First, this paper provides the way of constructing the relative degree of membership matrix of targeting index.
首先文中给出对象指标相对隶属度矩阵和标准指标值相对隶属度矩阵的建立方法；
Indexes and weights are firstly fuzzified, then relative membership degree to objectives is obtained by fuzzy operation, and the place of power stations is defined in whole valley.
首先对指标进行模糊化，通过模糊多目标运算得到各目标的相对隶属度，进而确定各个水电站在流域梯级开发中的位置。
Fuzziness, fuzzy concept and theory of relative membership degree are detailed based on the perspective of dialectical materialism on difference and common dimension, medium transition and two poles.
根据辩证唯物论关于差异与共维、中介和两极的观点，详细论述了模糊性、模糊概念、相对隶属度、相对隶属度函数等相对隶属度理论。
Schemes are optimized by using a fuzzy pattern-recognition crossover iteration method, which gives the objective weight and the relative membership degree of alternative at the same time.
根据多个可行方案，用同时确定目标的权重和方案隶属度模糊模式识别交叉迭代模型进行优选。
Then this paper develops a computing formula for relative membership degree of quantitative objectives that has the same standards as relative membership degree of qualitative objectives.
文中提出定性目标相对优属度矩阵的确定理论与方法。继而提出与定性目标相对优属度计算具有统一标准的定量目标相对优属度计算公式。
Finally, the optimal access network was chosen through the weighted ranking of the relative membership degree.
最后，通过对相对隶属度的加权排序，得到最优接入网络。
Finally, the optimal access network was chosen through the weighted ranking of the relative membership degree.
最后，通过对相对隶属度的加权排序，得到最优接入网络。
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