عنوان مقاله [English]
In this paper, Group Method of Data Handling (GMDH)-type neural networks based on Genetic Algorithm, as an effective means to model the complex and nonlinear system, used for the modeling of turbofan engine. Fuel consumption is an important factor in turbofan engines, particularly in commercial and passenger aircraft engines. Regarding to its importance, fuel/air ratio influence on two main parameters, namely, specific fuel consumption and thrust investigated in this study at different altitudes for lower Mach numbers. Therefore, GMDH-type neural networks based on Genetic Algorithm developed for modeling. The impact of fuel / air ratio and flight altitude on thrust and specific fuel consumption of a turbofan engine that mathematical functions obtained for thrust and specific fuel consumption will be applied to optimization of the engine and estimation of best operating points. Finally, the GMDH model`s value compared with experimental data that show the effectiveness and accuracy of the network.