Analysis of many civil engineering phenomena is a complex problem due to the participation of a large number of factors involved. During the past few years artificial neural networks (ANNs) have been the most widely used pattern recognition technique in modeling of complex civil engineering problems; however they suffer from a number of drawbacks. In this paper the feasibility of using a new evolutionary polynomial regression (EPR) method, for capturing nonlinear interaction between various parameters of civil engineering systems, is investigated. Like ANN, EPR can operate on large quantities of data. In addition, it provides a structured representation of the system, which allows the user to gain additional information on how the system performs. Capabilities of the EPR methodology are illustrated by application to two complex practical civil engineering problems which are difficult to solve or interpret using conventional approaches. The merits and limitations of the proposed method are discussed in detail.
|Titolo:||Evaluation of liquefaction potential based on CPT results using Evolutionary Polynomial Regression|
|Data di pubblicazione:||2010|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/j.compgeo.2009.07.006|
|Appare nelle tipologie:||1.1 Articolo in rivista|