Dynamic Monitoring Methods for Carbon Emissions in Commercial Buildings Based on the LSSVM Algorithm
王雅 1周俊超 1张丹丹 1王婷婷1
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作者信息
1. 哈尔滨普华电力设计有限公司 黑龙江哈尔滨 150000
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摘要
针对现阶段商业楼宇碳排放监测精准度较低的问题,提出基于最小二乘支持向量机的分类和回归算法(Least Squares Support Vector Machine,LSSVM)的商业楼宇碳排放量动态监测方法.获取碳排放量数据并计算碳排放指标,设计基于LSSVM算法的商业楼宇碳排放量动态监测流程,实现对商业楼宇碳排放量的动态监测.通过设计对比实验,表明该研究方法监测精准度更高,具有更好的监测效果.
Abstract
By mining the carbon emission data of existing monitoring methods for carbon emissions in commercial buildings,it is found that the monitoring accuracy of carbon emissions is low,so a dynamic monitoring method for carbon emissions in commercial buildings based on the classification and regression algorithm of the least squares support vector machine(LSSVM)is proposed.By this method,carbon emission data is obtained,carbon emission indicators are calculated based on the obtained results,and the dynamic monitoring process for carbon emissions in commercial buildings based on the LSSVM algorithm is designed in combination with indicators,in order to achieve the dynamic monitoring of carbon emissions in commercial buildings.By designing comparative experiments,it is shown that this research method has higher monitoring accuracy and better monitoring effect.
关键词
回归算法/碳排放量动态监测/指标计算/监测方法
Key words
Regression algorithm/Dynamic monitoring of carbon emissions/Indicator calculation/Monitoring method
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