Cold Greenhouse Tomato Environmental Parameters Optimization System Based On Data Mining

Greenhouse industry is an important part of agricultural industry,it has become the highest efficiency industry among agricultural planting.With the peculiar character of reduce the influence of meteorological factors,it can build the special environment to make the crop grow well in the unsuitable environment,and solve the problem of the vegetables supplies are very low in north of China.From 1970s,greenhouse production technology has developed very fast in our country.But it has certain disparity compared with developed countries such as United States and Denmark.The development of greenhouse is mostly based on varieties breeding and high-yield cultivation techniques,it is very difficult to achieve aim of improve economic benefits.And at the same time,some large greenhouse always set up a corresponding greenhouse information monitoring system in our country,it will monitor greenhouse information regularly,the greenhouse managers can make a more thorough understanding about the greenhouse environment and status of crop growth.It can provide greenhouse managers validation data about greenhouse.The monitoring and management of data are stored in the corresponding devices,they are used to provide a reference for managers,but the large amount of historical data accumulate such a long time has not been effective utilization.So how to make full use of these data,based on the large amounts of data,to find the valuable potential rules for greenhouse policymakers is the problem this article mainly discussed.Based on this problem,this article choose the technology of data warehouse and data mining,analysis the historical data and establish the corresponding model,extracting,transform the data from the heterogeneous data source and then loaded into the data warehouse.The data warehouse could provide quality and reliable data source for data analysis and data mining,ensure the truthfulness,accuracy of results.The data mining of greenhouse data could find the data unknown and hided.With this technology,greenhouse policymakers could understand the important environment model of parameters,the relationship between the environment parameters,the condition of plant diseases and insect pests,etc.To guide the greenhouse crop production better,and increase the economic benefits.The article makes the 80000 item of data about greenhouse tomato growth environment,growth status and the information data accumulate in the Northeast Agricultural University greenhouse tomato laboratory as the research object,studies the associated data and cluster analysis.According to the unique characteristics of greenhouse tomato data,classification and characteristics of discreteness,we choose algorithm of associated analysis Apriori,the algorithm of K-Means,it could complete the control of greenhouse tomato growth environment,establish the associated model between disease and the particular environment,and predict growth status,all of these could provide tomato greenhouse manager manufacturing strategy,to ensure the efficient and sustainable development of greenhouse tomato production,and provide reference for the research of related crops.At the same time,the system is based on B/S structure,the user does not need to install the huge client,they only need to connect to the corresponding server to access the relevant knowledge through a visual interface,it is convenient and fast,and provide users high-quality decision support information.