Reverse modeling of a diesel engine performance by FCM and ANFIS
CompSysTech '07 Proceedings of the 2007 international conference on Computer systems and technologies
CompSysTech '09 Proceedings of the International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing
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Comparision of numerical tehnique and Al techniques for determination of performance and emission characteristics of a diesel engine has been done in this study. Three different techniques namely multiple regression analysis, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) were used for modeling aims. Engine torque (Tq), power (P), specific fuel consumption (Sfc), emission values such as HC, CO2 and NOx have been investigated. R2 values of Tq, P, Sfc, HC, CO2 and NOx were obtained as 99.9, 99.45, 99.32, 99.84, 99.71 and 99.26 respectively when ANN was used. Main contribution of this study includes; 1) First study that makes comperision between a numerical technique and Al tehniques. 2) Dynamic load value was used as input parameter. So that both engine performance modeling and emission characteristic determination were done regarding to changing load. 3) Highest prediction for values of output parameters were reached.