数据与计算发展前沿 ›› 2021, Vol. 3 ›› Issue (6): 1-14.

doi: 10.11871/jfdc.issn.2096-742X.2021.06.001

• 专刊:科学大数据挖掘与知识发现 •    下一篇

多维数据驱动的粮食安全分析与智能决策系统研究与实践

陈文杰1(),胡正银1,2,*(),胡靖3,庞弘燊4(),何雨娟5()   

  1. 1. 中国科学院成都文献情报中心,四川 成都 610041
    2. 中国科学院大学,经济与管理学院,图书情报与档案管理系,北京 100190
    3. 华南师范大学,经济与管理学院,广东 广州 510631
    4. 深圳大学,图书馆,广东 深圳 518060
    5. 四川大学,公共管理学院,四川 成都 610065
  • 收稿日期:2021-10-22 出版日期:2021-12-20 发布日期:2022-01-26
  • 通讯作者: 胡正银
  • 作者简介:陈文杰,中国科学院成都文献情报中心,馆员,长期从事科技领域知识挖掘、知识发现研究与知识服务平台建设,主要研究方向为机器学习、表示学习和知识图谱。
    负责论文初稿撰写与KEDS开发。
    CHEN Wenjie is a librarian of Chengdu Library and Infor-mation Center, Chinese Academy of Sciences. He has long been engaged in the research of knowledge mining, knowledge discovery and the construction of knowledge service system. His research interests include machine learning, representation learning, and knowledge graph.
    In this paper, he is responsible for the paper drafting and KEDS development.
    E-mail: chenwj@clas.ac.cn|胡正银,中国科学院成都文献情报中心,知识系统部主任,中国科学院大学情报学硕士研究生导师,中国科学院西部之光人才培养计划人选,博士,研究馆员,合作出版专著（编著）3部、发表论文80余篇、申请计算机软件著作权8项,主要研究领域为科技大数据分析方法与技术、科技情报知识挖掘与知识发现。
    负责制定论文框架,撰写“1.4现有研究小结”与“2.1体系架构”,论文修改、审定,设计多维数据驱动的粮食安全分析与智能决策系统技术方案。
    HU Zhengyin, Ph.D., is an associated professor of Chengdu Library and Information Center, Chinese Academy of Sciences, master supervisor of University of Chinese Academy of Science, and a selected candidate of West Light Talent Program of the Chinese Academy of Sciences. He has published three monographs and more than 80 papers and has applied 8 computer software copyright cooperatively. His research interests include S&T big data analysis, S&T intelligence mining, and know-ledge discovery.
    In this paper, he is responsible for drawing up the paper frame-work, writing “1.4 Summary of existing research” and “2.1 Architecture”, and paper revision and approval; design the technology program of the multidimensional data driven food security analysis and intelligent decision system.
    E-mail:huzy@clas.ac.cn|胡靖,华南师范大学经济与管理学院,教授,博士,“三农”与城镇化研究所所长,出版学术专著4部,发表论文、评论100多篇,领导研建“广东粮食安全数据分析与实验系统”,主要研究领域为土地制度、集体经济和粮食安全。
    负责撰写“4结论与展望”,KEDS总策划。
    HU Jing, Ph.D., is a professor of School of Economics and Management, director of the Institute of Agriculture, Rural areas and Urbanization, South China Normal University. He has published four monographs and more than 100 papers and reviews and led the research and development of “Guangdong Province Food Security Data Analysis and Experimental Sys-tem”. His research interests include land system, collective economy, and food security.
    In this paper, he is responsible for writing “4 Conclusion and Prospect” and KEDS general director.
    E-mail:huj26@163.com;|庞弘燊,深圳大学图书馆/深圳大学国家知识产权信息服务中心,副研究馆员,博士,被评为全国专利信息师资人才,中国科学技术情报学会“青年情报科学家”,主持国家级基金多项,发表图书情报类论文数十篇,主要研究领域为情报计量学、知识产权信息分析等。
    参与撰写“2多维数据驱动的粮食安全分析与智能决策系统研究”,负责KEDS原型系统开发。
    PANG Hongshen, Ph.D., is an associated professor of Library and National Intellectual Property Information Service, Shen-zhen University. He was rated as a national patent information teacher and a “Young Information Scientist” of China Science and technology information society, and published more than 10 papers cooperatively. His research interests include Information metrics and Intellectual property information analysis.
    In this paper, he is responsible for writing “2 Research on multidimensional data-driven food security analysis and intel-ligent decision system” and KEDS prototype system deve-lopment. E-mail: phs@szu.edu.cn|何雨娟,四川大学公共管理学院信息管理与信息系统专业,本科生,研究兴趣为信息系统、大数据分析等。
    参与撰写“1数据驱动的粮食安全分析研究”部分与论文修改。
    HE Yujuan is an undergraduate of School of Public Administration, Sichuan University. Her research intersts include information system and big data analysis.
    In this paper, she is responsible for writing “1 Research on data driven food security analysis” and paper revision. E-mail: heyujuan@stu.scu.edu.cn
  • 基金资助:
    国家社会科学基金重点项目“面向领域知识发现的学科信息学理论与应用研究”(17ATQ008)

Study on Multidimensional Data Driven Food Security Analysis and Intelligent Decision System

CHEN Wenjie1(),HU Zhengyin1,2,*(),HU Jing3,PANG Hongshen4(),HE Yujuan5()   

  1. 1. Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China
    2. Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    3. School of Economics and Management, South China Normal University, Guangzhou, Guangdong 510631, China
    4. Library, Shenzhen University, Shenzhen, Guangdong 518060, China
    5. School of Public Administration, Sichuan University, Chengdu, Sichuan 610065, China
  • Received:2021-10-22 Online:2021-12-20 Published:2022-01-26
  • Contact: HU Zhengyin

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摘要：

【目的】在大数据时代,粮食安全领域产生了海量多维数据,对这些数据进行关联分析、多维透视和知识挖掘,可以有效地支撑粮食安全分析与智能决策。【方法】基于粮食安全领域需求,系统地描述了粮食安全分析与智能决策系统的体系架构、数据基础、指标体系和预警模型。以“昆阅粮食安全大数据分析与智能决策系统”为例,展示了粮食安全结构分析、因素分析、平衡分析、图谱预警与智能决策等应用服务。【结果】该系统可为区域粮食安全评估、粮食安全预警等决策分析提供快速、精准、多角度、个性化的知识服务。【结论】多维数据驱动的粮食安全分析与智能决策系统具有巨大潜力,能够分析全国各地区每年粮食安全的状态,但还需集成人工智能领域中的新模型和新方法,以提升粮食安全分析与智能决策的效能。

关键词: 多维数据, 粮食安全, 智能决策, 大数据分析

Abstract:

[Objective] In the era of big data, the field of food security has produced massive multidimensional data. These data are used for association analysis, multidimensional perspective, and knowledge mining, and can effectively support food security analysis and intelligent decision-making.[Methods] This paper systematically describes the system architecture, data schema, index system, and early warning model of food security analysis. Taking “Kunyue food security big data analysis system (KEDS)” as an example, this paper shows the services of food security structure analysis, factor analysis, balance analysis, security early warning and intelligent decision-making, etc. [Results] KEDS can provide fast, accurate, multi angle and personalized knowledge services for regional food security assessment, food security early warning and other decision-making analysis. [Conclusions] Multidimensional data driven food security analysis and intelligent decision-making system has great potential to analyze the state of food security in various regions every year, but it also needs to integrate new artificial intelligence models and methods to improve the efficiency and performance.

Key words: multidimensional data, food security, intelligent decision, big data analysis