地理学报 ›› 2002, Vol. 57 ›› Issue (2): 151-158.doi: 10.11821/xb200202004

• 地理信息科学 • 上一篇    下一篇

地理案例推理及其应

杜云艳1, 周成虎1, 邵全琴1, 苏奋振1, 史忠植2, 叶施仁2   

  1. 1. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室, 北京 100101;
    2. 中国科学院计算技术研究所, 北京 100081
  • 收稿日期:2001-06-04 修回日期:2001-09-26 出版日期:2002-03-25 发布日期:2010-09-06
  • 作者简介:杜云艳(1973- ),女, 主要从事海洋遥感和海洋GIS 研究。E-mail:duyy@lreis.ac.cn
  • 基金资助:

    国家863计划(818-11-03)

Theoretic and Application Research of Geo-Case Based Reasoning

DU Yun-yan11, ZHOU Cheng-hu1, SHAO Quan-qin1, SU Fen-zhen1, SHI Zhong-zhi2, YE Shi-ren2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Institute of Artificial Intelligent, Institute of Computing, CAS, Beijing 100081, China
  • Received:2001-06-04 Revised:2001-09-26 Online:2002-03-25 Published:2010-09-06
  • Supported by:

    The National 863 Project of China, No.818-11-03

摘要:

由于案例推理接近于人类认识、解决问题最原始的思维方式,具有在无法获取机理模型、确定规则或统计模型时,采用简单的历史相似性实现问题的定量求解和预测的特点,成为当前人工智能中备受关注的领域。在讨论案例推理方法发展的基础上,探讨应用案例推理进行地学问题求解的具体方法。从地学数据分析的角度提出了地理案例推理,并结合地理案例的特点,具体讨论了地理案例的表达模型和推理模型,最后结合东海中心渔场预报的实际工作,给出这种方法的具体应用实例。

关键词: 人工智能, 地理案例推理, 表达模型, 推理模型, 东海中心渔场

Abstract:

As an emerging branch of AI, Case-Based Reasoning (CBR) has the inborn ability of quantitative interpretation and prediction simply based on similarity of historical events even there is difficulty to get the working mechanism, principles, or build statistical models for those complex systems. Since it is a perfect model of human recognition and its working mechanism is very similar to the human primitive reasoning logic, the introduction of CBR to geographical system (Geo-case Based Reasoning) study to solve the problem of quantitative prediction was promoted. With tracking the front of international CBR research, expression and reasoning models of CBR have been promoted. And application of CBR model and method to specific geographical phenomenon has been fully discussed as well. The content of this paper can be summarized in the following aspects: (1) GeoCBR has been posed from the view of geographic case study. Furthermore, principle difference between GeoCBR and general CBR has been explored. (2) A comprehensive expression model for geographic case based reasoning has been established based on Tesseral model. (3) Geo-case based reasoning model was built in case of having fuzzy spatial-temporal distribution, a special FMP was used to calculate similarity of Geo-cases, and then reasoning model was given based on it. (4) With such a theoretical framework of Geo-CBR, a fishing ground prediction model, which can be regarded as a sample of Geo-CBR, has been built. This model has been applied to the East China Sea fishing center prediction. The validation result is satisfying.

Key words: artificial intelligent, Geo Case-Based Reasoning, representation model of Case-Based Reasoning, reasoning model, spatio-temporal distribution pattern