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顾及障碍物的朴素贝叶斯分类法在城镇土地定级中的应用
  • ISSN号:1007-7588
  • 期刊名称:《资源科学》
  • 时间:0
  • 分类:TP311.13[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]武汉大学资源与环境科学学院,武汉430079, [2]香港中文大学地理与资源管理系,香港, [3]香港大学城市规划与设计系,香港, [4]武汉市江岸区一元街办事处,武汉430010
  • 相关基金:国家自然科学基金资助项目(编号:40871179)
中文摘要:

本文以潮州市建成区和近期规划区为研究区,采用训练样本获取先验概率建立朴素贝叶斯分类器,以栅格点为单位,将各栅格点的土地定级因素作用分值作为输入变量,利用朴素贝叶斯分类器进行土地定级。在作用分值确定方法上,采用障碍距离代替传统直线距离,以达到客观反映点、线等要素对城镇土地使用价值作用的程度。最后,对顾及障碍物的朴素贝叶斯定级结果分别与空间聚类结果及未顾及障碍物的定级结果进行比较,结果表明本文所提出的方法在土地定级研究中具有一定的优势,能更加真实地反映城镇土地使用价值的空间分布特征。

英文摘要:

Traditionally,data mining models and spatial clustering methods are employed in the evaluation of urban land gradation.Given the subjectivity of these methods and their lack of artificial intelligence,intelligence models are required.Here,we propose a na ve Bayesian classifier to determine urban land gradation.Chaozhou in Guangdong province was selected as a case study area.First,according to the suggestions of experts and planners the training area of each gradation was selected.Then,the factors for commercial land gradation in Chaozhou were selected on the basis of the characteristic of the area and the‘Regulations for gradation and classification on urban land'.The function values of factors for commercial land were inputted into the model to determine commercial land gradation.To retrieve the obstacle distance,spatial analysis in AcrGIS was used.The advantage of obstacle distance is that it takes the actual distance in the real world into consideration.For example,if there is a mountain or water body between point a and point b in the real world,the obstacle distance between point a and point b will not pass through the impediment but around the obstacle.Oppositely,the Euclidean distance will pass the mountain or water body directly and is unlike real world.Within this context the impact of factors on urban systems is reflected by obstacle distance.Finally,to confirm the fitness our proposed Bayesian model and obstacle distance,a comparison of the result of the Bayesian based commercial land gradation method considering obstacles with the gradation arising from spatial clustering was carried out.This comparison showed that Bayesian methods are beneficial the research in this area,and accurately reflect the distribution of urban land quality.

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期刊信息
  • 《资源科学》
  • 中国科技核心期刊
  • 主管单位:中国科学院
  • 主办单位:中国科学院地理科学与资源研究所
  • 主编:成升魁
  • 地址:北京安定门外大屯路甲11号
  • 邮编:100101
  • 邮箱:zykx@igsnrr.ac.cn
  • 电话:010-64889446
  • 国际标准刊号:ISSN:1007-7588
  • 国内统一刊号:ISSN:11-3868/N
  • 邮发代号:82-4
  • 获奖情况:
  • 国内外数据库收录:
  • 日本日本科学技术振兴机构数据库,中国中国人文社科核心期刊,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:42316