针对大型公共建筑高能耗问题,将影响能耗的因素进行定量与定性分析,提出了遗传算法和神经网络相结合的大型公共建筑能耗预测模型。采用GA算法优化BP神经网络的权值和阈值的方法对大型公建能耗预测模型进行分析,并结合实例验证了该模型的有效性。结果表明:较传统的BP神经网络,该模型能更准确地预测大型公共建筑能耗,并且为其确保用能定额和节能工作的开展提供了科学依据。 In view of the problem of high energy consumption of large public buildings, the factors influencing energy consumption are quantitatively and qualitatively analyzed, and the prediction model of large-scale public buildings’ energy consumption based on genetic algorithm and neural network is proposed. GA method is used to optimize the weights and thresholds of BP neural network to analyze the prediction model of large-scale public buildings energy consumption, and the effectiveness of the model is verified by an example. The results show that, compared with the traditional BP neural network, this model can predict the energy consumption of large public buildings more accurately and provide a scientific basis for ensuring the use of energy quotas and energy conservation.