Research on cost prediction and optimization model of construction engineering based on machine learning
基于机器学习的建筑工程成本预测与优化模型研究

摘要

建筑工程成本管理是确保项目顺利进行和实现预期收益的关键。随着建筑工程项目的复杂化和规模化，传统的成本估算方法面临诸多挑战。基于机器学习的建筑工程成本预测与优化模型通过数据驱动的方法，可以在项目初期准确预测项目成本，并通过优化算法实现资源配置的最优解决方案。本研究通过构建机器学习模型，探讨了建筑工程成本的影响因素，并运用优化方法提高成本管理的精确性和效率。机器学习模型在建筑工程成本预测中的应用，能够有效提高预测的准确度，降低项目成本风险，并为决策提供科学依据。

Abstract

Cost management in construction engineering is the key to ensuring the smooth progress of a project and achieving expected benefits. With the complexity and large scale of construction engineering projects, traditional cost estimation methods face numerous challenges. The cost prediction and optimization model of construction engineering based on machine learning, through a data-driven approach, can accurately predict project costs in the early stage of a project and achieve the optimal solution for resource allocation through optimization algorithms. In this study, by constructing a machine learning model, the influencing factors of construction engineering costs are explored, and optimization methods are applied to improve the accuracy and efficiency of cost management. The application of machine learning models in the cost prediction of construction engineering can effectively improve the accuracy of prediction, reduce project cost risks, and provide a scientific basis for decision-making.