APPLICATION RESEARCH OF SUPPORT VECTOR REGRESSION ALGORITHM IN AHFO TEST OF SOIL WATER CONTENT

Active heating optical fiber method(AHFO)can realize the distributed measurement of soil moisture content in situ. But due to the complex environment of the site, the test results obtained by the interpretation of the existing moisture content calculation model are prone to large errors. Based on the experimental research, this paper explored the effect of soil dry density on the calculation of water content of AHFO method, and introduced support vector regression(SVR)algorithm into the calculation model of water content. The numerical result was compared with the traditional calculation model. The research results show that the dry density of the soil is an important factor that affects the accuracy of the water content calculation model. The larger the dry density fluctuation, the larger the calculation error of the traditional calculation model. The higher the soil content, the lower the sensitivity of the calculation model. Compared with the traditional water content calculation model, the radial basis kernel support vector regression method considering the influence of dry density has a higher calculation accuracy, and it is recommended to be applied in the test of the water content AHFO method.