Title :
Neural models for an intelligent greenhouse - the heating
Author :
Eredics, P. ; Dobrowiecki, T.P.
Author_Institution :
Dept. of Meas. & Inf. Syst., Budapest Univ. of Technol. & Econ., Budapest, Hungary
Abstract :
High quality greenhouse control requires accurate modeling of the greenhouse as a thermal system along with all the influences affecting it. A decomposed model is the only way to tackle the complexity of such a system. A very important module of the decomposition is the heating system, due to its high impact on the overall financial cost of the greenhouse. This paper inspects the theoretical limits of heating modeling considering the stochastic circumstances present in the data measured in an industrial greenhouse. After that various models of different complexity and structure are examined. The best performance is produced by the usage of two neural networks separately for the warming and cooling heating pipe process.
Keywords :
greenhouses; neural nets; heating pipe process; heating system; intelligent greenhouse; neural models; thermal system; Actuators; Artificial neural networks; Green products; Heating; Predictive models; Temperature; Temperature measurement;
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2010 11th International Symposium on
Conference_Location :
Budapest
Print_ISBN :
978-1-4244-9279-4
Electronic_ISBN :
978-1-4244-9280-0
DOI :
10.1109/CINTI.2010.5672271