Parameter optimization for growth model of greenhouse crop using genetic algorithms
Parameter optimization for growth model of greenhouse crop using genetic algorithms
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DOI：
10.1016/j.asoc.2008.02.002
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Chunni Dai;Meng Yao;Zhujie Xie;Chunhong Chen;Jingao Liu
中科院分区：
文献类型：
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作者：
Chunni Dai;Meng Yao;Zhujie Xie;Chunhong Chen;Jingao Liu
自动化温室生产在中国还是一个新鲜事。准确建立温室植物在不同环境下的模拟生长模型是我国现代农业发展的一个重要课题。我们研究的目的是开发一种校准温室作物生长模型的方法。本文针对这个问题提出并评估了一种自适应遗传算法（GA）。这个新算法由两个 GA 组成。第一个用于参数化增长模型，第二个用于确定主遗传算法的算法参数。与其他两种遗传算法相比，这个新程序的优越性能通过其在三个测试函数和温室优化问题上的应用得到了证明。该技术可能是开发复杂生物模型的类似应用程序的良好框架，当出现一组新的环境条件或需要考虑亚种或品种之间的差异时，需要参数化。
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.