|本期目录/Table of Contents|

[1]高胜国,翁海腾,朱忠礼.贝叶斯最大熵及其在地球科学领域的应用进展[J].江苏农业科学,2017,45(18):11-16.
 Gao Shengguo,et al.Bayesian maximum entropy and its application in earth science:a review[J].Jiangsu Agricultural Sciences,2017,45(18):11-16.
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贝叶斯最大熵及其在地球科学领域的应用进展(PDF)
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《江苏农业科学》[ISSN:1002-1302/CN:32-1214/S]

卷:
第45卷
期数:
2017年18期
页码:
11-16
栏目:
专论与综述
出版日期:
2017-09-20

文章信息/Info

Title:
Bayesian maximum entropy and its application in earth science:a review
作者:
高胜国1 翁海腾2 朱忠礼2
1.北京师范大学环境学院,北京 100875; 2.北京师范大学地理学与遥感科学学院/遥感科学国家重点实验室,北京 100875
Author(s):
Gao Shengguoet al
关键词:
贝叶斯最大熵地统计学时空估计软数据硬数据
Keywords:
-
分类号:
S127;S11+9
DOI:
-
文献标志码:
A
摘要:
贝叶斯最大熵方法(bayesian maximum entropy,简称BME)是现代时空地统计学的重要组成部分。该方法采用统计学中的贝叶斯理论和信息论中熵的概念来认识和处理时空变量,可以将所研究时空要素的软数据和硬数据系统合理地综合到对该要素的空间估计和分析制图过程中。本文首先结构化梳理贝叶斯最大熵方法的原理,对理论较深奥、公式较复杂的贝叶斯最大熵方法及该方法的特点加以概括,同时归纳与总结贝叶斯最大熵方法在地球科学领域内多个方向的应用研究进展,最后对该方法及其应用作总结与展望。经国内外学者多年的研究和实践,贝叶斯最大熵方法已被证明在地球科学领域有着更广阔的应用前景。
Abstract:
-

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备注/Memo

备注/Memo:
收稿日期:2016-04-19
基金项目:国家自然科学基金(编号:91125002、41531174)。
作者简介:高胜国(1986—),男,山西忻州人,博士,讲师,研究方向为定量遥感、农业统计遥感。E-mail:cugbgaoshengguo@126.com。
通信作者:朱忠礼,博士,副教授,研究方向为遥感水文。E-mail:zhuzl@bnu.edu.cn。
更新日期/Last Update: 2017-09-20