Construction Cost Index Prediction: A Visibility Graph Network Method

Construction Cost Index (CCI) is a weighted aggregation index published by Engineering News-Record (ENR), a world-famous academic journal in the field of engineering and construction. CCI provides a long recorded construction costs that reflect the overall cost level of construction and engineering development status. Therefore, many companies and cost estimators have done a lot of work for CCI prediction in order to better plan investment and prepare bids. In this paper, in order to improve the accuracy of CCI prediction, unlike previous forecasting methods based on causal model and statistical analysis, we propose a network method based on the visibility graph to better forecast CCI. The main idea is to map CCI data into networks, so that each CCI data can be seen as a node in the network, and then use node visibility and network structures to predict CCI. The proposed method is applied to predict the short-term, mid-term and long-term CCI separately, and compared with other popular prediction models based on common evaluation indicators. The experimental results show that this method has good prediction performance and can effectively improve the CCI prediction accuracy.