模糊综合评价取大取小算法的改进

为了克服模糊综合评价取大取小算法的一些弊端,提高其通用性，提出了一种模糊综合评价取大取小算法的改进方法。通过提高评价指标权重向量的总和来使综合评价关系矩阵中的更多数据被得以使用,从而提高综合评价的信度和适用范围。以比较运算的接近原则为标准,给出了确定指标权重总和的非线性规划数学模型,通过实例验证了该模型在海明距离、欧氏距离与车比雪夫距离3种度量标准下的有效性和正确性。给出了确定指标权重总和的更为一般的多个数学模型，以供进一步深入研究。

Improved max min algorithm of fuzzy synthetic

To overcome the disadvantages of max min algorithm of fuzzy synthetic evaluation and to enhance its quality. An improved maxmin algorithm of fuzzy synthetic evaluation was propsoed. By adjusting the total sum of the weights of index, the more data of the relation matrix were used than the oringal max min algorithm widely used before, the reliability rised,and the application scope enlarged. The mathmetical model of determination of the total amount of the weight was presented. The examples show the validity of the model at the rule of hamming distance, Euclidean distance and Cbcbyshev dsitance of the evaluation results of the improved and original max min algorithm. The six general models with the problem were given in the end, which mainly considered the originality or varidation of the date of the evaluation results, or the distances such as hamming, Euclidean and Cbcbyshev of the evaluation results of the weight average algorithm to the given algorithm.