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基于覆盖粗糙Vague软专家集的动物疾病诊断算法

Animal Disease Diagnosis Algorithm Based on Covering Rough Vague Soft Expert Set
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摘要 针对现有Vague软集扩展模型的不足,文中将覆盖粗糙集、Vague软集和软专家集3种模型融合扩展,提出了新的处理不确定性问题的数学模型,即覆盖粗糙Vague软专家集,并研究了相关性质。在此基础上,文中给出了一个基于覆盖粗糙Vague软专家集的动物疾病辅助诊断算法。该算法计算了覆盖粗糙Vague软专家集的上下近似算子,通过隶属函数建立了患病程度和疾病水平的关系,并做出辅助诊断。非洲猪瘟疾病的诊断实验表明,文中所提出的ADADA_CRVSES算法是一种有效的针对动物疾病的辅助诊断算法,疾病诊断准确率达90%以上。 In view of the shortcomings of the existing Vague soft set extension model,three models including covering rough set,Vague soft set and soft expert set are merged and expanded,and a new mathematical model for dealing with uncertain problems is proposed in this study,namely covering rough Vague soft expert set,and related properties are studied.On this basis,this study presents an assisted diagnosis algorithm for animal diseases based on a rough set of Vague soft experts.The algorithm calculates the upper and lower approximation operators covering the rough Vague soft expert set,establishes the relationship between the disease degree and the disease level through the membership function,and makes an auxiliary diagnosis.The diagnostic results of African swine fever disease show that the ADADA_CRVSES algorithm proposed in the study is an effective auxiliary diagnosis algorithm for animal diseases,and the accuracy rate of disease diagnosis is more than 90%.
作者 陈鹏岗 冯晓毅 CHEN Penggang;FENG Xiaoyi(Information Network Department,The Second Affiliated Hospital of Xi′an Jiaotong University,Xi′an 710004,China;School of Electronics and Information,Northwestern Polytechnical University,Xi′an 710072,China)
出处 《电子科技》 2021年第6期1-10,共10页 Electronic Science and Technology
基金 国家自然科学基金青年项目(61902301)。
关键词 VAGUE集 软集 Vague软集 软专家集 覆盖粗糙Vague集 覆盖粗糙Vague软专家集 上下近似算子 疾病诊断算法 Vague set soft set Vague soft set soft expert set covering rough Vague set covering rough Vague soft expert set upper and lower approximation operator disease diagnosis algorithm
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