| With the emergence of new green buildings,the continuous innovation of building material production technology,the continuous increase in the structural requirements and complexity of buildings,and the rapid increase in construction costs,how to minimize real estate costs and maximize profits have become An extensive topic.Project cost forecasting and dynamic cost process control are particularly important.This article takes a real estate project as an example during the construction of an enterprise.The main research work is as follows:(1)Summarize the research theory and analysis methods of cost control issues,expound the principle and process of target cost control,and summarize the target cost control system and Control Method.The influencing factors of dynamic cost are analyzed,and the dynamic cost control system and characteristics are summarized,as well as the dynamic cost management method during project implementation.(2)The SIMCA data analysis software is used to predict and analyze the target cost of a real estate enterprise’s implementation project,comparative analysis and data mining of the target cost of each project,combined with the principal component analysis and partial least squares analysis method provided by the software,summary The important components and differences of each project’s target cost composition are presented,and a predictive analysis model is proposed.The research results show that the degree of fitting of the model obtained through Principal Component Analysis is 0.98,and the prediction accuracy of the model reaches 0.919.The optimized partial least squares regression target cost analysis model has a fitting degree of 0.996,and the model’s prediction accuracy reaches 0.972.The data results show that SIMCA analysis software can be applied to real estate target cost data analysis.The software can not only perform in-depth data mining but also realize cost data visual analysis.(3)Analyze and predict the dynamic cost in the process of project implementation through SIMCA software,study the three main factors(engineering duration,on-site visa,engineering changes)that affect the dynamic cost control,establish a linear regression analysis model,and Visual analysis of the data shows that the dynamic cost prediction model established by partial least squares(PLS)has a coefficient of fit of 0.962 and 0.937 for thedynamic cost analysis model of the basement and the residential cost analysis model,and The error of the prediction value obtained by substituting other sample data into the prediction model is only 0.006582346,and the prediction accuracy of the model is high.Studies have shown that this method can solve the multiple correlations between the respective variables and the dependent variables very well Multiplication is applied to the dynamic cost prediction of real estate projects. |
