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Comparative analysis on the application of neuro‐fuzzy models for complex engineered systems: Case study from a landfill and a boiler
Author(s) -
Meher Saroj K.,
Behera Shishir K.,
Rene Eldon R.,
Park HungSuck
Publication year - 2017
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12215
Subject(s) - computer science , neuro fuzzy , artificial neural network , complex system , nonlinear system , boiler (water heating) , exploit , fuzzy logic , multivariable calculus , machine learning , fuzzy control system , artificial intelligence , control engineering , physics , computer security , quantum mechanics , engineering , waste management
This work aims at developing an explicit neuro‐fuzzy (NF) model to characterize complex engineered systems associated with high nonlinearity, uncertainties, and multivariable couplings. The NF model synergistically exploits the advantages of fuzzy belongingness of each input variable to all output variables and learning ability of neural networks. Owing to the inherent complexities associated with 2 complex engineered systems, a landfill and a boiler were selected to develop models that provide intelligent decisions for optimizing the operational parameters. Data compiled from field‐scale investigation/real plant operation involving various operating scenarios were used to develop the models. Predicting capability of the developed models was evaluated through the correlation coefficient and mean absolute percentage error values. Superiority of the proposed NF model to other similar models has been justified and demonstrated.