洁净室空气洁净度评价的模糊模式识别方法

洁净室空气洁净程度的高低属于模糊概念，将各评价样本实测指标矩阵转变为相对隶属度矩阵，同时将各标准模式指标标准值矩阵转变为指标准相对隶属度矩阵，以全体样本对于各标准模式间的加权广义距离平方和最小建立目标函数，经构造拉格朗日函数，建立了洁净室空气洁净度评价的模糊模式识别模型。斗净室洁净程度评价是一个多目标评价问题，提出了确定指标权重的主、客观结合法，即先建立求解各指标权重的迭代模型并求出指标权重的初始值，然后根据评价的经验，采用重要性语气算子调整各指标的相对隶属度，对初始值进行调整，归一化后得到合理的指标权重值，经计算实例验证，本建立的模式识别方法物理意义明确，评价结果符合实际。

STUDY ON FUZZY RECOGNITION MODEL OF PURIFICATION DEGREE OF AIR IN SPOTLESS ROOM

Based on the fact that the purification degree of air in spotless room is a fuzzy concept, the measure value matrix of all samples are transferred to a normalized matrix, and the standard value matrix of all standard models to a normalized cluster center matrix. By the objective function to minimize the sum of least squares of weighted general weighted distances between all samples and all cluster centers, a Lagrange function is constructed. The present paper gives a fuzzy pattern recognition model of the purification degree of air in spotless room. Because the fuzzy pattern recognition of the purification degree of air in spotless is a multi-objective question, the method combining subjective and objective is adopted. First, a lgorithm model that define the indexes weight of multi-objective is set up, and an initial weighting vector is obtained. Second, based on the experience of the evaluator, by the correspondence relation of mood operator and fuzzy scale, the new weighting vector is given. Third, by setting the sum of the element in the vector of indexes weight to equal to one, a rational vector of indexes weight is obtained. And finally, a case study is given. By the case study, it is found that the model is very rational and effective.