关键词: 森林火灾, 贝叶斯网络, 参数学习, 联合树算法, 概率推理

Abstract: Forest fire prediction involves many influence factors, complex occurrence mechanism, and unstructured input data. To address these issues, a practical forest fire prediction system based on Bayesian Network（BN） is designed and implemented. The system inputs meteorological, geographical, vegetation and human activities data, builds BN model with historical forest fires records, performs probabilistic inference via the junction tree algorithm, and outputs the probability of forest fire occurrence. Experimental results on real records of forest fires in Yunnan province and comparison with the Canadian Forest Fire Weather Index System（FWI） demonstrate that the system is feasible and practical.

Key words: forest fire, Bayesian Network（BN）, parameter learning, junction tree algorithm, probabilistic inference