As a typical deep network, stacked autoencoder (SAE) has an outstanding modeling capability in soft sensors due to its ability to extract deep features. However, SAE ignores the expanded ...

Serial-autoencoder for personalized recommendation. Higher Education Press . Journal Frontiers of Computer Science DOI 10.1007/s11704-023-2441-1 ...

Compared to SAE, the idea of SDGAE lies in stacking a series of hierarchical dual-guided autoencoder (DGAE), aiming to allow each DGAE to accurately reconstruct the original input data. It also ...

Normalizing and Encoding Source Data for an Autoencoder In practice, preparing the source data for an autoencoder is the most time-consuming part of the dimensionality reduction process. To normalize ...

For the State predictor variable with 3 possible values, the encoding is Michigan = 100, Nebraska = 010, Oklahoma = 001. If the State variable had an additional possible value, say Pennsylvania, the ...

First, for each latent variable, we find out the maximum value that it occupies across a set of randomly selected trials. We then change that specific latent to achieve its maximum value, and this new ...

Following this, the predicted x values were input into the decoder associated with the chemical VAE model and the SMILES string representations (or chemical structures of molecules) were obtained as ...

In chemical plants and other industrial facilities, the rapid and accurate detection of the root causes of process faults is essential for the prevention of unknown accidents. This study focused on ...