(1. 东北大学 资源与土木工程学院， 沈阳 110006；
2. 沈阳大学， 沈阳 110044；
3. 国家经济贸易委员会 安全科学技术研究中心， 北京 100029)
摘 要: 针对矿山系统安全的随机性及模糊性， 将模糊熵引入系统安全性评价模型的建模之中，提出了基于模糊熵和权广义距离之和最小的模糊模式识别模型， 实现了系统安全等级隶属度向量的离散化， 给出了模糊熵和权广义距离之间平衡参数的两种确定方法。 实例表明，该模型优于基于权广义距离平方和最小的原则所建立的模糊模式识别模型； 平衡参数的两种确定方法对评价结果具有良好的一致性。 模糊熵可作为安全等级隶属度向量离散程度的评价指标。
关键字: 模糊熵； 安全评价； 隶属度
（1. College of Resource and Civil Engineering, Northeastern University, Shenyang 110006, P.R.China;
2. Shenyang University, Shenyang 110044, P.R.China;
3. Center for Accident Investigation and Analysis, State Economic and Trade Commission, Beijing 100029, P.R.China）
Abstract: In view of randomness and fuzziness of mine safety system, leading fuzzy entropy into establishing models of assessment models of systemrisk,a new type of fuzzy pattern recognized model was put forward based on entropy and least generalized distance square sum of weight, which can realize subordinated vector dispersed of system safety grades. Two methods of defined balanced parameters were given between entropy and broad sense distance sum of weight. Examples showed that these methods have advantages over fuzzy pattern recognized models based on principle of least generalized distance square sum of weight. Two methods of defined balance parameters have good unison for assessment result. Fuzzy entropy can be assessment standard of dispersed extent of subordinated vector of safety grades.
Key words: fuzzy entropy； safety assessment； subordinate degree
