Study On Maize Recommendation Fertilization System Based On Data Mining Technology

The development of agricultural informatization and digitalization is the mainstream trend in nowadays.The use of data mining technology,information technology and intelligent decision-making technology to manage the cultivation of crops,fertilization,pest control,etc.,has a positive effect on further improving the quality of agricultural production.In the context of agricultural informatization construction,we can easily solve problems such as controlling fertilizer dosage and selecting fertilizer in the process of corn planting.Based on the above background,this study based on data mining technology,researches on corn fertilizer selection and fertilizer dosage control.In order to further improve the production of corn planting,improve the efficiency of corn production and realize the digitalization of agriculture,using data mining technology,Web GIS platform,intelligent space decision-making technology and Big Data Statistics,the data space,database and fertilization precision of corn intelligent fertilization system,the management and other aspects are analyzed to realize the realization of the corn intelligent fertilization system.The specific research contents are as follows:Firstly,the domestic and international viewpoints on variable fertilization,corn planting and data mining technology are studied,and the existing information in the existing corn fertilization planting is not shared,and the amount of fertilization cannot be quantified and controlled,which is used as the reference for this study.Moreover,using clustering algorithm based on K-means,data spatial processing and construction process are studied,and agricultural data analysis under Intelligent space construction and Web GIS data statistics and data analysis under the construction of smart space are counted,which provides the theoretical basis of the construction and implementation of the subsequent corn intelligent fertilization system.Secondly,the core of this research is to design the fertilization module,nutrient partition module and data acquisition module of the corn intelligent fertilization system,and improve the application practicability of the corn intelligent fertilization system on the premise of clear system flow construction.Using data mining technology,the login module,spatial query module,knowledge navigation module,precision management module,system management module,pest diagnosis and treatment module and database of corn intelligent fertilization system are designed.Based on the analysis of the functional requirements of corn intelligent fertilization system,Ensurethat the functions of the intelligent fertilization system can be effectively implemented into practical applications.Finally,the field learning method is used to analyze the knowledge-learning function and intelligent decision function of the corn intelligent fertilization system to research on the precise fertilization management and date warehouse collections,data decisions,etc.Which is based on the analization of the performance and function of the corn intelligent fertilization system.Practice has proved that this research on corn intelligent fertilization system can provide scientific basis for information interaction in corn fertilization and the accuracy of the model is over 80%,and basically achieve the goal of intelligent fertilization in corn planting.