Date of Award
2012
Document Type
Thesis
First Advisor
Chang, Shoou-Yuh
Abstract
The objective of this thesis research is to apply two artificial neural network (ANN) methods, back-propagation neural network (BPN) and radial basis function generalized regression neural network (RBFGRNN) in two environmental engineering case studies to explore their ability to modeling the complex environmental engineering systems. The traditional environmental engineering systems modeling are frequently using the physical-based modeling methods.
Recommended Citation
Tao, Xiaojue, "Artificial Neural Network Application In Environmental Engineering." (2012). Theses. 88.
https://digital.library.ncat.edu/theses/88