基于模糊数学的覆盖集模型在鱼病诊断中的应用  

A new method for fish-disease diagnostic problem solving based on parsimonious covering theory and fuzzy inference model

作　　者：温继文[1] 李道亮[2] 傅泽田[2] 

机构地区：[1]北京林业大学经济管理学院,北京100083 [2]中国农业大学教育部现代精细农业系统集成技术重点实验室,北京100083

出　　处：《农业网络信息》2005年第12期24-27,共4页Agriculture Network Information

基　　金：国家"863"高技术研究发展资助项目(2002AA243031)

摘　　要：本文结合鱼病诊断中随机性、模糊性和不完备性同时存在的特点,基于节约覆盖集理论的概率模型,将模糊数学方法集成到症状的提取中,并根据获取信息的序贯性给出求解算法,构造了一个能够有效处理随机性、模糊性和不完备性知识表示和推理的鱼病诊断模型。通过大量鱼病诊断实例证明该模型具有一定的有效性和实用性。There are three kinds of uncertainty in the process of fish-disease diagnosis, such as randomicity, fuzzy and imperfection, which affect the veracity of fish-disease diagnostic conclusion. So, it is important to construct a fish-disease diagnostic model that can effectively deal with these uncertainty knowledge＇s representation and reasoning. In this paper, the well-developed parsimonious covering theory based probability model capable of handling randomicity knowledge is extended. A fuzzy inference model capable of handling fuzzy knowledge is proposed, and the corresponding algorithms based the sequence of obtaining manifestations are provided to express imperfection knowledge. In the last, the model is proved to be effective and practicality through many fish-disease diagnosis cases.

关 键 词：模糊数学 节约覆盖集 鱼病诊断 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程] TP387[自动化与计算机技术—控制科学与工程]