基于BP神经网络的建筑能耗预测研究

Research on Building Energy Consumption Prediction Based on BP Neural Network

建筑能耗是建筑物运营管理的重点,会直接影响建筑物的使用成本。利用BP神经网络预测原理,可以对建筑的能耗状况进行预测分析,分析建筑能耗情况,实现能量的均衡分布,从而为建筑节能设计和绿色建筑发展提供支撑。因此,本文针对耗电量、燃气消耗和建筑面积等因素,进行建筑能耗预测,旨在根据预测结果合理分配能源,提高能源利用率。

Building energy consumption is a key focus of building operation and management,which directly affects the cost of building use.By utilizing the principle of BP neural network prediction,the energy consumption of buildings can be predicted and analyzed,achieving a balanced distribution of energy and providing support for energy-saving design and green building development.Therefore,this article focuses on factors such as electricity consumption,gas consumption,and building area to predict building energy consumption,aiming to allocate energy reasonably based on the predicted results and improve energy utilization efficiency.