Abstract: Greenhouse climate and crop models and specially reduced models are necessary for bettering environmental management and control ability. In this paper, we present a new metaheuristic method, called Cuckoo Search (CS) algorithm, established on the life of a bird family for selecting the parameters of a reduced model which optimizes their choice by minimizing a cost function. The reduced model was already developed for control purposes and published in the literature. The proposed models target at simulating and predicting the greenhouse environment. [?]. This study focuses on the dynamical behaviors of the inside air temperature and pressure using ventilation. Some experimental results are used for model validation, the greenhouse being automated with actuators and sensors connected to a greenhouse control system on the cuckoo search methods to determine the best set of parameters allowing for the convergence of a criteria based on the difference between calculated and observed state variables (inside air temperature and water vapour pressure content). The results shown that the tested Cuckoo Search algorithm allows for a faster convergence towards the optimal solution than classical optimization methods.

Hasni Abdelhafid, Haffane Ahmed, Sehli Abdelkrim and Draoui Belkacem, “Cuckoo Search Optimization for Reduction of a Greenhouse Climate Model” International Journal of Advanced Computer Science and Applications(IJACSA), 7(7), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070785

@article{Abdelhafid2016,
title = {Cuckoo Search Optimization for Reduction of a Greenhouse Climate Model},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070785},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070785},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {7},
author = {Hasni Abdelhafid and Haffane Ahmed and Sehli Abdelkrim and Draoui Belkacem}
}