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QPAIS: A WEB-BASED EXPERT SYSTEM FOR ASSISTED IDENTIFICATION OF QUARANTINE STORED INSECT PESTS

机译:QPAIS:基于Web的检疫性昆虫害虫辅助鉴定专家系统

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Stored insect pests can seriously depredate stored products causing worldwide economic losses. Pests enter countries traveling with transported goods. Inspection and Quarantine activities are essential to prevent the invasion and spread of pests. Identification of quarantine stored insect pests is an important component of the China's Inspection and Quarantine procedure, and it is necessary not only to identify whether the species captured is an invasive species, but determine control procedures for stored insect pests. With the development of information technologies, many expert systems that aid in the identification of agricultural pests have been developed. Expert systems for the identification of quarantine stored insect pests are rare and are mainly developed for stand-alone PCs. This paper describes the development of a web-based expert system for identification of quarantine stored insect pests as part of the China 11th Five-Year National Scientific and Technological Support Project (115 Project). Based on user needs, textual knowledge and images were gathered from the literature and expert interviews. ASP.NET, C# and SQL language were used to program the system. Improvement of identification efficiency and flexibility was achieved using a new inference method called characteristic-select-based spatial distance method. The expert system can assist identifying 150 species of quarantine stored insect pests and provide detailed information for each species. The expert system has also been evaluated using two steps: system testing and identification testing. With a 85% rate of correct identification and high efficiency, the system evaluation shows that this expert system can be used in identification work of quarantine stored insect pests.
机译:储存的害虫会严重淘汰储存的产品,从而造成全球经济损失。害虫进入运输货物的国家。检验检疫活动对于防止有害生物的入侵和传播至关重要。隔离存储的病虫害的识别是中国检验检疫程序的重要组成部分,不仅要识别捕获的物种是否为入侵物种,还必须确定存储的虫害的控制程序。随着信息技术的发展,已经开发了许多有助于识别农业害虫的专家系统。鉴定隔离存储的害虫的专家系统很少,主要用于独立PC。本文描述了作为“十一五”国家科技支撑计划(115项目)一部分的基于网络的专家系统,用于鉴定隔离的病虫害。根据用户需求,从文献和专家访谈中收集文字​​知识和图像。使用ASP.NET,C#和SQL语言对系统进行编程。使用一种称为基于特征选择的空间距离方法的新推理方法,可以提高识别效率和灵活性。专家系统可以帮助识别150种检疫性储存的害虫,并提供每种物种的详细信息。还使用两个步骤对专家系统进行了评估:系统测试和标识测试。系统评估表明,该专家系统的正确识别率高达85%,效率很高,可用于隔离存储的病虫害的识别工作。

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