Soil Data Construction Method for Cross-country Trafficability Analysis

doi:10.16182/j.issn1004731x.joss.17-0069

Abstract

Abstract: Soil is one of the most important factors influencing the off-road maneuver of the army. The combination of soil and weather factors makes cross-country trafficability analysis extremely complicated. The soil data from unified soil classification system (USCS) are the basis for the analysis of soil trafficability. In this paper, the random forest method is used to predict the type of soil by using various attribute information. The method extracts sample data from existing USCS soil data to construct multiple random forest models, then analyses the accuracy of random forests and the importance of characteristic variables, and finally uses the third random forest model to process soil database according to the characteristics of the data. Compared with the previous methods, this method is more accurate and can meet the requirements of cross-country trafficability analysis.

Key words: cross-country trafficability, soil data, random forest, cone index

CLC Number:

S153

Li Kunwei, You Xiong, Zhang Xin, Tang Fen. Soil Data Construction Method for Cross-country Trafficability Analysis[J]. Journal of System Simulation, 2019, 31(1): 158-165.

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