Mar 25, 2021 · This paper proposes a novel algorithm for spatially correlated multiple loads wherein a global parameter is learned from state-space parameters ...
This paper proposes a novel algorithm for spatially correlated multiple loads wherein a global parameter is learned from state-space parameters of individual ...
Mar 27, 2021 · This paper proposes a novel algorithm for spatially correlated multiple loads wherein a global parameter is learned from state-space parameters ...
A novel gated dual convolutional neural network model with autoregressive method and attention mechanism for probabilistic load forecasting · Engineering, ...
1. DOI - Is supplement to Remodelling State-Space Prediction with Deep Neural Networks for Probabilistic Load Forecasting. Journal.
This paper proposes a novel algorithm for spatially correlated multiple loads wherein a global parameter is learned from state-space parameters of individual ...
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This paper proposes a novel neuroevolution algorithm for handling the uncertainty associated with load forecasting.
We present a novel approach to probabilistic time series forecasting that combines state space models with deep learning.
Missing: Remodelling Prediction Load
The main idea is to utilize the state-space approaches to dynamically adjust the weight coefficients used to combine the base models. The dynamic ensemble ...