文献类型： 会议论文

第一作者： Jie Zhang

作者： Jie Zhang ¹ ; Qing Zhao ¹ ; Xiaohong Li ² ; Hecang Zang ¹ ; Feng Hu ³ ; Guoqiang Li ¹ ; Guoqing Zheng ¹ ;

作者机构： 1.Key Laboratory of Huang-Huai-Hai Smart Agricultural Technology, Henan Academy of Agricultural Sciences, Institute of Agricultural Economics and Information, Zhengzhou, China|Henan Technology Innovation Strategic Alliance for Intelligence Agriculture Industry, Zhengzhou, China|Henan Engineering and Technology Research Center for Intelligent Agriculture, Zhengzhou, China

2.Key Laboratory of Huang-Huai-Hai Smart Agricultural Technology, Henan Academy of Agricultural Sciences, Institute of Agricultural Economics and Information, Zhengzhou, China

3.Key Laboratory of Huang-Huai-Hai Smart Agricultural Technology, Henan Academy of Agricultural Sciences, Institute of Agricultural Economics and Information, Zhengzhou, China|Henan Technology Innovation Strategic Alliance for Intelligence Agriculture Industry, Zhengzhou, China

关键词： Analytical models;Visualization;Technology management;Urban areas;Time series analysis;Crops;Weather forecasting

会议名称： International Conference on Computer Science and Management Technology

主办单位：

页码： 23-28

摘要： Given the problems existing in the application of agricultural resources data, such as scattered datum resources, low degree of sharing, poor pertinence of technical guidance, low efficiency, and so on, this study designed a crop Variety Recommendation and Production Decision System based on GIS technology, multi-source database, and knowledge model, and preliminarily realized the sharing and visual analysis of meteorological environment, soil fertility and other agricultural resources data. The system adopts the REST framework to discover the front and back separation framework. Deep data mining builds expert knowledge rules for crop production technology management based on factors such as historical meteorological data, soil data, and crop variety suitability. They rely on spatial statistical analysis, time series data analysis, multi-source data fusion, and related crop knowledge model technology. It realizes application services such as various recommendations, post-disaster emergency guidance, production management decision-making, etc. The system was popularized and applied in Yuanyang County, Xinxiang City, in July 2021. According to the flood disaster on July 20 and the Internet weather forecast for seven days after the disaster, the system provides growers with replanted crops and varieties. Technical services are provided to reduce post-disaster economic losses and guide agricultural water-saving, fertilizer-saving, and other production applications.

分类号： tp3-53