支持向量机在供水方案综合评价中的应用研究

The Application of support vector machine in water supply scheme

针对开始不能确定目标权重或隶属度的多方案综合评价的问题时,提出了一种支持向量机的学习算法实现多方案的综合评价。本文在电厂以中水作为水源的情况下,引入支持向量机算法,通过建立目标、综合属性的优化模型,再对建立的多种供水方案进行综合评价。计算结果表明,三种方案的综合评判值分别为:0.24、0.55和0.61,方案三为首选的供水方案,与实际首选方案和层次分析法确定的方案一样。将支持向量机算法应用于供水方案的选取,得到的综合效果评价是可行的。

As for comprehensive evaluation of alternative schemes which can not confirm its goal attribute weight or membership, a support vector machine learning algorithm is presented. Based on water supply scheme as reclaimed water source for the power plant, the learning algorithm sets up a model to synthesize attribute optimization utilizing the support vector machine. The result shows that the comprehensive evaluation value of three schemes were 0.24, 0.55 and 0.61, which shows that the third scheme is reasonable. Contrasted with actual choice scheme and AHP to determine scheme, the result is the same as them. The effect of comprehensive evaluation is feasible for the selection of water supply scheme by support vector machine method.