高校能源消耗建模研究与应用

针对高校能源消耗建模研究与应用问题,文中介绍了高校能耗日益增长现状,给出了高校能耗模型构建,为节约能源必须做好精准能耗预测.建立了灰色径向基函数神经网络高校能耗预测模型,并采用基于排序等分法赌盘规则选择算子的遗传算法对该模型进行全局优化,进一步用实例对比分析评估了模型的有效性.实践表明,优化后的模型能有效预测能耗,与传统单一的建模方式相比,有更好的拟合性、稳定性、预测精度和更快的收敛速度,为节能评估和设计提供了决策依据.

Modeling and Application Energy Consumption of Colleges and Universities

Focused on energy consumption modeling research and application problems in colleges and universities, this pa-per introduces the growing energy consumption situation in colleges and universities.The energy consumption modeling in colleges and universities is given to precise prediction of energy consumption.Energy consumption of radial basis function( RBF) neural network in colleges and universities is established based on a gray forecast model.Based on the uniform method roulette rule se-lection operator of genetic algorithm to global optimization of the model, the study further evaluated the effectiveness of the model with a practical example.The results shows that the optimized model can predict the energy consumption more effectively than tra-ditional single modeling method with a better fitting, stability, accuracy and faster convergence speed.The paper provides a deci-sion-making basis for energy saving assessment and design.