Artificial neural network and fuzzy expert system comparison for prediction of performance and emission parameters on a gasoline engine

A comparative study of GEP and an ANN strategy to model engine performance and emission characteristics of a CRDI assisted single cylinder diesel engine under CNG dual-fuel operation

“…Research studies dedicated in developing computationally cost effective system identification tools as a viable alternative have resulted in the foray of AI based meta modelling techniques (Canakci et al, 2006;Çelik and Arcaklio glu, 2005;Cay, 2013;Arcaklio glu and Çelıkten, 2005;G€ olcü et al, 2005;Kara Togun and Baysec, 2010;Mohamed Ismail et al, 2012;Najafi et al, 2009;kumar et al, 2011;Hosoz et al, 2013;Mariani et al, 2014;Tasdemir et al, 2011;Rai et al, 2012;Roy et al, 2014b;Al-Hinti et al, 2009) in the contemporary IC engine domain. The ability to quickly and efficiently simulate nonlinear trends in operating data have helped establish AI methodologies (ANN, ANFIS, Fuzzy etc.)…”

Development and validation of a GEP model to predict the performance and exhaust emission parameters of a CRDI assisted single cylinder diesel engine coupled with EGR

“…Studies involving the development of accurate yet computationally cost effective metamodels as a viable system identification tool (SIT) have resulted in the proliferation of various AI based techniques in contemporary IC engine paradigms [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]. Among the many facets of the AI paradigms, ANN endeavours with its inherent aptitude to quickly and efficiently emulate nonlinear trends in engine emission data have helped establish it as a credible metamodelling platform in engine optimization and real time control strategies.…”

Sparse Bayesian extreme learning machine and its application to biofuel engine performance prediction

“…In the current literature [5][6][7][8][9][10], many researches already attempted to apply artificial neural networks (ANNs) to model and predict the spark-ignition (SI) engine performance, either with or without using biofuels. Traditional ANN approach, such as backpropagation neural network (BPNN), was adopted in these studies.…”