Real Estate Investment Estimation Based on BP Neural Network

Investment estimation is an important link in the feasibility study stage of residential projects. In this paper, a genetic algorithm is used to improve the BP neural network to estimate the construction and installation cost of residential construction project investment. Taking the project data of a construction company as an example, a genetic BP neural network model is constructed. Through the detection of the actual data, the error is within 10%, which meets the actual investment estimation needs.