References
- Aliramezani, M., C. R. Koch, and R. Patrick. 2018. Phenomenological model of a solid electrolyte NOx and O2 sensor using temperature perturbation for on-board diagnostics. Solid State Ionics 321:62–68. doi:10.1016/j.ssi.2018.04.004.
- Aliramezani, M., C. R. Koch, M. Secanell, R. E. Hayes, and R. Patrick. 2019. An electrochemical model of an amperometric NOx sensor. Sensors and Actuators. B, Chemical 290:302–11. doi:10.1016/j.snb.2019.03.135.
- Bhardwaj, A., H. Bae, Y. Namgung, J. Lim, and S.-J. Song. 2019. Influence of sintering temperature on the physical, electrochemical and sensing properties of Α-Fe2O3-SnO2 nanocomposite sensing electrode for a mixed-potential type NOx sensor. Ceramics International 45 (2):2309–18. doi:10.1016/j.ceramint.2018.10.146.
- Cao, J., Y. Pang, X. Li, and J. Liang. 2018. Randomly translational activation inspired by the input distributions of ReLu. Neurocomputing 275:859–68. doi:10.1016/j.neucom.2017.09.031.
- Chen, Y. 2021. Effects of electrode microstructures on the sensitivity and response time of mixed-potential NO2 sensor based on La0.6Sr0.4CoO3 sensing electrode. IEEE Sensors Journal 21 (6):8621–26. doi:10.1109/JSEN.2021.3049182.
- Grimstad, B., and H. Andersson. 2019. ReLU networks as surrogate models in mixed-integer linear programs. Computers & Chemical Engineering 131:106580. doi:10.1016/j.compchemeng.2019.106580.
- Jiang, K., E. Cao, and L. Wei. 2016. NOx sensor ammonia cross-sensitivity estimation with adaptive unscented Kalman filter for diesel-engine selective catalytic reduction systems. Fuel 165:185–92. doi:10.1016/j.fuel.2015.10.019.
- krishna, S., and S. Vasu, 2018. Fuzzy PID based adaptive control on industrial robot system. Materials Today: Proceedings, International Conference on Materials Manufacturing and Modelling, ICMMM - 2017, Atlanta, USA , 9 - 11, March 5, 13055–60. doi:10.1016/j.matpr.2018.02.292.
- Liu, M., Z. Yu, Y. Zhang, H. Wu, H. Liao, and S. Deng. 2019. Prediction and analysis of high velocity oxy fuel (HVOF) sprayed coating using artificial neural network. Surface & Coatings Technology 378:124988. doi:10.1016/j.surfcoat.2019.124988.
- Liu, T., X. Zhang, L. Yuan, and J. Yu. 2015. A review of high-temperature electrochemical sensors based on stabilized zirconia. Solid State Ionics 283:91–102. doi:10.1016/j.ssi.2015.10.012.
- Nundy, S., T. Eom, K.-Y. Song, J.-S. Park, and H.-J. Lee. 2020. Hydrothermal synthesis of mesoporous ZnO microspheres as NOx gas sensor materials — calcination effects on microstructure and sensing performance. Ceramics International 46 (11):19354–64. doi:10.1016/j.ceramint.2020.04.278.
- Oostwal, E., M. Straat, and M. Biehl. 2021. Hidden unit specialization in layered neural networks: ReLu vs. sigmoidal activation. Physica A: Statistical Mechanics and Its Applications 564:125517. doi:10.1016/j.physa.2020.125517.
- Ritter, T., J. Lattus, G. Hagen, and R. Moos. 2019. On the influence of the NOx equilibrium reaction on mixed potential sensor signals: a comparison between Fe modelling and experimental data. Sensors and Actuators. B, Chemical 296:126627. doi:10.1016/j.snb.2019.126627.
- Roy, S., R. Banerjee, and P. K. Bose. 2014. Performance and exhaust emissions prediction of a CRDI assisted single cylinder diesel engine coupled with EGR using artificial neural network. Applied Energy 119:330–40. doi:10.1016/j.apenergy.2014.01.044.
- Sayyed, S., R. K. Das, and K. Kulkarni. 2021. Performance assessment of multiple biodiesel blended diesel engine and NOx modeling using ANN. Case Studies in Thermal Engineering 28:101509. doi:10.1016/j.csite.2021.101509.
- Söderena, P., J. Laurikko, C. Weber, A. Tilli, K. Kuikka, A. Kousa, O. Väkevä, A. Venho, S. Haaparanta, and J. Nuottimäki. 2020. Monitoring Euro 6 diesel passenger cars NOx emissions for one year in various ambient conditions with pems and NOx sensors. Science of the Total Environment 746:140971. doi:10.1016/j.scitotenv.2020.140971.
- Somwanshi, D., M. Bundele, G. Kumar, and G. Parashar, 2019. Comparison of fuzzy-PID and PID controller for speed control of DC motor using LabVIEW. Procedia Computer Science, International Conference on Pervasive Computing Advances and Applications- PerCAA 2019, Jaipur, India 152, 252–60. doi:10.1016/j.procs.2019.05.019.
- Taghavifar, H., H. Taghavifar, A. Mardani, and A. Mohebbi. 2014. Modeling the impact of in-cylinder combustion parameters of DI engines on soot and NOx emissions at rated EGR levels using ANN approach. Energy Conversion and Management 87:1–9. doi:10.1016/j.enconman.2014.07.005.