Paper Title:
Weighted LS-SVM Method for Building Cooling Load Prediction
  Abstract

A number of different forecasting methods have been proposed for cooling load forecasting including historic method, real-time method, time series analysis, and artificial neural networks, but accuracy and time efficiency in prediction are a couple of contradictions to be hard to resolve for building cooling load prediction. In order to improve the prediction accuracy of cooling load time series, weighted least squares support vector machine regression (WLS-SVM) method for a chaotic cooling load prediction is proposed. In this method, a sliding time window is built and data in the sliding time window are employed to reconstruct the dynamic model. Different weights are assigned to different data in the sliding time window, and the model parameters are refreshed on-line with the rolling of the time window. The results show that the method has more superior performance than other methods like LS-SVM.

  Info
Periodical
Advanced Materials Research (Volumes 121-122)
Edited by
Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo
Pages
606-612
DOI
10.4028/www.scientific.net/AMR.121-122.606
Citation
X. M. Li, J. S. Chen, L. X. Ding, "Weighted LS-SVM Method for Building Cooling Load Prediction", Advanced Materials Research, Vols. 121-122, pp. 606-612, 2010
Online since
June 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Yun Yun Zhao, Yan Ping Zhang, Wei Deng, Shu Hong Huang
Abstract:A simulation model of the condenser in a 600MW supercritical thermal power plant was developed by using Matlab/Simulink. The important...
897
Authors: Kun Luo, Cheng Zhao, Xiang Li
Chapter 5: Materials in Energy and Environment (2)
Abstract:The paper had researched relief annealing of 65Mn Metal Rubber. Test results had shown that relief annealing significantly changed static and...
2956
Authors: Cui Cui Qin, Li Hua Zhao
Chapter 1: Materials Science and Engineering
Abstract:Natural ventilation is the most effective measure to reduce the cooling energy consumption, but it is quite difficult to control and...
597
Authors: Xing Lei Yin, Zhe Tian, Kui Xing Liu, Feng Li
Chapter 9: Environmentally Sustainable Manufacturing Processes and Systems
Abstract:Combined system of radiant cooling and dedicated outdoor air system (DOAS) has advantage in energy-saving and thermal comfort. In order to...
1458
Authors: Wei Chen, Yong Ping Feng, Na Zheng, Ying Chen
Chapter 3: Metallurgical Technologies
Abstract:For understanding the surface and internal defects of Q195 steel of 150mm×220mm rectangular bloom, a solidification heat transfer mathematics...
932