基于改进平衡优化器算法的电力消费预测

Electricity Consumption Prediction Based onImproved Equilibrium Optimizer Algorithm

针对当前用电预测模型预测精度不足的问题,提出一种基于改进平衡优化器算法的电力消费预测方法。首先,在基本平衡优化器中引入自适应搜索机制,以克服其易陷入局部最优的缺陷;其次,使用自适应平衡优化器调节梯度增强回归器的参数;最后,使用平衡优化器改进的优化梯度增强回归器进行电力消费预测。为了验证所提模型的有效性,使用大规模数据集对所提算法进行了测试。结果表明,所提出的电力消费预测模型具有较好的预测准确性和预测稳定性。

A power consumption prediction method based on an improved equilibrium optimizer algorithm was proposed to address the issue of insufficient prediction accuracy in current power consumption prediction models.Firstly,an adaptive search mechanism was introduced into the basic equilibrium optimizer to overcome its vulnerability to falling into local optima;secondly,an adaptive equilibrium optimizer was used to adjust the parameters of the gradient enhanced regressor;finally,the optimized gradient enhanced regressor improved by the equilibrium optimizer was used for power consumption prediction.In order to verify the effectiveness of the proposed model,a large-scale dataset was used to test the proposed algorithm.The results indicate that the proposed power consumption prediction model has good prediction accuracy and stability.