Parameter optimization for growth model of greenhouse crop using genetic algorithms

Authors:
Chunni Dai;Meng Yao;Zhujie Xie;Chunhong Chen;Jingao Liu
Affiliations:
School of Information Science and Technology, East China Normal University, Shanghai 200062, PR China and College of Physics and Electronic Engineering, Guangxi University for Nationalities, Nanni ...;School of Information Science and Technology, East China Normal University, Shanghai 200062, PR China;Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201106, PR China;Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201106, PR China;School of Information Science and Technology, East China Normal University, Shanghai 200062, PR China
Venue:
Applied Soft Computing
Year:
2009

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Abstract

Automatic greenhouse production is quite new in China. For the development of our modern agriculture it is a significant issue to accurately formulate the simulation growth models of greenhouse plants in different environments. The objective of our study was to develop an approach to calibrate the growth model of greenhouse crop. In this paper, an adaptive genetic algorithm (GA) is proposed and evaluated for this issue. This new algorithm is composed of two GAs. The primary one is utilized to parameterize the growth model and the secondary is to determine the algorithmic parameters of the primary GA. The superior performance of this new procedure is demonstrated through its applications to three test functions and the greenhouse optimization problems compared with other two GAs. This presented technique may be a fine framework for the development of similar application for complex biological models that require parameterization when a new set of environmental conditions arises or there is a need to account for differences among subspecies or varieties.