  The construction cost index is an important indicator of the construction
industry. Predicting CCI has important practical significance. This paper
combines information fusion with machine learning, and proposes a multi-feature
fusion (MFF) module for time series forecasting. The main contribution of MFF
is to improve the prediction accuracy of CCI, and propose a feature fusion
framework for time series. Compared with the convolution module, the MFF module
is a module that extracts certain features. Experiments have proved that the
combination of MFF module and multi-layer perceptron has a relatively good
prediction effect. The MFF neural network model has high prediction accuracy
and prediction efficiency, which is a study of continuous attention.
