Calibration of a greenhouse climate model using evolutionary algorithms

This paper presents a comparison of different evolutionary algorithms (EAs), such as Genetic Algorithms (GAs), Evolutionary Strategies (ES) and Evolutionary Programming (EP) to calibrate parameters of a climate model that describes the behaviour of air temperature and relative humidity (RH) within a greenhouse where a tomato crop is being grown. The objective was to determine which method generates parameter values that give the best prediction of the environment of a greenhouse located in the central region of Mexico. Simulation and analysis of the climate model show that the estimations of the inside temperature and RH are closest to the measurements when EP was used to calibrate the parameters of the greenhouse model