Improvement of Fuel Moisture Content Prediction Model

Forest fuel moisture content is an important part of the work of the forest disaster prevention and mitigation, such as the division of forest fire danger rating, forest fire prediction. An important indicator of forest fires is forest fuel moisture content. And it has a strong correlation with local weather, such as temperature, relative humidity, wind speed. It is a result of the combined action of various meteorological elements. It affects the difficult degree of forest fires and fire spread. Studying on the variation of forest fuel moisture content plays a very important role in the forest fire danger forecasting. And it provides theoretical basis for forest fire danger forecast.In this thesis, the existing fuel moisture content prediction model is improved. This, in turn, establishes the prediction model of forest fuel moisture based on time series analysis, linear mixed model and linear measurement error model. Through the analysis of the model test results, the purpose of this paper is to find better ways to predict forest fuel moisture content. The main conclusions of the study are as follows:First of all, using the theory of time series analysis to establish fuel moisture content prediction model. The results show that the precision of established model is up to91.7precent when the relative error is less than3precent. Show that the model can be used to predict the change of fuel moisture content under the condition of no rain. This model effectively improves the forecasting accuracy. The factor of equilibrium moisture content didn’t appear in the model.Secondly, using the thought of linear mixed model, this thesis establishes prediction model. Meteorological factors are introduced into the model as random factors.The method of meteorological factors as random factors is correct.Finally, using the theory of linear measurement error model, this thesis establishes prediction model. The meteorological factors with measurement error are introduced into it. The method of meteorological factors such as temperature, relative humidity, effectively improves the forecasting accuracy. But the method of wind speed is not attain desired consequence.