A Cascaded Neural Network On Construction Labor Cost Forecasting

Construction industry is the traditional and pillar industry in China. With theinternational construction market opening up, a fresh blood has been injected into thedevelopment of the construction process and project management of China. Thenational construction industry output value and added value of an average annual willgrow more than15%during the "Twelve Five" period. However, with thelabor-intensive construction industry facing the increasing labor cost year by year, alarge area of labor shortage appearing, as well as the low desire of the new generation ofmigrant workers, the construction industry meet a great challenge. Hence, theestablishment of labor costs forecasting system is extremely urgent, and accurately predictlabor costs is a good basis for management and control labor costs.This study reviews the concept of labor cost structure, analysis of the currentdomestic and foreign construction labor costs there is a series of practical managementissues in order to study analyzed factors affecting the construction industry labor costs,labor costs to establish a more accurate prediction model, which proposes to optimizebuilding industry labor cost management recommendations. After a lot of literatureidentification, this study identified47impact indicators, with10structured interviewswith professionals, to streamline the38indicators of greater relevance, throughquestionnaires, on38impact indicators evaluation scoring, receipts and aggregate thedata, the use of mathematical statistical methods for data analysis, reveal impact ofrising labor costs, China’s construction industry factors include five categories:macroeconomic market, industry development, construction companies maturity,construction costs, and on-site construction. Conclusions based on factor analysis, theestablishment of labor cost forecasting model, and Chongqing as an example, anempirical test for predictive models.Through these studies, one can improve the management of constructionenterprises on a comprehensive understanding of labor costs, improve constructionlabor costs forecast accuracy. On the other hand, can promote the profits of constructionmanagement and economic efficiency of enterprises, the construction industry as well asfor the entire country’s comprehensive development of basic research basis.