Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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GMDH Algorithm with Data Weighting Performance and Its Application to Power Demand Forecasting

데이터 가중 성능을 갖는 GMDH 알고리즘 및 전력 수요 예측에의 응용

  • 신재호 (인천대학교 전자공학과) ;
  • 홍연찬 (인천대학교 전자공학과)
  • Published : 2006.07.01
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Abstract

In this paper, an algorithm of time series function forecasting using GMDH(group method of data handling) algorithm that gives more weight to the recent data is proposed. Traditional methods of GMDH forecasting gives same weights to the old and recent data, but by the point of view that the recent data is more important than the old data to forecast the future, an algorithm that makes the recent data contribute more to training is proposed for more accurate forecasting. The average error rate of electric power demand forecasting by the traditional GMDH algorithm which does not use data weighting algorithm is 0.9862 %, but as the result of applying the data weighting GMDH algorithm proposed in this paper to electric power forecasting demand the average error rate by the algorithm which uses data weighting algorithm and chooses the best data weighting rate is 0.688 %. Accordingly in forecasting the electric power demand by GMDH the proposed method can acquire the reduced error rate of 30.2 % compared to the traditional method.

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References

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