农业云服务可适性技术研究进展
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  • 英文篇名:Advances in adaptable technologies of agricultural cloud services
  • 作者:陈天恩 ; 刘军萍 ; 王登位 ; 史晓慧
  • 英文作者:Chen Tian'en;Liu Junping;Wang Dengwei;Shi Xiaohui;National Engineering Research Center for Information Technology in Agriculture Beijing;Information Center of Beijing Municipal Commission of Rural Affairs;
  • 关键词:农业云服务 ; 可适性 ; 农业时空数据 ; 一体化存储 ; 农业知识发现 ; 知识服务选择与优化组合 ; 按需服务
  • 英文关键词:adaptive agriculture cloud service;;integrated storage of agriculture spatial-temporal data;;agriculture knowledge discovery;;knowledge services selection and optimum combination;;on-demand services
  • 中文刊名:NXTS
  • 英文刊名:China Agricultural Informatics
  • 机构:北京农业信息技术研究中心/农业部农业信息技术重点实验室;北京市农村工作委员会信息中心;
  • 出版日期:2018-02-25
  • 出版单位:中国农业信息
  • 年:2018
  • 期:v.30
  • 基金:北京市自然科学基金重点项目“农业云服务可适性关键技术及应用模型研究”(4151001);; 北京市科技计划课题“服务乡村振兴的都市农业双创平台建设与成果示范应用”(Z181100002418002)
  • 语种:中文;
  • 页:NXTS201801010
  • 页数:12
  • CN:01
  • ISSN:11-4922/S
  • 分类号:71-82
摘要
【目的】作为农业信息化应用新的交付模式,农业云服务在降低农业信息化技术及成本门槛、响应个性化服务需求等方面具有明显优势。但农业行业应用的特殊性、用户需求地区差异性和动态变化性等特征,也对通用云计算应用模型的适用性构成挑战,研究突破可适性技术瓶颈,是云计算在农业领域深入应用所面临的首要问题。【方法】文章围绕农业云服务涉及的数据管理、知识发现和服务提供等关键环节,系统阐述了农业云服务可适性技术在农业数据存储方法与模型、农业数据挖掘与知识发现、农业知识服务组合、农业应用按需服务这4个方面的研究进展情况,并提出了一种可适性农业云服务参考模型。【结果 /结论】揭示了云服务可适性技术的研究潜力,为开展云计算行业应用和大规模农业云服务应用研究提供参考。
        [Purpose]As a new delivery mode of agricultural information technology applications,agricultural cloud service has obvious advantages in reducing technical and cost threshold,and better responding to personalized service requirements. But the particularity of agricultural applications,regional differences and dynamics based service requirements challenges the applicability of general cloud computing technologies. It is the most important factor of agricultural cloud service application to breakthrough adaptable technologies. [Method] In current paper,around key links of agricultural cloud service,such as data management,knowledge discovery and service,the advance of adaptable technologies in agriculture cloud service,which includes agriculture data storage method and model,agriculture data mining and knowledge discovery,agriculture knowledge service composition,on-demand services of agriculture application,were systematically summarized and presented,and a reference model of adaptive agriculture cloud service was put forward. [Result/conclusion] However,there are still some problems deserve more attentions in future,the research of adaptive agriculture cloud service revealed its great potential,methods presented in this paper can provide reference for the development of large-scale agricultural and other industry applications based on cloud services.
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