Abstract
The water content of forest combustible material is a key factor affecting forest fire and spread, and is the main reference factor for forest fire prediction and forecasting. The live branches, live leaves, dead branches and dead leaves of cap-dou oak, green oak, Yunnan poplar, Yunnan oil fir and silver wattle in central Yunnan were selected as the research objects, and the slope ( x1 ), slope direction ( x2 ), slope position ( x3 ), elevation ( x4 ), wind speed ( x5 ), wind direction ( x6 ), humidity ( x7 ), ground diameter ( x8 ), crown height ( x9 ), crown width ( x10), tree height (x11), depression (x12), and tree species (x13), and used correlation analysis to screen the main modeling factors, and constructed a prediction model of water content of combustible materials by multiple linear regression method. The results show that the correlation between the four factors of slope (x1), slope direction (x2), wind speed (x5) and humidity (x7) and the water content of combustible materials is significant, the water content decreases when the three influencing factors of slope (x1), slope direction (x2) and wind speed (x5) increase, and the water content is higher when the influencing factor of humidity (x7) increases, and the water content of combustible materials is constructed into a model of water content of 20 groups by these factors. Compare the predicted value of the water content prediction model with the actual value to analyze the error of the model, and the results show that the established model can be used to predict the water content. The errors were caused by rainfall during sampling, which absorbed water into the combustible materials and resulted in errors in the moisture content, and wind speed measurements, which resulted in inaccurate wind speed measurements. The established water content model can provide a basis for the classification of forest danger level and combustibility of combustible materials, and can provide help and reference for forest fire prevention and management.
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More From: International Journal of Computer Science and Information Technology
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