Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Fuzzy set theory: foundations and applications
Fuzzy set theory: foundations and applications
Small engine control by fuzzy logic
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Engineering applications of Computational Intelligence
POPFNN-AAR(S): a pseudo outer-product based fuzzy neural network
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement
IEEE Transactions on Fuzzy Systems
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The spark ignition engine, by far, is the largest source of motive power in the world. Therefore, continuous endeavours to improve its performance are needed to save in fuel consumption and reduce cost. The main goal of this paper is to develop a neuro-fuzzy model for fuel Injection Time (IT) in order to design a neuro-fuzzy controller for improving the performance of the spark ignition engine. The obtained results showed that the developed neuro-fuzzy model is capable of predicting the fuel IT with a mean squared error less than 0.0072. Furthermore, the power produced by the neuro-fuzzy controller has higher values of about 15-73% than the power produced by the PID controller used in the basic engine. The BSFC is reduced by about 2-5% compared to the PID controller.