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基于SOA的农作物病虫害监测预警系统设计
  • ISSN号:1673-9639
  • 期刊名称:《铜仁学院学报》
  • 时间:0
  • 分类:TP302.1[自动化与计算机技术—计算机系统结构;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]安徽农业大学信息与计算机学院,安徽合肥230036
  • 相关基金:国家自然科学基金资助项目(31371533);安徽省自然科学基金资助项目(1308085MF89);安徽省“十二五”科技攻关资助项目(12010302079,1301032169)
中文摘要:

农作物病虫害监测预警是农业防灾减灾、确保主要农产品有效供给的重要组成部分和关键环节.中国病虫害监测预警工作的准确性和时效性因“信息孤岛”而受制约.提出了“基于AHP的CBR的预警决策”模型,采用Web Service技术,设计了基于SOA架构的安徽农作物病虫害监测预警系统.该系统实现了安徽省农作物病虫数据的采集标化、传输网络化、分析规范化、处理图形化、发布可视化、汇报制度化、管理自动化、决策智能化.该预警系统实现了安徽省6年实践运行结果表明,安徽省各级植保站的工作效率及预警决策准确度和时效性均有显著提高.

英文摘要:

Crop pests and diseases monitoring and forecasting is an important part of the key to agricultural disaster prevention and mitigation,and to ensure that effective supply of major agricultural products. At present ,it is widespread phenomenon that the accuracy and timeliness of work pest monitoring and early warning is greatly restricted because of "Information isolated island". "AHP-based CBR Warning Decision" model was proposed, which using Web Service technology, designed and developed a monitoring and warning system based on SOA structure in Anhui Crop pests and diseases,and put it into application. This early warning system has achieved collecting standardized, transmission networking, analysis standardized, graphical processing, publishing visualization, reporting institutionalized, management auto- mation,intelligent decision-making of Anhui crop pest data work. The practical result of six years showed significant efficiency at all levels of Anhui plant protection stations, in terms of accuracy and timeliness of decision-making in early warning.

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期刊信息
  • 《铜仁学院学报》
  • 主管单位:贵州省教育厅
  • 主办单位:铜仁学院
  • 主编:王大忠
  • 地址:贵州省铜仁市碧江区清水大道103号铜仁学院学报编辑部
  • 邮编:554300
  • 邮箱:xbtu07@vip.163.com
  • 电话:0856-5223394
  • 国际标准刊号:ISSN:1673-9639
  • 国内统一刊号:ISSN:52-1146/G4
  • 邮发代号:
  • 获奖情况:
  • 国内外数据库收录:
  • 被引量:1596