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。 Combining the characteristics of randomness, fuzziness and incompleteness in the diagnosis of fish diseases, this paper integrates the fuzzy mathematical method into the extraction of symptoms based on the probabilistic model of conservation set theory, An algorithm to solve the problem is proposed to construct a fish disease diagnosis model which can effectively deal with the knowledge representation and inference of randomness, fuzziness and incompleteness. Through a large number of fish disease diagnosis examples prove that the model has some validity and practicality.