Work

Research on Investment Estimation of Prefabricated Buildings Based on Genetic Algorithm Optimization Neural Network

Year: 2025

Type: article

Abstract: At present, China’s prefabricated buildings have entered a period of comprehensive development. Starting from the investment decision-making stage of construction projects, this paper analyses the characteristics of prefabricated investment estimation and the relevant literature on the characteristics of prefabricated construction projects, uses the rough set attribute reduction algorithm to screen the key engineering characteristic factors, and establishes a BP neural network model optimized by genetic algorithm to estimate and analyze the investment of completed prefabricated construction projects. The results of the study show that the accuracy of the improved BP neural network prediction model is better than that of the standard BP neural network prediction model, and the results are more stable, which provides a more scientific and effective method for the investment estimation of prefabricated buildings projects.

Source: Applied Sciences

DOI: 10.3390/app15073474

Authors: Jin Gao, Wanhua Zhao

Institution: Wuhan Polytechnic University

Language: English

Topic: BIM and Construction Integration

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896