Optimization Control of Construction Project Management Project Based on Deep Learning Algorithm

In view of the limitations of the traditional gray wolf algorithm in the optimal control of construction project management projects, an optimal control scheme for management projects based on deep learning algorithm was proposed. Firstly, the influencing factors is accurately located through the gradient ascent theory, and the indicators is reasonably divided to reduce interference, and the deep learning algorithm is used to construct the optimal control scheme of the management project. Experimental results show that under certain evaluation criteria, the proposed scheme is superior to the traditional gray wolf algorithm in terms of the optimal control accuracy of management projects and the processing time of influencing factors, and has obvious advantages. The optimal control of management projects plays an extremely important role in construction projects, which can accurately predict and optimize the growth characteristics and product generation of construction projects. However, the traditional gray wolf algorithm has certain limitations in solving the project optimization simulation problem, especially when dealing with complex problems. In this paper, this paper proposes an optimal control scheme for management projects based on deep learning algorithm to better solve this problem. In this scheme, the influencing factors is accurately located through the gradient ascent theory, so as to determine the division of indicators, and the deep learning algorithm is used to construct the scheme. Experimental results show that under certain evaluation criteria, the accuracy and speed of the scheme is significantly improved for different problems, and it has better performance. Therefore, the simulation scheme based on the deep learning algorithm can better solve the limitations of the traditional gray wolf algorithm and improve the simulation accuracy and efficiency in the optimal control of construction project management projects.