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

Construction Cost Index Forecasting: A Multi-feature Fusion Approach