Construction Cost Index Forecasting: A Multi-feature Fusion Approach

2021/08/18 by Zhan, Tianxiang, He, Yuanpeng, Xiao, Fuyuan
#FOS: Computer and information sciences #Machine Learning (cs.LG)

paper · doi:10.48550/arxiv.2108.10155

Abstract

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.

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