Impact Factors Analysis on Prefabricated Building Quality Based on Apriori Algorithm

Abstract:

Through data mining， quality impact factors were extracted from prefabricated building articles， then filtered into key factors and analyzed by the Apriori algorithm. Results indicate that big data help to reduce the interference on index selection caused by human factors， while a more universal law could be obtained by observing the correlation between impact factors and the quality of prefabricated buildings. Among all 5M1E factors， the “Method” branch gains greater support， indicating a significant impact on prefabricated buildings’ quality. Based on confidence analysis and the proposed strong association rules， it is found that “standardization of component manufacturers” receives not only a higher support degree but also the greatest frequency among the associated factors. Suggestions are put forward and shall be an effective reference for quality impact factors’ evaluation and management formulation.