Contextually Enhanced ES-dRNN with Dynamic Attention for Short-Term Load Forecasting

12/18/2022
by   Slawek Smyl, et al.
0

In this paper, we propose a new short-term load forecasting (STLF) model based on contextually enhanced hybrid and hierarchical architecture combining exponential smoothing (ES) and a recurrent neural network (RNN). The model is composed of two simultaneously trained tracks: the context track and the main track. The context track introduces additional information to the main track. It is extracted from representative series and dynamically modulated to adjust to the individual series forecasted by the main track. The RNN architecture consists of multiple recurrent layers stacked with hierarchical dilations and equipped with recently proposed attentive dilated recurrent cells. These cells enable the model to capture short-term, long-term and seasonal dependencies across time series as well as to weight dynamically the input information. The model produces both point forecasts and predictive intervals. The experimental part of the work performed on 35 forecasting problems shows that the proposed model outperforms in terms of accuracy its predecessor as well as standard statistical models and state-of-the-art machine learning models.

READ FULL TEXT

page 1

page 4

page 5

page 8

page 9

research
12/05/2021

ES-dRNN: A Hybrid Exponential Smoothing and Dilated Recurrent Neural Network Model for Short-Term Load Forecasting

Short-term load forecasting (STLF) is challenging due to complex time se...
research
03/17/2022

Recurrent Neural Networks for Forecasting Time Series with Multiple Seasonality: A Comparative Study

This paper compares recurrent neural networks (RNNs) with different type...
research
03/02/2022

ES-dRNN with Dynamic Attention for Short-Term Load Forecasting

Short-term load forecasting (STLF) is a challenging problem due to the c...
research
01/24/2023

Forecasting the 2016-2017 Central Apennines Earthquake Sequence with a Neural Point Process

Point processes have been dominant in modeling the evolution of seismici...
research
11/16/2017

Speech Dereverberation with Context-aware Recurrent Neural Networks

In this paper, we propose a model to perform speech dereverberation by e...
research
12/16/2021

A Statistics and Deep Learning Hybrid Method for Multivariate Time Series Forecasting and Mortality Modeling

Hybrid methods have been shown to outperform pure statistical and pure d...
research
10/18/2022

Research of an optimization model for servicing a network of ATMs and information payment terminals

The steadily high demand for cash contributes to the expansion of the ne...

Please sign up or login with your details

Forgot password? Click here to reset