Jove, EstebanCasado Vara, RobertoCasteleiro-Roca, José-LuisMéndez Pérez, Juan AlbinoVale, ZitaCalvo-Rolle, José Luis2025-06-092025-06-092021-09-10E. Jove, R. Casado-Vara, J.-L. Casteleiro-Roca, J.A. Méndez Pérez, Z. Vale, J.L. Calvo-Rolle, A hybrid intelligent classifier for anomaly detection, Neurocomputing 452 (2021) 498–507. https://doi.org/10.1016/j.neucom.2019.12.138.1872-8286http://hdl.handle.net/2183/42214[Abstract] The present research is focused on the use of intelligent techniques to perform anomaly detection. This task represents a special concern in complex systems that operate in different regimes. Then, this work proposes a hybrid intelligent classifier based on one-class techniques, capable of detecting anomalies of the different operating ranges. The proposal is implemented over an industrial plant designed to control the water level in a tank, taking into consideration three different operating points. The hybrid classifier is validated by using real anomalies, obtaining successful results.engAttribution-NonCommercial-NoDerivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/http://creativecommons.org/licenses/by-nc-nd/3.0/es/One-classOutlier detectionSVDDAutoencoderPCAAPEjournal articleopen accesshttps://doi.org/10.1016/j.neucom.2019.12.138