City electricity forecast based on the GM (1,1) model of metabolism

Zhixing Gao; Xianliang Shi

doi:10.1117/12.2613661

10 November 2021 City electricity forecast based on the GM (1,1) model of metabolism

Zhixing Gao, Xianliang Shi

Proceedings Volume 12050, International Conference on Smart Transportation and City Engineering 2021; 120502H (2021) https://doi.org/10.1117/12.2613661
Event: 2021 International Conference on Smart Transportation and City Engineering, 2021, Chongqing, China

Abstract

The traditional gray prediction theory requires less sample size and simple modeling, but it ignores new information that is more beneficial to prediction, and it is easy to cause the phenomenon of aging of the prediction model, and the prediction accuracy is not high. Therefore, a more scientific and reasonable GM (1,1) gray prediction model based on metabolism is proposed for the problem of urban electricity forecasting. This method avoids the limitations of local information modeling, and the metabolic processing of removing the oldest data of the original sequence of each prediction result ensures the effectiveness of the prediction sequence. The application of model prediction with Jurong city electricity data and the programming calculation of improved GM(1,1) model with Mtalab verify the practicability.

Citation Download Citation

Zhixing Gao and Xianliang Shi "City electricity forecast based on the GM (1,1) model of metabolism", Proc. SPIE 12050, International Conference on Smart Transportation and City Engineering 2021, 120502H (10 November 2021); https://doi.org/10.1117/12.2613661

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