Pengaruh Perubahan Jumlah Layer Pada Prediksi Konsumsi Daya Listrik

Autor:	Sofiah Sofiah, Erliza Yuniarti, Mgs. Abd Fattah
Rok vydání:	2021
Předmět:	Mean absolute percentage error Electrical load Artificial neural network business.industry Statistics Electricity Time series business Performance metric Mathematics Power (physics)
Zdroj:	Jurnal Serambi Engineering. 6
ISSN:	2541-1934 2528-3561
DOI:	10.32672/jse.v6i4.3498
Popis:	Electrical load forecasting is very important to meet consumer needs according to load patterns. The electricity generated if it exceeds the amount needed will cause waste, on the other hand if the generator is smaller than the demand it can result in rotating power outages which result in losses to consumers. The purpose of this study was to determine the performance metric of the mean absolute percentage error (MAPE) in forecasting the load one day ahead by using an artificial neural network (ANN) algorithm. Forecasting with this ANN uses variations in the number of layers, namely 1 layer, 2 layers, 3 layers and other constant parameters. Forecasting uses time series data in period one from 1-28 December 2017. Forecasting output finds that ANN 1 layer provides the best value with a MAPE of 5,0053%, and is able to identify existing load patterns.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3298ee9f8ae15f1984c31ade112be6c9 https://doi.org/10.32672/jse.v6i4.3498 Zobrazit plný text záznamu