The Application And Study Of Soil Quality Grade Evaluation Based On Decision Tree

In recent years, with population growth and rapid socio-economic development, "Population, resources, food, the environment," the structural problem has been caused widespread concern around the world. Fertility of arable land will have a direct impact on the sustainable development of agriculture and food security. Soil is the basis for agricultural production, farmland is the people's survival and irreplaceable the most basic means of production. Farmland is the essence of the land, which is the most important resource for agricultural production. As an important evaluation of the quality of cultivated land areas, one of the fertility of arable land's tasks is that must find out a certain area of cultivated land quality, quantity and distribution of space. Arable land in fertility evaluation is to strengthen the quality of cultivated land and make rational use of land an important basis .The major significance of doing a good job of arable land fertility evaluation is to create conditions for the rational use of land resources, prevention of land degradation, improved use of arable land, farmland protection and construction quality, food security, and agricultural restructuring. Therefore, this article in Dehui City, Jilin Province to conduct a pilot survey of arable land fertility, using data mining technology, selects SQL Server2000, Java and Excel as a development tool, to achieve a grip on the investigation and assessment of arable land, provides a smooth technology for the construction of the grip levels, edit, query, retrieve and update, and has made some prog??.Through the use of traditional soil survey methodology and data mining technology, from Dehui City, Jilin Province plans grouper data source 20 randomly selected records. Grades to grip the object, from organic matter, nitrogen, phosphorus, and potassium to analyze the problem of arable land fertility levels of Dehui City. Common use of data mining in the classification algorithm - Decision Tree Algorithm, Dehui City, Jilin Province established a grip of arable land evaluation model. And then apply this model to 15,326 records training, get - Results and grade level of analysis used by the classification results were compared. Farmland fertility levels consistent grading results prove that this method can be used for farmland fertility ratings. This article is useful to explore the grip on the evaluation method.This paper in the course of the study, the software platform for building soil fertility levels of arable land, through the parameters and results of the output of automation plans, worked out a set of data mining technologies for the use of arable land fertility survey and evaluation of the quality of the effective methods of work and technical processes. Thus greatly reduce the digital editing of the workload and improve work efficiency.