基于Boosting的决策树集成土地评价  

Land evaluation based on Boosting decision tree ensembles

作　　者：薛月菊[1] 胡月明[2] 杨敬锋[1] 陈强[1] 

机构地区：[1]z华南农业大学南方农业机械与装备关键技术省部共建教育部重点实验室,广州510642 [2]华南农业大学信息学院,广州510642

出　　处：《农业工程学报》2008年第7期78-81,共4页Transactions of the Chinese Society of Agricultural Engineering

基　　金：广东省自然科学基金项目(04300504,05006623);广东省科技攻关项目(2005B20701008,2005B10101028,2004B20701006);国家科技攻关项目(2002BA516A08);国家星火计划项目(2006EA780057)

摘　　要：传统的土地评价方法易受人为因素的限制,探索更科学合理的土地资源评价方法,对土地利用与规划具有重要意义。由于决策树具有分类精度高、分类器可解释性强的优点,特别是C5.0采用了提高决策树分类精度的Boosting技术,提出利用Boosting技术的决策树集成C5.0进行土地评价的方法。采用C5.0算法对广东省土地资源进行了评价,对不使用Boosting的决策树和使用Boosting决策树集成的评价结果进行了分析和比较。研究结果表明利用决策树进行土地质量评价能够得到较高的评价精度,且Boosting决策树集成的土地评价精度高于不使用Boosting的决策树的精度。Traditional land evaluation methods are more liable to be restricted with human elements. It is significant to investigate more scientific and reasonable land evaluation methods for land use and planning. Because decision tree has the characteristics of high accuracy and intelligibility, and especially C5.0 uses Boosting technique to improve classification accuracy, land evaluation using C5.0 with the function to build Boosting decision tree ensembles was conducted. Moreover, C5.0 was used to evaluate the land resources of Guangdong Province, and the results using decision tree with and without Boosting were analyzed and compared. The experimental results demonstrate that C5.0 can be used to evaluate land resources accurately, and the land evaluation accuracy of decision tree without Boosting was lower than that of the decision tree ensemble with Boosting.

关 键 词：土地评价 决策树集成 Boosting技术 评价规则 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] S159.2[自动化与计算机技术—控制科学与工程]