Genetic programming for multitimescale modeling

Genetic Programming for Economic Modeling

The problem of finding an econometric model expressing the mathematical relationship between empirically observed econometric variables can be viewed as a search of the space of possible computer programs for a program that produces the desired output for given inputs. This computer program can be found via the recently developed genetic programming paradigm which breeds populations of computer...

Genetic Programming for Multiscale Modeling

We propose the use of genetic programming (GP)—a genetic algorithm that evolves computer programs—for bridging simulation methods across multiple scales of time and/or length. The effectiveness of genetic programming in multiscale simulation is demonstrated using two illustrative, non-trivial case studies in science and engineering. The first case is multi-timescale materials kinetics modeling,...

Modeling Ghotour-Chai River’s Rainfall-Runoff process by Genetic Programming

Considering the importance of water and computing the amount of rainfall runoff resulted from precipitation in recent decades, using appropriate methods for predicting the amount of runoff from rainfall date has been really essential. Rainfall-runoff models are used to estimate runoff generated from precipitation in the catchment area. Rainfall-runoff process is totally a non-linear phenomenon....

Modeling Ghotour-Chai River’s Rainfall-Runoff process by Genetic Programming

Considering the importance of water and computing the amount of rainfall runoff resulted from precipitation in recent decades, using appropriate methods for predicting the amount of runoff from rainfall date has been really essential. Rainfall-runoff models are used to estimate runoff generated from precipitation in the catchment area. Rainfall-runoff process is totally a non-linear phenomenon....

Application of Genetic Programming as a Powerful Tool for Modeling of Cellulose Acetate Membrane Preparation