基于智能模型群的鲜切花产业平台的构建
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摘要
为保障云南鲜切花产业健康、可持续的发展,增强从业人员的收入,壮大鲜切花生产、销售企业的实力,确保亚洲最大鲜切花生产、拍卖基地的实力,通过对鲜切花产业平台建设的需求进行详细分析,拟使用多种不同的智能算法建立鲜切花病虫害预测模型、鲜切花价格预测模型、鲜切花价格预警系统以及鲜切花产量预测模型,将建立的模型群搭建于鲜切花产业平台上,构建基于智能算法群的鲜切花产业平台,提出云南省鲜切花产业发展的第一期、第二期和远景构建目标,充分发挥大数据技术、智能算法、管理信息系统学在农业领域中作用,为多学科结合构建智能平台提供参考依据。
In order to ensure the healthy and sustainable development of Yunnan fresh cut flower industry,strengthen the income of employees and expanding the strength of fresh cut production and sales enterprises,ensure the strength of the largest fresh cut flower production and auction base in Asia.Through detailed analysis of the demand for fresh cut flower industry platform,a variety of intelligent algorithms were used to establish prediction models for diseases and pests of fresh cut flowers,price prediction models for fresh cut flowers,early warning system for fresh cut flowers and prediction models for fresh cut flowers.The model group on the industrial platform of fresh cut flower and a new cut flower industrial platform based on intelligent algorithm group were built.The first,second and future vision of Yunnan′s cut flower industry were presented,to give full play to the big data technology,intelligent algorithm,management information systems in agricultural field,to provide reference for the construction of intelligent platform for the integration of multiple disciplines.
In order to ensure the healthy and sustainable development of Yunnan fresh cut flower industry,strengthen the income of employees and expanding the strength of fresh cut production and sales enterprises,ensure the strength of the largest fresh cut flower production and auction base in Asia.Through detailed analysis of the demand for fresh cut flower industry platform,a variety of intelligent algorithms were used to establish prediction models for diseases and pests of fresh cut flowers,price prediction models for fresh cut flowers,early warning system for fresh cut flowers and prediction models for fresh cut flowers.The model group on the industrial platform of fresh cut flower and a new cut flower industrial platform based on intelligent algorithm group were built.The first,second and future vision of Yunnan′s cut flower industry were presented,to give full play to the big data technology,intelligent algorithm,management information systems in agricultural field,to provide reference for the construction of intelligent platform for the integration of multiple disciplines.
引文
[1] 王淑娟.云南鲜切花产量连续23年全国第一总产值463.7亿元[J].云南农业,2017(5):95.
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[13] 钱晔,孙吉红,孙媛媛,等.农业大数据环境下的鲜切花行情监测系统设计[J].安徽农业科学,2018,15(57):185-187.
[14] 郑强,彭琳,邹秋霞,等.基于嵌入式Web服务器的远程温室监控系统设计[J].农机化研究,2013(11):84-87.
[15] 姜海燕,朱艳,徐焕良,等.作物模型资源构造平台(CMRCP)的构建研究[J].农业工程学报,2008,36(2):170-175.
[2] 周三多.管理学[M].北京:中国石化出版社,2010.
[3] 金帅军.基于GRNN神经网络的农作物虫害量预测系统设计[D].呼和浩特:内蒙古工业大学,2013.
[4] 李哲敏,许世卫,崔利国,等.基于动态混沌神经网络的预测研究:以马铃薯时间序列价格为例[J].系统工程理论与实践,2015,35(8):2083-2090.
[5] 魏明桦,郑金贵.基于改进BP神经算法的农产品价格预测模型的构建与实现[J].唐山师范学院学报,2014,36(2):66-68.
[6] 孙吉红,张丽莲,武尔维,等.基于智能算法的价格预测模型探究[J].计算机技术与发展,2014,24(11):107-110.
[7] 陈芳,楼文高.基于广义回归神经网络的蔬菜市场日价格预测[J].浙江农业学报,2015,27(7):1253-1258.
[8] 任伟宏.农产品市场价格预测方法探析[J].中国农学通报,2011,27(26):209-212.
[9] LIU C J,WECHSLER H.Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition[J].IEEE Transactions on Image Processing,2002,11(4):467-476.
[10] QIAO L S,CHEN S C,TAN X Y.Sparsity preserving projections with applications to face recognition[J].Pattern Recognition,2010,43(1):331-341.
[11] PAPAJORGJI P J,PARDALOS P M.Software engineering techniques applied to agricultural systems:An object-oriented and UML approach(applied optimization)[M].New York:Springer Verlag,2005.
[12] 钱晔,孙吉红,彭琳,等.基于智能算法的月季鲜切花病虫害预测模型的探究[J].计算机技术与发展,2017,27(12):156-160.
[13] 钱晔,孙吉红,孙媛媛,等.农业大数据环境下的鲜切花行情监测系统设计[J].安徽农业科学,2018,15(57):185-187.
[14] 郑强,彭琳,邹秋霞,等.基于嵌入式Web服务器的远程温室监控系统设计[J].农机化研究,2013(11):84-87.
[15] 姜海燕,朱艳,徐焕良,等.作物模型资源构造平台(CMRCP)的构建研究[J].农业工程学报,2008,36(2):170-175.