摘要
Over the past 10 years,lightning disaster has caused a large number of casualties and considerable economic loss worldwide.Lightning poses a huge threat to various industries.In an attempt to reduce the risk of lightning-caused disaster,many scholars have carried out in-depth research on lightning.However,these studies focus primarily on the lightning itself and other meteorological elements are ignored.In addition,the methods for assessing the risk of lightning disaster fail to give detailed attention to regional features(lightning disaster risk).This paper proposes a grid-based risk assessment method based on data from multiple sources.First,this paper considers the impact of lightning,the population density,the economy,and geographical environment data on the occurrence of lightning disasters;Second,this paper solves the problem of imbalanced lightning disaster data in geographic grid samples based on the K-means clustering algorithm;Third,the method calculates the feature of lightning disaster in each small field with the help of neural network structure,and the calculation results are then visually reflected in a zoning map by the Jenks natural breaks algorithm.The experimental results show that our method can solve the problem of imbalanced lightning disaster data,and offer 81%accuracy in lightning disaster risk assessment.
基金
the National Key R&D Program of China under grant number 2018YFB1003205
by the National Natural Science Foundation of China under grant number U1836208,U1536206,U1836110,61602253 and 61672294
by the Startup Foundation for Introducing Talent of NUIST(1441102001002)
by the Jiangsu Basic Research Programs-Natural Science Foundation under grant number BK20181407
by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund
by the Postgraduate Research and Innovation Plan Project in Jiangsu Province under grant number KYCX20_0934 and by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China.
