Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.374
After analyzing the features of species mass in engine combustion process, considering the accuracy and calculating time together, based on a network for one specie, this paper proposes an algorithm for selecting RBF-ANN centers with sectional method to apply in engine combustion species mass: in the image of species mass fraction-temperature, mass fraction area is divided into N parts dynamically, temperature area is divided into 6 fixed parts, then selects a sample as RBF-ANN center in every overlapped area of vertical (mass fraction) area and horizontal (temperature) area. Through calculating 135 diesel combustion process, it shows that the accuracy of function approximation has been improved greatly with sectional method, compared with subtractive cluster method.
Artificial neural network; RBF; Function approximation; Combustion; Chemical species
Xiao-Ping Guo, "An Algorithm for Selecting RBF-ANN Centers of Species Mass in Engine", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 40-44, doi:10.1109/CSIE.2009.374