Soft computing technology for modeling of greenhouse climate control

Lujuan Deng; Kanyu Zhang; Youmin Gong; Shengxue Wang

doi:10.1117/12.522080

2 September 2003 Soft computing technology for modeling of greenhouse climate control

Lujuan Deng, Kanyu Zhang, Youmin Gong, Shengxue Wang

Proceedings Volume 5253, Fifth International Symposium on Instrumentation and Control Technology; (2003) https://doi.org/10.1117/12.522080
Event: Fifth International Symposium on Instrumentation and Control Technology, 2003, Beijing, China

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.

Citation Download Citation

Lujuan Deng, Kanyu Zhang, Youmin Gong, and Shengxue Wang "Soft computing technology for modeling of greenhouse climate control", Proc. SPIE 5253, Fifth International Symposium on Instrumentation and Control Technology, (2 September 2003); https://doi.org/10.1117/12.522080

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available