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논문검색

Predicting Electricity Consumption Based on Optimized Model of GM(1,1)

원문정보

Zhang Zheng, Yang Shanlin, Liu Huizhou, Yu Bengong

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초록

영어

Optimized GM(1,1) model based on least absolute criteria is proposed in this paper. Since the initial condition of original GM(1,1) model is not very suitable, we use the modified latest data which generating from the accumulative generating operation as the new initial condition. And the least absolute criteria is applied instead of least square criteria to improve the stability and prediction accuracy of GM(1,1) model. Then the particle swarm optimization is adapted to the parameters optimization. At the end, the optimized GM(1,1) model is used to predict the whole social electricity consumption of China and the result shows its prediction accuracy is better than the original model and the GM(1,1) model with latest initial condition.

목차

Abstract
 1. Introduction
 2. Original GM (1,1) Model
 3. Optimized GM(1,1) Model
  3.1. Optimization of Initial Condition
  3.2. PSO-GM(1,1) Model based on Least Absolute Criteria
 4. Model Construction and Prediction
 5. Conclusion
 Acknowledgements
 References

키워드

  • Prediction; GM(11) model
  • Least absolute criteria
  • PSO
  • Initial condition

저자정보

  • Zhang Zheng School of Management, Hefei University of Technology, Hefei, 230009, P.R. China
  • Yang Shanlin School of Management, Hefei University of Technology, Hefei, 230009, P.R. China
  • Liu Huizhou Tongling Power Supply Company, Anhui Electric Power Corporation, Tongling, 244000, P.R. China
  • Yu Bengong School of Management, Hefei University of Technology, Hefei, 230009, P.R. China

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자료제공 : 네이버학술정보

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