… We introduce a new neural network architecture that we call “grid-functioned” neural networks.
It utilises a grid structure of network parameterisations that can be specialised for different …

… The variable Ahist (j) is used to denote if the grid functioned optimally for a specific case
year ‘j’. In the training data set the weighted average of each company’s SAIDI minutes are …

… The files `gfnn_code.zip` and `gfnn_data.zip` contain the code and data for the experiments
with grid-functioned neural networks discussed in chapter 3 of the thesis. The files `…

… We propose a new neural network architecture, “grid-functioned neural networks” (GFNN), …
Our results show that grid-functioned neural networks surpass other comparable models in …

… We can even use another neural network to predict the parameterization, which enables
generalization [5, 38, 42]. With the hybrid approach, one first obtains a local feature with the …

… Historically, the power grid functioned by sending electricity from traditional power plants,
such as coal and natural gas power plants to the customer. However, in recent years, the …

… My starting hypothesis is that the geometrical order of the grid functioned as a constitutive
pre-modern element of the rationalization process that is considered to be the main aspect of …

… This refers to a system component that employs a specialized type of neural network known
… inside the network. In contrast, negative values signify that a nano-grid functioned as an …

… Within the domain of image processing, GAN typically uses multilayered gridbased artificial
neural networks as its models: Convolutional Neural Network (CNN) is frequently used as …

… In this study, we fabricated the 3D-printed scaffold in the form of a “porous grid scaffold”, in
which the 3D-printed gelatin grid functioned as the basic structural network that was coated …