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Research on the Method and Application of Construction Cost Prediction Based on Deep Learning

Year: 2025

Type: article

Abstract: The successful implementation also affects the economic benefits of the project and the decision-making of stakeholders. However, traditional prediction methods have not fully considered the temporal, nonlinear, and complex characteristics of construction project costs, resulting in a need for further improvement in accuracy. This article focuses on the characteristics of construction project cost and constructs a deep learning based construction project cost prediction model. This article aims to study the methods and applications of engineering cost prediction based on artificial intelligence. Aiming at the problems of traditional engineering cost prediction models, such as complexity, inaccuracy, and dependence on manual experience, an innovative approach based on artificial intelligence technology is proposed. Firstly, this article proposes using a large amount of historical data and deep learning algorithms to construct a prediction model, and designing an optimized feature extraction process. Secondly, this article adopts adaptive learning algorithms to continuously update the model to adapt to the increasingly changing needs of engineering.

Source: Academic journal of management and social sciences

DOI: 10.54097/1ejz4656

Author: Jiaying Zhou

Institution: Liaoning Communication University

Language: English

Topic: Construction Project Management and Performance

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: Liaoning University