建筑节能
建築節能
건축절능
CONSTRUCTION CONSERVES ENERGY
2013年
2期
56-58
,共3页
最小二乘支持向量机%短期空调负荷%预测%fortran软件建模
最小二乘支持嚮量機%短期空調負荷%預測%fortran軟件建模
최소이승지지향량궤%단기공조부하%예측%fortran연건건모
Least Squares Support Vector Machine(LS-SVM)%short-term air-conditioning load%prediction%Modeling with Fortran
将最小二乘支持向量机(LS-SVM)引入空调负荷预测中,在Fortran软件平台上建立LS-SVM空调负荷预测模型,并将其应用于绵阳一栋办公类建筑的空调负荷预测中.试验表明所提出的方法预测精度较高,运算简单,收敛速度快,具有较强的可行性和实用性.
將最小二乘支持嚮量機(LS-SVM)引入空調負荷預測中,在Fortran軟件平檯上建立LS-SVM空調負荷預測模型,併將其應用于綿暘一棟辦公類建築的空調負荷預測中.試驗錶明所提齣的方法預測精度較高,運算簡單,收斂速度快,具有較彊的可行性和實用性.
장최소이승지지향량궤(LS-SVM)인입공조부하예측중,재Fortran연건평태상건립LS-SVM공조부하예측모형,병장기응용우면양일동판공류건축적공조부하예측중.시험표명소제출적방법예측정도교고,운산간단,수렴속도쾌,구유교강적가행성화실용성.
A new algorithm for short-term air-conditioning load forecasting is expounded based on the Least Squares Support Vector Ma-chine(LS-SVM) method, establishing a prediction model for air-conditioning load with the FORTRAN software. The LS-SVM prediction mod-el is used for predicting air-conditioning load of an office building in summer months in Mianyang area. Simulated results show that the LS-SVM method enjoys better forecasting accuracy and speed, which proved to be feasible and practical.
