J Gama, PP Rodrigues, E Spinosa… - Web Intelligence and …, 2010 - ebooks.iospress.nl
In the last two decades, machine learning research and practice has focused on batch learning, usually with small datasets. Nowadays there are applications in which the data are …
YD Xue, W Luo, L Chen, HX Dong, LS Shu… - … and Underground Space …, 2023 - Elsevier
Accurate, continuous real-time perception of surrounding rock conditions on the tunnel boring machine (TBM) tunnel face provides particularly important prior information to ensure …
H Ren, X Liao, Z Li, A Ai-Ahmari - Applied Intelligence, 2018 - Springer
Anomaly detection has received much attention due to its various applications. Generally, the first step to discover anomalies is a data representation method which reduces …
In spite of being a small country, concerning geographic area and population size, Portugal has a very active and respected Artificial Intelligence community, with a good number of …
P Pereira, RP Ribeiro, J Gama - … , DS 2014, Bled, Slovenia, October 8-10 …, 2014 - Springer
Abstract Machine or system failures have high impact both at technical and economic levels. Most modern equipment has logging systems that allow us to collect a diversity of data …
Abnormal pattern detection is an important task in series data anomaly detection. Because of the noise interference, the accuracy of abnormal detection method based on deterministic …
Recently, predicting multivariate time-series (MTS) has attracted much attention to obtain richer semantics with similar or better performances. In this paper, we propose a tri-partition …
Alarm fatigue caused by false alarms and alerts is an extremely important issue for the medical staff in Intensive Care Units. The ability to predict electrocardiogram and arterial …
This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian …