
Abstract Genetic programming is an orderly method for getting computers to regularly solve a problem. The genetic programming creates a computer program from an obtained data and solves the problem. In this work, treatment of oily wastewaters with synthesized mullite ceramic microfiltration membranes was studied and a new approach for modeling of the membrane flux is presented. The model used input parameters for operating conditions (flux and filtration time) and feed oily wastewater quality (oil concentration, temperature, trans-membrane pressure and cross-flow velocity). The genetic programming utilized here delivers a mathematical function for the membrane flux as a function of the independent variables stated above. Parameters for controlling and termination criterion for a run are provided by the user. Result is provided as a tree of functions and terminals. The results thus obtained from the genetic programming model demonstrated good representation of the experimental data with an average error of less than 5%.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 53 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
