Forecast Study on Civil Aviation Material Consumption Based on Support Vector Machine Regression

As the key part of maintenance support,the accuracy support of aviation material plays an important role in the inventory management cost reduction,fund allocation optimization and flight safety improvement.In order to support the normal take-off of aircraft,improve the operating income of airline companies and reduce the cost of aviation material support,a material consumption forecast model based on support vector machine regression is proposed to overcome the problem which is difficult to forecast aviation material consumption with small sample size and large variation.Taking the actual consumption data of a domestic civil aircraft as an example,the forecast accuracy of the support vector machine regression model is verified.The results show that the support vector machine regression model is of good adaptability for small sample data,and has higher forecast accuracy than that of the exponential smoothing method.