Abstract
In order to gain better experience and knowledge from historical disaster response and improve the ability of decision support in emergency management, a method of mining processing schemes based on belief rule-base is proposed based on forest fire history cases. Combined with the historical data of American forest fires in 2014 provided by the National Fire Incident Reporting System (NFIRS), the data extraction of fire status and coping strategies was realized, and the rules were mined by Apriori algorithm to form the forest fire processing rule-base. The reasoning model of belief rule-base for practical business is constructed to realize the optimal selection of fire processing scheme and to provide a supporting scheme for forest fire response decision.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (No. 71774021, No. 71373034, No. 71533001).
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Xu, Y., Wang, N., Wang, X., Ni, Z., Li, H., Chen, X. (2018). Research on Forest Fire Processing Scheme Generation Method Based on Belief Rule-Base. In: Chen, J., Yamada, Y., Ryoke, M., Tang, X. (eds) Knowledge and Systems Sciences. KSS 2018. Communications in Computer and Information Science, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-3149-7_10
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DOI: https://doi.org/10.1007/978-981-13-3149-7_10
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