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

Küçük Resim Yok

Tarih

2011

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

PERGAMON-ELSEVIER SCIENCE LTD

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

This study is deals with artificial neural network (ANN) and fuzzy expert system (FES) modelling of a gasoline engine to predict engine power, torque, specific fuel consumption and hydrocarbon emission. In this study, experimental data, which were obtained from experimental studies in a laboratory environment, have been used. Using some of the experimental data for training and testing an ANN for the engine was developed. Also the FES has been developed and realized. In this systems output parameters power, torque, specific fuel consumption and hydrocarbon emission have been determined using input parameters intake valve opening advance and engine speed. When experimental data and results obtained from ANN and FES were compared by t-test in SPSS and regression analysis in Matlab, it was determined that both groups of data are consistent with each other for p > 0.05 confidence interval and differences were statistically not significant. As a result, it has been shown that developed ANN and FES can be used reliably in automotive industry and engineering instead of experimental work. (C) 2011 Elsevier Ltd. All rights reserved.

Açıklama

Anahtar Kelimeler

Fuzzy expert system, Artificial neural network, Engine performance, Engine emission

Kaynak

EXPERT SYSTEMS WITH APPLICATIONS

WoS Q Değeri

Q1

Scopus Q Değeri

Q1

Cilt

38

Sayı

11

Künye