基于神经网络和仿生算法的区域经济能源消耗结构优化

Optimization of Energy Consumption Structure of Regional Economy Based on Neural Network and Bionic Algorithm

为了进一步优化区域经济能源消耗结构,采用神经网络对区域能源消费总量进行预测,再根据预测结果及仿生算法来进行结构优化。首先,结合2002—2016年度的能源消耗及GDP等相关数据,建立神经网络预测模型,预测了后续年度的区域能源消耗总量;其次,结合年鉴数据及国家能源消耗相关政策,进行仿生算法的能源消耗结构优化,确定能源消耗比例;最后,以京津冀地区为例进行实例仿真,结果表明,预测精度较高且能有效地为能源结构方案的制定提供数据支持。

In order to further optimize the energy consumption structure of regional economy,a neural network is used to predict the total regional energy consumption,and the structure is optimized according to the prediction results and the bionic algorithm.Firstly,combining with the relevant data of energy consumption and GDP from 2002 to 2016,a neural network prediction model is established to predict the total regional energy consumption in subsequent years.Secondly,combining with the yearbook data and related policies of national energy consumption,the bionic algorithm-based energy consumption structure optimization is carried out to determine the energy consumption ratio.Finally,the simulation experiment is made by taking Beijing-Tianjin-Hebei region as a case study,and the results show that the prediction accuracy is high and it can effectively provide data support for energy structure plan formulation.