Intelligent Cost Estimation Method for Large-Scale Projects Based on PCA Optimized RBF Neural Networks

In this paper, we break down the large-scale project into small units so that we can extract the parameters that relates most to the total cost more easily. However, the amount of these parameters are huge, causing much trouble for RBF neural fitting, so we need to reduce the number of these parameters by using PCA. Then we put the newly generated parameters as the inputs of RBF neural networks. The results of the empirical analysis showed a sound verification that the proposed cost estimation method is worthy of expanding.