基于果蝇算法优化小波神经网络的输电工程造价预测

Transmission Project Cost Prediction Based on Wavelet Neural Network Optimized by Fruit Fly Algorithm

为了准确控制输电工程造价水平,提出一种基于果蝇算法优化小波神经网络的混合预测模型。首先,对输电工程造价影响因素进行归一化处理,并将归一化结果作为输入变量;其次,利用果蝇算法对小波神经网络参数进行优化,在此基础上,利用优化后的小波神经网络模型预测输电工程造价;最后,将本文的预测结果和其他方法进行对比。算例结果表明,该混合模型的预测效果更理性,精度更高。

bIn order to accurately control the transmission project cost,a hybrid prediction model based on the wavelet neural network optimized by the fruit fly algorithm is proposed.Firstly,the influencing factors of transmission project cost are normalized,and the normalized result is taken as input variable.Secondly,the parameters of wavelet neural network are optimized by using the fruit fly algorithm.On this basis,the optimized wavelet neural network model is used to predict the construction cost of transmission project.Finally,the forecast result of this article is compared with other methods.The results of the example show that the hybrid model is more rational and more accurate.