基于大数据处理的农业气象灾害分类模型

摘要

For the problems of the data classification with low efficiency caused by the large amount of meteoro-logical data and the highly complex of heterogeneous data,a K-nearest neighbor combined classifier and a distributed parallel processing method were adopted to obtain the agro-meteorological disaster classification model.Firstly,according to the grade index of meteorological disaster,an exponential formula of the agro-meteorological disaster was proposed.And then,a parallel K-nearest neighbor combined classifier was used to complete the statistical classification of agro-meteorological disaster index.Finally,the ranking information of meteorological disaster which has been classified was analyzed to assess the disaster risk of crops.The evaluated meteorological disaster information can guide the agricultural production for farmers reasonably and reduce property loss.The experiment simulation shows that,faced with various and huge agro-meteorological data,the parallel K-nearest neighbor combined classifier is faster and more precise.%针对气象数据量大、异构数据复杂度高而导致数据分类效率低下的问题,采用K最近邻组合分类器和分布式并行处理方法,得出农业气象灾害分类模型.首先依据气象灾害等级指标,提出农业气象灾害风险指数公式,再由并行化的K最近邻组合分类器,完成农业气象灾害风险指数的统计分类,最后对已经分类的气象灾害等级信息进行分析,实现农作物的灾害风险评估.农户能够根据评估的气象灾害信息合理的进行农业生产,减少财产损失.仿真表明,面对种类繁多、数据量巨大的农业气象数据,并行化的K最近邻组合分类器处理速度更快,准确度更高.