单 位：
南阳师范学院;河南省月季种质创新与栽培技术工程研究中心;河南工业职业技术学院
关键词：
智能调控系统;育苗温室;多属性决策;灰熵
摘 要：
【目的】解决传统温室环境参数较难控制、水肥利用效率低等问题。【方法】引入灰色熵权理论,将各种环境要素视为不确定型多属性决策,计算与理想情况的接近度,建立了评价植物生长环境要素的数学模型;通过无线传感网络片上系统CC2530与传感器、物联网相结合,设计温室环境调控系统,调配温湿度、光照等各生长要素达到最优值,从而给植物配置最优生长环境。【结果】温室生产环境实地试验表明,无线网络通信丢包率不超过1%,满足环境信息实时采集和稳定传输要求,育苗植株成活率提高3.1%,同时节水率约为14%。【结论】该系统与传统温室手动调节环境参数的方法相比,运行稳定、可靠、有效,为提高温室育苗成活率、减少水资源浪费提供理论支持和实践指导,具有较高的推广价值。
译 名：
A Smart Control System for Greenhouse Designed Based on Grey Entropy Correlation Analysis
作 者：
LI Wei;JIN Liang;DU Li;Henan Polytechnic Institute;Nanyang Normal University;Henan Rose Germplasm Innovation and Cultivation Technology Engineering Research Center;
关键词：
smart control system;;greenhouse seedling;;multiple attribute decision making;;grey entropy
摘 要：
【Background and objective】Facility agriculture growing crops in greenhouses has developed rapidly in China over the past decades. As crop growth and its ultimate yield depend on a multitude of factors, how to control the local environment in greenhouses is important but challenging. The purpose of this paper is to present a smart control system for greenhouses designed based on grey entropy correlation analysis.【Method】A mathematical model for evaluating environmental factors responsible for plant growth in greenhouse was established first, and it was then integrated with the grey entropy weight theory. We took the factors affecting crop growth as multiple attributes to the uncertain decision-making system to calculate the optimal environment, from which we designed a monitoring system including wireless sensor network on chip CC2530, to allocate temperature, humidity, light and other factors into internet to adjust the optimal greenhouse environment for crops to grow.【Result】Test of the system in a greenhouse showed that the packet loss rate of the wireless network communication was less than 1%, meeting the requirements for real-time environmental information collection and stable transmission. It also increased the survival rate of seedlings by 3.1% and saved water use by 14%, compared with traditional method.【Conclusion】The control system we designed based on the grey entropy correlation analysis for greenhouse is stable, reliable and effective, compared with traditional methods that manually adjust environmental parameters in the greenhouse. It hence has a wide application for facility agricultural production by increasing the survival of crop seedlings and saving water usage simultaneously.
