|Table of Contents|

Research on Intelligent Diagnostic System of Pests and Diseases of Chinese Rose Based on Android Mobile Phone System

《北方园艺》[ISSN:1001-0009/CN:23-1247/S]

Issue:
2019年10
Page:
151-157
Research Field:
Publishing date:

Info

Title:
Research on Intelligent Diagnostic System of Pests and Diseases of Chinese Rose Based on Android Mobile Phone System
Author(s):
QIAN Ye12LI Chao3LI Tong4SUN Jihong5SHEN Yingming5CAI Mingfei1
(1.School of Big Data(Information Engineering),Yunnan Agricultural University,Kunming,Yunnan 650201;2.Key Laboratory of Agricultural Information Technology in Yunnan,Kunming,Yunnan 650201;3.Kunming Jingkun Technology Co.Ltd.,Kunming,Yunnan 650000;4.Party Committee,Yunnan Agricultural University,Kunming,Yunnan 650201;5.Science and Technology Institute in Yunnan,Kunming,Yunnan 650051)
Keywords:
qualitymaximum profitintelligent diagnosis systemAndroidclustering analysis algorithm
PACS:
-
DOI:
10.11937/bfyy.20182746
Abstract:
In order to strengthen the quality management of fresh cut flowers and ensure the maximum profit of growers,for the convenience of growers,the fresh cut flowers were taken as an example,the intelligent system of the pests and diseases of Chinese rose was creatively proposed based on Android mobile phone system.Under the guidance of system engineering ideas,using the Android system,SQLite database technology,clustering algorithm,software engineering,management information system,MATLAB platform and other related knowledge and technology for system design and mobile APP development,the treatment plan was realized based on the names of diseases identified according to the symptoms of the leaves and stems of the rose during the whole process of planting seedlings and picking.The on-site test was carried out for the intelligent diagnosis system,and the cluster analysis algorithm was used to analyze on the MATLAB platform.The improved scheme of the intelligent diagnosis system was proposed to realize the intelligent and convenient mobile APP pest and disease intelligent diagnosis system,effectively strengthening the cultivation of fresh cut flowers.The safety and efficiency of management were achieved,thus protecting the interests of growers and fresh cut flower industries.

References:

[1]胡建东,余泳昌,江敏,等.PDA作物施肥通专家系统的技术研究[J].农业工程学报,2006,22(8):149-152.[2]郭银巧,郭新宇,李存东,等.基于知识模型的玉米栽培管理决策支持系统[J].农业工程学报,2006,22(10):163-166.[3]刘晴蕊,何东健,张宏鸣,等.苹果病害智能诊断方法研究与设计[J].农机化研究,2011,33(4):76-78,84.[4]陈立平,王东辉,赵春江,等.掌上电脑农业专家系统开发平台的研究与开发[J].农业工程学报,2002,18(3):142-145.[5]涂运华,王东辉,赵春江.基于Windows CE的HPC/PDA农业专家系统开发平台的研究与开发[J].高技术通讯,2000(10):28-31.[6]雷宏洲.Windows Mobile 技术在农业中的应用领域[J].农业网络信息,2007(10):31-32.[7]欧阳建权,钱跃良,褚诚缘,等.基于PDA的农业专家系统的设计和实现[J].计算机工程与应用,2002,38(2):30-31,114.[8]张荣安,胡建东,高知林,等.基于Palm OS平台的农业施肥通PDA的研制[J].河南农业大学学报,2004,38(1):23-27.[9]魏圆圆,王儒敬,张英.农业智能系统开发平台的知识表示与推理策略[J].智能系统学报,2008,3(6):523-528.[10]杨林楠,郜鲁涛,林尔升,等.基于Android系统手机的甜玉米病虫害智能诊断系统[J].农业工程学报,2012,28(18):163-168.[11]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):107-109.[12]董玉德,丁保勇,张国伟,等.基于农产品供应链的质量安全可追溯系统[J].农业工程学报,2016,32(1):280-285.[13]吴亚峰,索依娜.Android核心技术与实例详解[M].北京:电子工业出版社,2010.[14]孟猛.基于B/S结构的农产品质量安全追溯系统研究[J].热带农业工程,2010,34(3):21-24.[15]张亚科,马孝义.农产品质量安全追溯系统设计与实现[J].陕西农业科学,2011(6):244-146.[16]张文静,王晶,杨捧,等.农业专家系统可视化人机交互界面的设计[J].农机化研究,2008(9):120-121,131.[17]AIZENBERG I,SHEREMETOV L,VILLA-VARGAS L.Multilayer neural network with multi-valued neurons in time series forecasting of oil production[J].Neurocomputing,2016,175:980-989.[18]FINK O,ZIO E,WEIDMANN U.Predicting time series of railway speed restrictions with time-dependent machine learning techniques[J].Expert Systems With Applications,2013,40(15):6033-6040.[19]FINK O,ZIO E,WEIDMANN U.Predicting component reliability and level of degradation with complex-valued neural networks[J].Reliability Engineering and System Safety,2014,121(6):198-206.[20]AIZENBERG I N.Pattern recognition using neural network based on multi-valued neurons[M].Berlin Heidelberg:Lecture Notes in Computer Science,1999:383-392.[21]张德丰.MATLAB神经网络应用设计[M].北京:机械工业出版社,2009.[22]赵荣钦,黄贤金,钟太洋,等.聚类分析在江苏沿海地区土地利用分区中的应用[J].农业工程学报,2010,26(6):310-314.[23]马智民,乔亮.聚类分析在土地利用功能分区中的应用:以西安市雁塔区为例[J].国土资源科技与管理,2007,24(6):90-93.

Memo

Memo:
-
Last Update: 2019-06-27