Estimation of stadium construction schedule based on big data analysis

There are many constraints on the progress of the construction of stadiums, which leads to the difficulty of schedule estimation. Aiming at this problem, a method of estimating the progress of stadium construction based on big data analysis is proposed. Firstly, the constrained parametric index analysis model of the progress analysis is constructed, and the Gaussian–Markov model of the progress constraint is established. The phase-space reconstruction of the constraint index information data of the construction progress is carried out. Then, an improved quantitative recursive feature extraction algorithm is used to realize the information entropy feature extraction of constraint feature information. Combined with big data information fusion and K-means clustering algorithm, the parameter cluster analysis of the stadiums construction progress parameters is achieved to improve the accuracy of prediction. On this basis, the corresponding manpower, scheduling, resource demand planning and construction preparation plan are compiled, to achieve the purpose of progress control, and effective arrange the progress of construction. Finally, the simulation results show that the prediction accuracy of the stadium construction is high, which is superior in convergence and efficiency, and has good engineering significance. © 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group.