胡瑾,闫柯,何东健,张海辉,辛萍萍,陶彦蓉.基于改进型鱼群算法的番茄光环境调控目标值模型[J].农业机械学报,2016,47(1):260-265.
Hu Jin,Yan Ke,He Dongjian,Zhang Haihui,Xin Pingping,Tao Yanrong.Light Environment Regulation Target Model of Tomato Based on Improved Fish Swarm Algorithm[J].Transactions of the Chinese Society for Agricultural Machinery,2016,47(1):260-265.
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基于改进型鱼群算法的番茄光环境调控目标值模型   [下载全文]
Light Environment Regulation Target Model of Tomato Based on Improved Fish Swarm Algorithm   [Download Pdf][in English]
投稿时间:2015-05-12  
DOI:10.6041/j.issn.1000-1298.2016.01.035
中文关键词:  番茄  改进型鱼群算法  光环境调控  目标值模型  温度  光饱和点
基金项目:国家自然科学基金项目(31501224)、“十二五”国家科技支撑计划项目(2012BAH29B04)和陕西省科学技术研究发展项目(2013K02-03、2014K08-02-03、2014K02-08-02)
作者单位
胡瑾 西北农林科技大学 
闫柯 西北农林科技大学 
何东健 西北农林科技大学 
张海辉 西北农林科技大学 
辛萍萍 西北农林科技大学 
陶彦蓉 西北农林科技大学 
中文摘要:To struggle with the problems of hard to acquire the optimum light value for tomato planting rapidly and precisely, a model was developed to control the light staying around the optimum value in the environment. In order to evaluate the optimum light saturation points under different temperatures, a novel light and temperature coupling optimizing method based on improved fish swarm algorithm was proposed. This new method effectively improved the optimum speed of traditional fish swarm algorithm through adjusting the vision and step dynamically. In addition, the method could avoid trapping into local optimum, and get more accurate optimal solution than genetic algorithm. Based on the light saturation points by optimizing this method, the light environment regulation target model was established with nonlinear regression. For verifying the accuracy of the method, a set of light and temperature coupling photosynthetic rate test was performed. The results showed that the model determination coefficient can reach 0.9999, the squared error term was 1543, and the root mean square error was 0.712. A comparison between simulation results and testing results was made, which showed the highly linear correlate relation with a value of 0.988 between them. In addition, the maximum relative error was less than ±2%, which is obviously better than the results of genetic algorithm. At last, a positive conclusion was obtained that the proposed light and temperature coupling optimizing method in this study can acquire the optimum light saturation points rapidly and dynamically, and has great significance to the precise control of light environment in facility.
Hu Jin  Yan Ke  He Dongjian  Zhang Haihui  Xin Pingping  Tao Yanrong
Northwest A&F University,Northwest A&F University,Northwest A&F University,Northwest A&F University,Northwest A&F University and Northwest A&F University
Key Words:tomato  improved fish swarm algorithm  light environment regulation  target value model  temperature  light saturation point
Abstract:

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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