Modeling Electricity Consumption using Modified Newton's Method
In this paper we present modified Newton’s model (MNM) to model electricity consumption data. A previous method to model electricity consumption data was done using forecasting technique (FT) and artificial neural networks (ANN). A drawback to previous techniques is that computations give less relia...
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| 主要な著者: | , , , |
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| フォーマット: | E-Article |
| 言語: | English |
| 出版事項: |
International Journal of Computer Applications
2013
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| 主題: | |
| オンライン･アクセス: | http://ir.unimas.my/id/eprint/8467/1/Modeling%20Electricity%20Consumption%20using%20Modified%20Newton%E2%80%99s%20Method%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/8467/ http://dx.doi.org/10.5120/15046-3414 |
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| 要約: | In this paper we present modified Newton’s model (MNM) to model electricity consumption data. A previous method to model electricity consumption data was done using forecasting technique (FT) and artificial neural networks (ANN). A drawback to previous techniques is that computations give less reliable results when compared to MNM. A comparative analysis is carried out for FT, ANN and MNM to investigate which of these methods is the most reliable technique. The results indicate that MNM model reduced mean absolute percentage error (MAPE) to 0.93%, while those of FT and ANN were 3.01% and 3.11%, respectively. Based on these error measures, the study shows that the three methods are highly accurate modeling techniques, but MNM was found to be the best technique when mining information. Experimental results indicate that MNM is the most accurate when compared to FT and ANN and thus has the best competitive performance level. |
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