A TensorFlow-based deep auto-encoder model is proposed for short-term electric load forecasting and claimed to outperform traditional neural networks in accuracy and stability.
A strategy for short-term load forecasting by support vector regression machines,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Short-term Electric Load Forecasting Using TensorFlow and Deep Auto-Encoders
A TensorFlow-based deep auto-encoder model is proposed for short-term electric load forecasting and claimed to outperform traditional neural networks in accuracy and stability.