基于支持向量机的生鲜农产品风险损失预估

生鲜农产品的损失预测对我国的农业生产和应急处理具有重要的意义,本论文在考虑自然灾害风险如:多旱、涝、风、雹、霜冻等农业气象灾害的条件下,构建了基于网格搜索的支持向量机（Support vector machine,SVM ）生鲜农产品损失预测模型。对多项指标进行预测。选取1999 年-2015 年的河南受灾数据作为研究样本,结果验证了基于网格搜索的支持向量机损失预测模型在生鲜农产品损失预估上的合理性和有效性。

Support vector machine risk loss estimate for fresh agricultural products

The loss prediction of fresh agricultural products is of great significance to China's agriculturalproduction and emergency treatment, and this study, taking into account the risks of natural disasters such asdrought, flood, wind, flood, frost and other agricultural meteorological disasters, has constructed a supportingestive search-based forecast ingress of fresh agricultural products, and has built a model for the loss offresh agricultural products based on grid search, with a total output and per unit area yield. The area of thedisaster and the disaster area and other indicators to predict. Taking fresh vegetables as an example inHenan Province, the disaster data from 1999-2015 were selected as a research sample, and the resultsverified the rationality and validity of the support vector machine loss prediction model based on grid searchin the estimation of fresh agricultural products.