基于机器学习的建材消耗预测研究

Research on Building Materials Consumption Prediction Based on Machine Learning

摘要: 建筑业作为国民经济支柱性产业，在推动社会发展的同时也消耗了大量建材。我国在推动建筑行业高质量发展，同时进行节约材料和节能减排的行动，这对实现我国“双碳”目标具有重要意义，也节约大量经济成本和资源。优化建筑建材消耗的一个重要手段是建筑建材精细化管理，而进行这一工作的基础就是对建筑建材进行准确的预测，从而支撑建筑运行优化管理，实现节约建材的目标。本项目利用机器学习方法分析和研究建筑建材历史数据和影响因素，构建建筑建材消耗预测体系，以便预测建筑在设计、建造和使用阶段的建材需求。本项目旨在为建筑业的智能建造和可持续发展提供理论依据和实践指导。

Abstract: As a pillar industry of the national economy, the construction industry consumes a lot of building materials while promoting social development. China is promoting the high-quality development of the construction industry while saving materials and energy saving and emission reduction actions, which is of great significance to achieve China’s “double carbon” goal, but also save a lot of economic costs and resources. An important means to optimize the consumption of building materials is the fine management of building materials, and the basis of this work is to accurately forecast building materials, to support the optimal management of building operations, and to achieve the goal of saving building materials. This project uses a machine learning method to analyze and study the historical data and influencing factors of building materials and builds a building materials consumption prediction system to predict the building materials demand in the design, construction and use stages of buildings. This project aims to provide a theoretical basis and practical guidance for intelligent construction and sustainable development in the construction industry.