In the construction industry today,the concept of high-quality development is gradually deepening,assembly building is promoting the industrialisation of modern construction,green,intelligent integration of development,its development trend is increasingly significant,China has also issued a number of policies and relevant documents to promote the vigorous development of the assembly building industry.While the current development of assembled buildings has a good level of scale and realistic conditions,the procurement of prefabricated components is a constant part of assembled construction,.Therefore,a scientific and efficient method of selecting a precast component supplier that meets the actual conditions of the construction site is of vital importance to improving the quality of the assembled building.To solve such problems,it is necessary to use information technology to deal with complex and redundant information,and to carry out scientific and reasonable index screening among a rich variety of indicators,so as to realise the construction enterprises’ selection of prefabricated building component suppliers with different characteristics.This paper focuses on the following aspects of research: the selection of the recycling decision model for building precast suppliers,the construction of an intelligent recommendation model for building precast suppliers,simulation and so on.The main research contents are as follows:(1)The suppliers of prefabricated building components were considered as suppliers with certain recycling capacity,and the Hotelling linear city model was used to depict the respective recycling market shares of suppliers and informal recyclers,and a profit function was constructed based on the Bertrand price competition model.By comparing the changes in the respective recycling market shares,recycling prices and profits of suppliers and informal recyclers before and after the implementation of smart recycling decisions,it was found that the implementation of smart recycling decisions effectively improves the competitive advantages of suppliers and informal recyclers in the recycling market,promotes the positive sales of new precast products and the reverse recycling of old products,and realises the maximisation of resource value for suppliers of precast building components.Maximising the value of resources for the selection of precast suppliers.(2)By using literature analysis method and combining with the current national documents,a reasonable evaluation system of prefabricated building component suppliers is established.The TF-IDF algorithm is used to extract user dynamic comment feature words,complete feature mining of the original data,and complete feature matching between prefabricated component suppliers.Using Snow NLP to calculate feature sentiment values,the SPM supplier user portrait feature model is constructed,and the four types of supplier features in the model and the construction company’s concerns are visualised with the help of Word Cloud tools.The K-Means algorithm is optimised and improved to better match the recommendation model that follows.The K-Means+clustering algorithm was used to cluster the user profile model,and a collaborative filtering algorithm was incorporated on the basis of the clustering results to build a hybrid recommendation model based on the clustering results of the supplier user profile.(3)Combined with simulation,the intelligent recommendation model of precast building component suppliers is applied to the selection of precast building component suppliers in this paper.The experimental results show that the model can break through the drawbacks of traditional supplier selection methods and make a scientific and reasonable selection among a large number of precast building component suppliers.The recommendation algorithm can not only screen out suppliers matching with construction enterprises more accurately,but also promote the comprehensive use of construction resources,strengthening the upstream and downstream linkage of the supply chain,and ultimately realising the high-quality development of the construction industry. |