| International trade in agricultural products is developing towards openness,pluralism and multi-polarization,involving domestic and foreign agricultural production and circulation systems,as well as political and economic aspects.Its decision-making is very complicated and strategic,requiring decision makers to carry out creative thinking and judgment on the basis of a large amount of analysis information.However,the traditional decision support technology and system cannot effectively combine the data mining analysis ability with the cognitive ability of decision makers,and its decision support effect is not obvious.Maize,as an important import and export food crop in China,occupies an important position in the strategic management of national food security.Taking China's maize international trade as an example,this study introduces situation awareness technology to present decision-makers with a panoramic view of decision-making by constructing the "state" and "potential" of maize trade,and effectively supports decision-makers' creative thinking with visualization as the main means.This research is based on Python data processing technology to form a global maize trade database and construct a global maize trade situation visualization system supporting government decision-making and management.The main research contents are as follows:(1)Demand analysis of global maize trade situation visualization system.Through literature research,interviews with scholars in professional fields,etc.,the "state" and "trend" of maize international trade and the design of analysis indicators were clarified,and the functional requirements of system multi-theme display,system rapid response and human-computer interaction were also clarified.(2)The realization of global maize trade situation visualization system.According to the multi-topic display requirements,the system clearly defines the index of maize trade situation analysis,extracts data supporting multi-topic and multi-dimensional synchronous demonstration demand indicators to carry out parallel calculation,and converts the data into multi-topic views through front-end visualization technology to realize panoramic display of maize trade situation.In response to the demand for rapid data response,the system adopts Python data processing and analysis technology to effectively improve the response capability of the system and ensure the efficiency of maize trade situation analysis.To meet the needs of human-computer interaction,the system adopts PyEcharts and Tableau.js two visualization technologies,and combines the system's fast response ability to speed up data scaling,filtering and correlation.It supports multi-layer data drilling and improves users' insight into data based on good interactive experience.In addition,the system supports various visualization methods such as cartographic visualization,text visualization and relationship visualization,and supports synchronous presentation of multi-topic views.(3)System testing and evaluation.The SoapUI test tool is used to simulate the pressure test on the visual view,and the system has strong response capability.The global maize trade situation visualization system can effectively assist the government in decision-making management.The system realizes multi-topic synchronous demonstration of international trade decision-making scenarios,supports users to obtain more effective data and information in a limited screen space,and carries out comprehensive judgment on global maize trade situation.The system supports users to carry out real-time extraction and multi-layer drilling of multi-dimensional data.It can realize unified display of multi-theme views and different display of the same theme views according to the differences of visual perception habits and methods of different users.It is convenient for users to carry out data interpretation,analysis and insight according to personal preferences,and provides users with a convenient global maize trade situation analysis tool. |
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