Share Email Print

Proceedings Paper

Soft computing technology for modeling of greenhouse climate control
Author(s): Lujuan Deng; Kanyu Zhang; Youmin Gong; Shengxue Wang
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The objective of this paper is present a reasonable system model to set greenhouse daytime optimal temperature thereby to achieve the most net profit. In order to set an optimal tmeperature point in a greenhouse, it is essential to construct plants growth model and calculate the cost of modifying environment. In this paper a soft computing system for greenhouse temperature setting has been developed and integrated. It includes three parts. One is an algorithm depending on the energy consumption of each component of heating and ventilation equipment according to two reasonable formulae. The other is a neural network for forecast the photosynthesis rate of tomato according to light intensity, temperature, CO2 concentration, and LAI. The sample data rooted in TOMGRO. The last part is a GA for searching an optimal temperature setting point in daytime.

Paper Details

Date Published: 2 September 2003
PDF: 6 pages
Proc. SPIE 5253, Fifth International Symposium on Instrumentation and Control Technology, (2 September 2003); doi: 10.1117/12.522080
Show Author Affiliations
Lujuan Deng, Shanghai Univ (China)
Zhengzhou Institute of Light Industry (China)
Kanyu Zhang, Shanghai Univ. (China)
Youmin Gong, Shanghai Univ. (China)
Shengxue Wang, Shanghai Univ. (China)

Published in SPIE Proceedings Vol. 5253:
Fifth International Symposium on Instrumentation and Control Technology
Guangjun Zhang; Huijie Zhao; Zhongyu Wang, Editor(s)

© SPIE. Terms of Use
Back to Top