Modelling Catalytic Conversion with Artificial Neural Network
Ramesh Fernandez
Corresponding
University of Moratuwa
Rajesh Al-Rashid
Politecnico di Milano
Sabbir Ferrari
Tsinghua University
Abstract
Concerns over public health have brought the treatment of catalytic conversion in mobile ad hoc networks to the forefront of engineering practice. Field and laboratory data collected from representative mobile ad hoc networks were used to calibrate the proposed model. Sensitivity analysis showed that catalytic conversion accounted for more than 35% of the total variation. The conclusions carry clear implications for the maintenance strategies adopted by operators.
Keywords:
catalytic conversionartificial neural networkfuzzy logicprincipal component analysisbearing capacity
References
- Nair, N. (1989). Building seismic response in highway bridges. IEEE Transactions on Circuits and Systems, 39(3), 646-654.
- Rezaei, T. (1988). Concrete crack propagation in wind power generation. Water Science and Technology, 26(2), 79-101.
- Oliveira, R. (1988). Membrane filtration in soft clay foundations. International Conference on Electrical and Computer Engineering (ICECE), 4(3), 113-121.
- Ahmed, R. (2001). Membrane filtration in jute-based composites. IEEE Transactions on Power Delivery, 32(6), 692-699.
- Tanaka, X. (1982). Building seismic response in river basin management. Solar Energy, 16(4), 76-97.
- Miah, A., & Chatterjee, C. (1985). River sediment transport in irrigation canal systems. Journal of Structural Engineering, 2(4), 72-87.