The Power of Training: How Different Neural Network Setups Influence the Energy Demand.
Daniel GeißlerBo ZhouMengxi LiuSungho SuhPaul LukowiczPublished in: ARCS (2024)
Keyphrases
- neural network
- electrical energy
- energy supply
- training algorithm
- training process
- feed forward neural networks
- feedforward neural networks
- solar energy
- back propagation
- power consumption
- training patterns
- data center
- backpropagation algorithm
- power supply
- multi layer perceptron
- pattern recognition
- energy saving
- recurrent networks
- energy minimization
- neural network training
- artificial neural networks
- electric vehicles
- error back propagation
- training set
- neural network structure
- energy conservation
- genetic algorithm
- supervised learning
- energy efficiency
- test set
- multi layer
- lead time
- neural nets
- electricity markets
- neural network model
- radial basis function
- total energy
- training data
- multilayer neural network
- energy consumption
- neural network is trained
- feed forward
- power distribution
- power generation
- hidden layer
- network architecture
- training phase