Symbolic regression (SR) is a machine learning-based regression method based on genetic
programming principles that integrates techniques and processes from heterogeneous …

Discovering knowledge from data is a quantum jump from quantity to quality, which is the
characteristic and the spirit of the development of science. Symbolic regression (SR) is …

Using only a limited number of computationally expensive functions, we show a way how to
construct accurate and computationally efficient approximations of the Colebrook equation …

In recent years, machine-learning methods have profoundly impacted research in the
interdisciplinary fields of physics. However, most machine-learning models lack …

The Colebrook equation is a popular model for estimating friction loss coefficients in water
and gas pipes. The model is implicit in the unknown flow friction factor, f. To date, the …

This paper provides a new unified formula for Newtonian fluids valid for all pipe flow regimes
from laminar to fully rough turbulent flow. This includes laminar flow; the unstable sharp …

The empirical Colebrook equation from 1939 is still accepted as an informal standard way to
calculate the friction factor of turbulent flows (4000< Re< 108) through pipes with roughness …

Artificial bee colony programming (ABCP) is a novel evolutionary computation based
automatic programming method, which uses the basic structure of artificial bee colony (ABC) …

Predictive emission monitoring systems (PEMS) are software solutions for the validation and
supplementation of costly continuous emission monitoring systems for natural gas electrical …

In this paper, we analyze the interpretable models from real gasification datasets of the
project “Centre for Energy and Environmental Technologies”(CEET) discovered by symbolic …