Received date: 2001-06-04
Revised date: 2001-09-26
Online published: 2002-03-25
Supported by
The National 863 Project of China, No.818-11-03
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.
DU Yun-yan1, ZHOU Cheng-hu, SHAO Quan-qin, SU Fen-zhen,SHI Zhong-zhi, YE Shi-ren . Theoretic and Application Research of Geo-Case Based Reasoning[J]. Acta Geographica Sinica, 2002 , 57(2) : 151 -158 . DOI: 10.11821/xb200202004
[1] Shi Zhongzhi. Advanced Artificial Intelligence. Beijing: Science Press, 1998.
[史忠植. 高级人工智能. 北京: 科学出版社, 1998.]
[2] Wu Quanyuan, Liu Jiangning. Artificial Intelligence and Expert System. Beijing: National Defense Science and Technology University Press, 1995.
[吴泉源, 刘江宁. 人工智能与专家系统. 北京: 国防科技大学出版社, 1995.]
[3] Barletta R. An Introduction to Case-based Reasoning. AI Expert, August 1991, 42-49.
[4] Helton T. The Hottest New AI Technology. The Spang Robinson Report on Artificial Intelligence. 1991, 7(8).
[5] Ian Watson, Farhi Marir. Case-based reasoning: a review. Knowledge Engineering Review, 1994, 9(4).
[6] Kolodner J. Case-Based Reasoning. San Mateo: Morgan Kaufmann Publishers, 1993. 1-30.
[7] Zhou Chenghu, Sun Zhanli. The Study on Geo-CA. Beijing: Science Press, 1999.
[周成虎, 孙战利. 地理元胞自动机的模型和应用研究. 北京: 科学出版社, 2000.]
[8] F P Coene. A case base representation technique to support case based reasoning. In: Proceedings of the International Joint Conference on Artificial Intelligence, 1999.
[9] A Holt, G L Benwell. Applying case-based reasoning technique in GIS. IJGIS, 1991, 13(1): 9-25.
[10] E K Burke, B Maccarthy, S Petrovic et al. Structured cases in case-based reasoning: re-using and adapting cases for time-tabling problems. Knowledge-Based Systems, 2000, 13: 159-165.
[11] Asad Khattak, Adib Kanafani. Case-based reasoning, a planning tool for intelligent transportation systems, transportation research, Part C: Emerging Technologies, 1996, 4(5): 267-288.
[12] Coenen F P, Beattie B. Spatio-temporal reasoning using a multi-dimentional Tesseral representation. In: European Conference on Artificial Intelligence '98 (Proceedings of ECAI '98), 1998. 140-144.
[13] Wang Guojun. 3I method and range value fuzzy reasoning. Science in China (Series E), 2000, 30(4): 331-340.
[王国俊. 三I方法与区间值模糊推理. 中国科学 (E辑), 2000, 30(4): 331-340.]
/
| 〈 |
|
〉 |