2006Unpublished venueRequires access

Applying Support Vector Machine Method to Forecast Electricity Consumption

Shu-xia Yang, Yi Wang

Open publisher page 9 citations

Abstract

Electricity consumption reflects the electricity usage of the whole society, so the prediction study and analysis to electricity consumption have important realistic and theoretical significance. The influence that different factors affect the electricity consumption is in different degrees. And the influence works in complicated ways, which makes the characteristics of the electricity consumption forecast take on complexity, linearity and so on. To enhance the precision of the electricity consumption forecast, this paper adopts the support vector machine method to analyze the statistical data which influences electricity consumption with the aid of the computer and discover the intrinsic rule. This paper puts forward the corresponding electricity consumption forecasting model, and carries on the forecast to the electricity consumption with the actual data from 1980 to 2004, the result indicates that it's an accurate method to predict the electricity consumption

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What this paper is about

Electricity consumption reflects the electricity usage of the whole society, so the prediction study and analysis to electricity consumption have important realistic and theoretical significance. The influence that different factors affect the electricity consumption is in different degrees. And the influence works in complicated ways, which makes the characteristics of the electricity consumption forecast take on complexity, linearity and so on. To enhance the precision of the electricity consumption forecast, this paper adopts the support vector machine method to analyze the statistical data which influences electricity consumption with the aid of the computer and discover the intrinsic rule. This paper puts forward the corresponding electricity consumption forecasting model, and carries on the forecast to the electricity consumption with the actual data from 1980 to 2004, the result indicates that it's an accurate method to predict the electricity consumption

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Electricity consumption reflects the electricity usage of the whole society, so the prediction study and analysis to electricity consumption have important realistic and theoretical significance. The influence that different factors affect the electricity consumption is in different degrees. And the influence works in complicated ways, which makes the characteristics of the electricity consumption forecast take on complexity, linearity and so on. To enhance the precision of the electricity consumption forecast, this paper adopts the support vector machine method to analyze the statistical data which influences electricity consumption with the aid of the computer and discover the intrinsic rule. This paper puts forward the corresponding electricity consumption forecasting model, and carries on the forecast to the electricity consumption with the actual data from 1980 to 2004, the result indicates that it's an accurate method to predict the electricity consumption

Key concepts: Electricity, Consumption (sociology), Computer science, Support vector machine, Stand-alone power system, Electricity market, Environmental economics, Econometrics

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