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Developing machine learning-based models to estimate time to failure for PHM.

, , , and . ICPHM, page 1-6. IEEE, (2016)

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On-Demand Regression to Improve Preciseness of Time to Failure Predictions., , and . AAAI Fall Symposium: Artificial Intelligence for Prognostics, volume FS-07-02 of AAAI Technical Report, page 81-87. AAAI Press, (2007)Specification of Multi-Agent Systems in the Gamma Language., and . CCECE, page 1372-1375. IEEE, (2006)Two-stage classifications for improving time-to-failure estimates: a case study in prognostic of train wheels., and . Appl. Intell., 31 (3): 255-266 (2009)A Data Driven Approach for Smart Lighting., , and . IEA/AIE (2), volume 8482 of Lecture Notes in Computer Science, page 308-317. Springer, (2014)Exploring User Perceptions of Virtual Reality Scene Design in Metaverse Learning Environments., , , , and . CoRR, (2023)3D Scene Analysis Using UIMA Framework., , , , , and . IEA/AIE, volume 5579 of Lecture Notes in Computer Science, page 369-378. Springer, (2009)Multi-agent Planning for Ship Collision Avoidance., , and . RAM, page 549-554. IEEE, (2008)Toward failure mode and effect analysis for heating, ventilation and air-conditioning., , , and . CSCWD, page 408-413. IEEE, (2017)Transfer Learning-enabled Modelling Framework for Digital Twin., , , , and . CSCWD, page 113-118. IEEE, (2022)Experimental study on the stress and magnetic behavior of non-ferromagnetic materials in weak magnetic field., , , , and . ISIE, page 1-4. IEEE, (2021)