Genetic programming approach to predict torque and brake specific fuel consumption of 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

“…It is in this context, that the present study attempts to evolve a GEP model to bridge the gap of exploiting the simplicity and faster iteration speeds of an AI meta-model with that of the explicitness of polynomial regression technique. Due to the inherent advantage of the simplicity of the GEP approach it has already found a wide range of applicability to empirical formulation of various engineering problems where sufficient experimental results exist (Nazari, 2012;Togun and Baysec, 2010;Sarıdemir, 2010;Yang et al, 2013;Hashmi et al, 2011;Nazari and Pacheco Torgal, 2013). The footprint of GEP application in IC engine domains, till date has been very limited where studies investigating its prospects have been restricted to the modelling of performance parameters only .…”

Genetic algorithm optimization applied to the fuel supply parameters of diesel engines working at plateau

“…At the aspects of GA applications for modeling, Alonso et al [8] has employed the GA and ANN (artificial neural networks) for prediction of engine emissions, while Togun and Sedat [9] has established a GA model to predict the toque and BSFC for a gasoline engine based on experimental data. In Ref.…”

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

“…The training and testing data employed were same in both the studies. The comparative performance measures of both methods is detailed in Table 4 along with the R GEP /R ANN metric of comparison as developed in the study of Togun and Baysec [42]. Comparing the 2 approaches, it can be observed that the GEP prediction results are more accurate than the ANN ones.…”

“…Such explicit correlation in terms of common mathematical operators provide a distinct advantage of a greater transparency and simplicity in interpreting the results and provide a scope of investigating and corroborating the credibility of the developed model through parametric sensitivity analyses. The potential advantages of a GEP based modelling strategy has already been explored and credited in various engineering problems [35,36,[40][41][42][43]. However, the footprint of GEP application in IC engine domains is yet to mature as is evident from the very sparse literature available [42,44].…”

“…The potential advantages of a GEP based modelling strategy has already been explored and credited in various engineering problems [35,36,[40][41][42][43]. However, the footprint of GEP application in IC engine domains is yet to mature as is evident from the very sparse literature available [42,44]. The significance of the intended study can thus be rationalised as an endeavour to address a distinct knowledge gap wherein the potency of the GEP methodology needs to be explored as per its capability to model emission parameters which bear far more non-linear characteristics as compared to performance parameters in the IC engine domain.…”