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...

Forecasting the prices of metals is important in many aspects of economics. Metal prices are also vital variables in financial models for revenue evaluation, which forms the basis of an effective payment regime using resource policymakers. According to the severe changes of the metal prices in the recent years, the classic estimation methods cannot correctly estimate the volatility. In order to...

precipitation is considered as one of the most important factures in water cycle. prediction of monthly precipitation is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins.in this study we studied and evaluated gene expression programming to predict the precipitation of the kakareza river (in lorestan...

This study is aimed at improving a formula that enables easy, correct, and fast estimation of an Early-Stage Cost Buildings (ESCE). formula, enabling ESCE, was developed by the authors based on artificial neural networks gene expression programming. A quantity survey conducted for hundred construction projects, data set created. analysed with many Artificial Neural Networks to determine variabl...

conclusions some results of the correlation coefficients are not the same with visualization. the reason may be due to the small number of data. materials and methods in the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as spearman’s rank correlation coefficient and blomqvist’s measure, and compared them with pearson’s correlation coefficie...