文献类型： 外文期刊

作者： Wang, Xiping ¹ ; Tan, Wenxue ² ;

作者机构： 1.Hunan Univ Arts & Sci, Sch Econ & Management, Changde 415000, Peoples R China

2.Beijing Acad Agr & Forestry Sci, NERCITA, Software Engn Dept, Beijing 100097, Peoples R China

关键词： Intelligent Information Processing;Ailment Diagnosing;KNN;Similarity Degree;Uncertainty Factors

期刊名称：2013 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND APPLICATIONS (CSA)

ISSN：

年卷期： 2013 年

页码：

收录情况： SCI

摘要： Intelligent Information Processing System has successful application in informationization of traditional industry. Exact addressing the stock case's ailment type and roots as quickly as possible has been the weight of developing information technology for veterinary. In order to assist human veterinarian expert diagnose animal ailment, this work proposes a machine diagnosing model based on KNN ailment-similarity-degree pattern recognition. The project crew devises 3 similarity distance measuring methods including Lee distance and Jaro distance, which are addressed to the uncertainty factor vector pattern and fuzzy membership pattern. In addition, the software architecture of the machine diagnosing model and diagnosing algorithm is constructed in detail. Field experimental statistics demonstrate that compared with the individual human veterinary expert, the proposed model achieve a preferable accuracy rate of diagnosis over 80%, and low a rate of misdiagnosis obviously, which is an alternate of existent ones with great potential.