NAHL: a Neural network with an Augmented Hidden Layer

An interesting new architecture for artificial neural networks

****The current version of NAHL is able to adapt with both classification and regession****

Please read these papers carefuly :

1) https://www.researchgate.net/publication/355985669_Auto-NAHL_A_Neural_Network_Approach_for_Condition-based_Maintenance_of_Complex_Industrial_Systems

2) https://www.researchgate.net/publication/361382499_EL-NAHL_Exploring_Labels_Autoencoding_in_Augmented_Hidden_Layers_of_Feedforward_Neural_Networks_for_Cybersecurity_in_Smart_Grids

Please cite our NAHL papers as:

[1] T. Berghout, M. Benbouzid, S. M. Muyeen, T. Bentrcia, and L.-H. Mouss, “Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems,” IEEE Access, vol. 9, pp. 152829–152840, 2021, doi: 10.1109/ACCESS.2021.3127084.

[2] T. Berghout and M. Benbouzid, “EL-NAHL: Exploring Labels Autoencoding in Augmented Hidden Layers of Feedforward Neural Networks for Cybersecurity in Smart Grids,” Reliab. Eng. Syst. Saf., p. 108680, Jun. 2022, doi: 10.1016/j.ress.2022.108680.

[3] T. Berghout, M. Benbouzid, Y. Amirat and G. Yao, "Lithium-ion Battery State of Health Prediction with a Robust Collaborative Augmented Hidden Layer Feedforward Neural Network Approach," in IEEE Transactions on Transportation Electrification, doi: 10.1109/TTE.2023.3237726.