Project engineering management evaluation based on GABP neural network and artificial intelligence

BP neural network is the most representative computational and research method of current machine learning, BP neural network has gradually developed into the most widely used and now the most widely used in the industry with its powerful nonlinear feature function mapping computing capabilities, good data induction and feature recognition computing capabilities. This paper closely links the actual activities of project engineering technology management with modern machine learning network technology, and proposes a new type of engineering management activity model based on machine-integrated GABP neural network. Based on artificial intelligence technology, this paper discusses the theory of analytical neural learning in depth, discusses the theory of analytical neural learning in combination with genetic algorithms, and systematically discusses the models commonly used in this study based on theoretical foundations such as genetic algorithms. And points out the defects and defects of the neural network structure itself. Good generalization ability, in order to minimize the impact of subjective factors on the valuation results. Although there are many management software specializing in construction project engineering currently on the market, the service scope and demand range of these management software specializing in construction project engineering are relatively narrow. For example, construction project management software can only be used manage a construction project. In the actual operation process, it is also found that unreasonable time arrangements often occur in various links, such as personnel scheduling and material distribution of engineering projects. It will not only cause a large waste of material resources, but also affect the effect of labor. To this end, starting from the government’s desire to improve the efficiency of engineering management projects, this paper designs an engineering management system for general projects based on artificial intelligence technology and neural networks, and after a large number of practical analysis.