Data Mining In Afforestation Work Analysis And Prediction Application

In today’s computer technology, the rapid development of the social environment in the face of a broad array of information, how can help us to effectively collect and process useful data field of information technology is a hot issue. Data mining is to meet this demand has developed rapidly generating and data processing technology. Data mining is a collection of computer statistics, databases, artificial intelligence and other disciplines, content, from large database or data warehouse extract large potential value of information technology. It includes neural network technology, classification and prediction, the decision tree method, genetic algorithm, association rule mining, rough set method and visualization technologies and other major technologies. Through data mining technology in forestry information and data processing, data obtained from the mass of useful knowledge and decision-making meaningful information, which the forestry industry and forestry data processing problems can have a positive role in promoting.In this paper, data mining related theories and methods are described in detail on the domestic and international data mining technology in planting suitable tree planting job design prediction and analysis of current situation of research. To Forest Resource Inventory and silviculture survey data based data, C4.5decision tree algorithm and Apriori association rules algorithm has been improved, the design of afforestation planning system. Eucalyptus plantations on the growth and site factors related to the relationship between the process of analysis, the full use of the C4.5decision tree algorithm analysis and algorithm modeling exercise found that the growth of eucalyptus plantations in southern Hunan and elevation, slope, aspect slope position and soil site factors are closely related, and through the decision tree to generate a high degree of confidence extracted rule set. In data mining association rules experiment, using the improved Apriori algorithm modeling, the main tree species by the relationship between qualitative and quantitative correlation analysis, design, site preparation specifications in afforestation and other forestry measures the relationship between, spacing and other measures the relationship between afforestation and reforestation measures mixed ratio and other relationships. Meanwhile, the relationship between species by qualitative and quantitative correlation analysis, we found loblolly pine, pine, fir and poplar are the main tree species in afforestation projects. Through overlay analysis between rules between the main species found mixed relationship, the choice of tree species has certain guiding significance.