Data for: Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series

Name: Data for: Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series
Creator: Frederico Guimaraes
Published: 2019-03-23T16:08:44.238Z
Keywords: Electrical Engineering, Electric Power, Demand Forecasting

Guimaraes, Frederico; Javedani Sadaei, Hossein

doi:10.17632/f4fcrh4tn9.1

Data for: Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series

Published: 23 March 2019| Version 1 | DOI: 10.17632/f4fcrh4tn9.1

Contributors:

Frederico Guimaraes, Hossein Javedani Sadaei

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This is hourly load data of the power supply company of the city of Johor in Malaysia generated in 2009 and 2010. This data has been used in the paper "Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series", for Energy: The International Journal.

Data for: Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series

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