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根据模糊等价关系，以15个矿43条回采巷道为样本，给出了不同置信度下的分类结果。
According to fuzzy equivalence relationship, taking 43 gateways in 15 mines as samples, classification result is given at the different confidence levels.
引入广义梯形模糊数描述风险等级，增加了评价者的置信度指标。
The paper introduces generalized trapezoidal fuzzy number to describe risk rate, which adds a degree of confidence of estimators opinion.
数值分析证明本文建立的模糊支撑向量机模型可根据数据置信度大小有效的控制各数据在学习机中的作用。
Numerical analysis testified that these fuzzy models can effectively control the influence of each sample on learning machine according to its confidence.
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