农产品价格异常波动的市场价格传递与时空分布特征研究

项目名称： 农产品价格异常波动的市场价格传递与时空分布特征研究

项目编号： No.41501418

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 天文学、地球科学

项目作者： 彭程

作者单位： 北京市农林科学院

项目金额： 20万元

中文摘要： 农产品价格的异常波动对农民收入、农业生产和国家粮食安全造成不利影响，如何从海量的农产品价格数据挖掘出有用信息是迫切需要解决的科学问题。本研究以近期价格波动幅度大频率高的农产品为例，运用时空数据挖掘、空间统计学、复杂网络、可视化等理论方法，定量分析农产品价格异常波动期间的时空关联性、聚集性和价格传递特征。主要内容包括：①研究不同时空尺度下农产品价格的空间自相关性、局部聚集特征，建立影响因素-农产品价格的时空自相关模型，归纳农产品价格与影响因素的时空耦合规律；②研究农产品价格时空点格局识别方法，分析价格的聚集特征和演变规律。建立基于复杂网络的农产品价格传递模型，挖掘价格在市场之间的时空传递特征；③建立农产品价格数据时空立方体模型，研究农产品价格时空分布三维可视化方法，实现数据的可视化表达。本项目一方面丰富和拓展时空数据挖掘的理论方法和应用领域，另一方面为农产品市场行情信息服务提供新的技术手段。

中文关键词： 农产品价格；价格传递；空间统计学；时空相关；点数据

英文摘要： The recent decade has witnessed a drastic fluctuation of agricultural product price. The frequent change of price has made significant impacts on the wellbeing of farmers, the sustainability of agriculture, and the food security of the entire nation. In response to these contingencies, mining mass increasing agricultural product price data is critical to monitoring the wellbeing of market and predicting imminent issues that might develop into large-scale food crisis. From the perspective of geography, the abnormality of agricultural product price and its influences on the market can be analyzed and presented by quantitative geographical methods, such as spatial-temporal autocorrelation, complex networks and 3D visualization. The main contents include： First, the project employs the technique of spatial autocorrelation to identify the pattern of agricultural product price at different geographical and temporal scales. A bivariate spatio-temporal autocorrelation model is established to account for both the market variables and price to study the spatial-temporal coupling rule. Second, the project identifies the spatial aggregation distribution and evolution rule of agricultural product price by implementing the spatio-temporal point pattern recognition method. Then the transmission model based on complex networks is established to summarize the transmission-diffusion characteristics among markets. Third, a 3D space-time model using kernel density function is built for improving the visualization of agricultural product price and highlighting the spatial locations and time periods in which the wholesale market of agricultural products may have involved abnormal events. This project applies cutting-edge spatio-temporal analyses to the case of abnormal fluctuation of agricultural product price in China. It provides a fruitful application of crowd sourcing big data while providing insight into practical challenges of abnormal fluctuation issues that China has experienced in recent years.

英文关键词： agricultural product price;price transmission;spatial statistics;spatio-temporal correlation;point data