Studies On Modeling Of Soil Erosion Forecast Under The System Of Soil And Water Conservation Cultivation In Phyllostachy Heterocycla Stands

Soil erosion is the process of soil and other composition materials be destroyed, denuded, taken away and deposition that caused by the power of water, wind, frozen and gravity. Soil erosion is a problem of environment and disaster all over the world, the problem has affected the existence and development of human kind. China is one of the countries that bearing the problem of soil erosion. The area of soil erosion has reached 800 000km~2 in red soil regions of southeast part of China, the most serious area has reached 165 000 km~2 .The red soil regions of southeast part of China has become the most serious soil erosion area except loess plateau of our country.The studies on modeling of soil erosion are the most effective method in the field of soil erosion. There two kinds of model of soil erosion: Empirical model and Physical model. Empirical model is using the former information by the method of statistics to forecast soil erosion and find out the relations of the Rainfall erosion index, vegetation cover, soil organic matter content, soil clay content, degree of slope, slope length. The process of soil erosion is complicated and has too many factors, the model of soil erosion based on process is hard to manipulate, some factors are difficult to get is the model is used in extensive areas, so it may have limited value. For the studies on modeling of soil erosion based on process is a new field, so the studies on empirical model play an important role in the study of soil erosion. So in such conditions empirical model is the most effective method. We aimed to enhance the empirical model fitting and prediction accuracy, to overcome lack of extension and poor accuracy, we use three methods of nonlinear of modeling, given three kinds of model for soil erosion forecast, provide new ideas for the modeling of soil erosion:According to the data collected from TianBaoYan Protected Areas FuJian Province, we use the different gradient, different way of cultivation, different way of fertilization, different way of clearing, different way of dealing with fertilization, different way of bamboo shoots harvest under the same conditions of local condition, forestry density, structure of the age, the way of cultivation as the factors of soil erosion forecast, established a model of nonlinear ridge regression based on kernel function principal component analysis, the model is effective and superior, factors can be got easily, so it can be used in soil erosion forecast under different way of cultivation, at the same time it also provide directions both to the renovation of traditional cultivation and new methods.Based on the univariate non-linear high-dimensional index model GWS (n,1), according to the largest multiple correlation coefficient, we divide variables into auxiliary variables and main variables, another model was established multivariate non-linear high-dimensional index model GWS ( n,m), the two models have a character of nonlinear, non-periodic, non-normal. We get a series of parameters easily; the model can be widely used. The data for modeling is collected from the southeast part of FuJian province, the correlation coefficient reached 0.986, accuracy was significantly higher than USLE model and the model was applied to soil erosion forecast under the system of soil and water conservation cultivation in Phyllostachy Heterocycla, the correlation coefficient reached 0.968, for a very significant level.we use optimization algorithm adaptive real-coded genetic algorithm to find out a series of parameters, we select the parameters avoid the man-made factors, it's different from artificial network model in the"black box-style optimization", the relationship between the data is more transparent, in the case of a large number of samples it also adaptive to a maximum correlation coefficient criterion , we divide variables into auxiliary variables and main variables, the model is accuracy to meet engineering applications in practical, it has a strong guiding significance.If we want to set up multiple regression prediction model, and to achieve considerable accuracy of approximation and prediction, we should confirmed that the impact factor and prediction factors is exist between the exact models is correct between assumes methods, which can be linear or non-linear. According to the estimate of samples to get a series of parameters, as the correlation between predictors is not a consistent relationship between the linear or nonlinear, the existence of a variety of related forms, so a consistent form of linear or non-linear regression model should not reflect the true regression relationship between the impact of forecasting and affect the accuracy of approximation, considering the uneven correlation between the introduction of thought-weighted, so that the impact of the important relations in the regression equation in a larger share of the weight, thus accuracy of the model can be improved. Projection Pursuit combined with multi-objective genetic algorithm used in soil erosion prediction have achieved better results and have higher accuracy in bamboo garden and tea garden the correlation coefficient reached 0.99, in the original literature, the use of linear regression and linear regression methods to predict soil erosion on a correlation coefficient of 0.90 and 0.84, significantly lower in accuracy, the model was applied to soil erosion forecast under the system of soil and water conservation cultivation in Phyllostachy Heterocycla stands to obtain the ideal simulation results. At the same time, it also avoid the situation "dimension curse" that have a large number of samples and the"precision and complexity can't coexistence", the model was set up without any assumptions reduce the man-made factors , high dimensional data will be mapped to a low-dimensional, it provide facilitates to study high-dimensional data in low-dimensional space.