due to the heterogeneous nature of granular soils and the involvement of many effective parameters in the geotechnical behavior of soil-foundation systems, the accurate prediction of shallow foundation settlements on cohesionless soils is a complex engineering problem. in this study, three new evolutionary-based techniques, including evolutionary polynomial regression (epr), classical genetic p...

 In this paper, a new Dynamic Geometric Genetic Programming (DGGP) technique is applied to empirical analysis of financial ratios and bankruptcy prediction. Financial ratios are indeed desirable for prediction of corporate bankruptcy and identification of firms’ impending failure for investors, creditors, borrowing firms, and governments. By the time, several methods have been attempted in...

Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...

gas compressibility factor (z-factor) is an important parameter widely applied in petroleum and chemical engineering. experimental measurements, equations of state (eoss) and empirical correlations are the most common sources in z-factor calculations. however, these methods have serious limitations such as being time-consuming as well as those from a computational point of view, like instabilit...

genetic programming (gp) is one of the computer algorithms in the family of evolutionary-computational methods, which have been shown to provide reliable solutions to complex optimization problems. the genetic programming under discussion in this work relies on tree-like building blocks, and thus supports process modeling with varying structure. in this paper the systems containing amino acids ...