模型，预测了专利侵权赔偿额，结果显示：该模型对0-5万元区间段赔偿额预测的正确率达94%，对5-10万元区间段赔偿额预测的正确率达68%，对10-50万区间段赔偿额预测的正确率达85%。最后，根据研究结果，提出了完善我国专利侵权赔偿制度的对策建议。

Based on the samples of 605 patent infringement cases judged during the year 2002 to 2012, the empirical study is conducted to explore the impact factors of compensation about the patent infringement damage in china by using the multiple regression analysis model. The results show that 12 variables, such as ‘the time of infringement’, ‘the number of infringers’ variables have a significant effect on the amount of damage judged. Secondly, by selecting the above 12 variables and establishing a BP neural network model, the study forecasts the amount of damage. The results show that by applying this model, the accuracy of forecasting for compensation on IP infringement ranging from RMB 0-50,000 can reach 94%; the accuracy of forecasting for compensation on IP infringement ranging from RMB 50,000-100,000 can reach 68%; the accuracy of forecasting for compensation on IP infringement ranging from RMB100,000-500,000 can reach 85%. Finally, some recommendations are given to improve patent compensation system in china.