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作 者:钱晔 彭琳 杨婷娜 沈颖鸣 韦翌 孙吉红 QIAN Ye;PENG Lin;YANG Ting-na;SHENG Ying-ming;WEI Yi;SUN Ji-hong(School of Big Data(Information Engineering),Yunnan Agricultural University,Kunming 650201,China;Science and Technology in Yunnan,Kunming 650051,China)
机构地区:[1]云南农业大学大数据学院(信息工程学院),昆明650201 [2]云南省科学技术院,昆明650051
出 处:《湖北农业科学》2018年第22期132-135,共4页Hubei Agricultural Sciences
基 金:国家自然科学基金项目(31260292);云南省科技厅自然科学基金项目(2012FD020);云南省教育厅科研基金项目(2015Y194)
摘 要:针对不同等级的鲜切花价格差别较大且同一地区、相同种植面积的种植户种植收入差距较大的现象,设计基于智能算法的云南省鲜切花质量等级评价系统。首先采用GRNN神经网络算法构建基于智能算法的鲜切花质量等级评价模型,然后构建包括用户层、展示层、应用层、支撑服务层、数据层在内的鲜切花质量等级系统模型架构,将智能预测模型引入框架中,设计了基于智能算法的鲜切花质量等级评价系统。该系统的实施将为鲜切花种植企业、花农等提供种植优质鲜切花的模型,为科研人员提供对鲜切花质量等级的研究提供重要依据。Prices of different grades of fresh cut flowers are quite different,resulting in the income gap among planting households in the same area and with the same planting area.This paper designs a quality evaluation system for fresh cut flowers in Yunnan based on intelligent algorithms:Using GRNN neural network algorithm to construct a fresh cut flower quality level assessment model based on intelligent algorithms,and then to construct a fresh cut flower quality level systematic model including user layer,presentation layer,application layer,support service layer,and data layer.Within the framework of the fresh cut flower quality level system model,the intelligent forecasting model was introduced into the framework,and a fresh cut flower quality rating system based on intelligent algorithms was designed.The implementation of such system will provide models for quality fresh cut flowers for fresh-cut flower planters and farmers,providing scientific research personnel with an important basis for the study of quality grades of fresh cut flowers.
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