计算机应用 ›› 2013, Vol. 33 ›› Issue (03): 771-775.DOI: 10.3724/SP.J.1087.2013.00771

• 人工智能 • 上一篇    下一篇

基于Jena的台风灾害领域本体模型推理

黄风华1,2*, 晏路明2   

  1. 1.福州大学 阳光学院, 福州 350015;
    2.福建师范大学 地理科学学院, 福州 350007
  • 收稿日期:2012-10-08 修回日期:2012-11-01 出版日期:2013-03-01 发布日期:2013-03-01
  • 通讯作者: 黄风华
  • 作者简介:黄风华(1982-),男,福建莆田人,讲师,博士研究生,主要研究方向:数据挖掘、遥感、地理信息系统; 晏路明(1951-),男,湖南浏阳人,教授,博士生导师,主要研究方向:自然地理、遥感、地理信息系统。
  • 基金资助:

    国家社会科学基金资助项目(03BTJ004); 福建省教育厅科技项目(JB11245)。

Reasoning of ontology model for typhoon disasters domain based on Jena

HUANG Fenghua1,2*, YAN Luming2   

  1. 1.Sunshine College, Fuzhou University, Fuzhou Fujian 350015, China;
    2.College of Geographical Sciences, Fujian Normal University, Fuzhou Fujian 350007, China
  • Received:2012-10-08 Revised:2012-11-01 Online:2013-03-01 Published:2013-03-01
  • Contact: Fenghua Huang

摘要: 针对传统台风灾害预测以统计学方法为主,而缺乏语义驱动和智能推理的问题,提出一种基于Jena的台风灾害领域本体模型推理机制。首先,在分析台风灾害的影响因素和演变历史的基础上,采用网络本体语言(OWL)建立台风灾害领域本体模型; 其次,利用Jena推理引擎和自定义规则对台风灾害本体模型进行推理,挖掘被隐藏的台风灾害影响因素或灾害链信息; 最后,构建了本体驱动的台风灾害专家系统(Onto-TDES)。实验结果证明,该方案能初步解决传统台风灾害预测缺乏语义驱动和智能推理的问题,提高台风灾害管理与预测的智能化水平。

关键词: 本体建模, 语义网络, 台风灾害, 专家系统

Abstract: Some problems exist in the traditional typhoon disasters prediction, such as depending mainly on statistical methods, lack of semantic-driven processes and intelligent reasoning. In order to solve these problems, a reasoning mechanism of the ontology model of typhoon disasters domain based on Jena was proposed. Firstly, the ontology model of typhoon disasters domain expressed by Web Ontology Language (OWL) was built based on analyzing the impact factors and evolution history of the typhoon disasters fully. Secondly, the Jena reasoning engine and custom rules were used for the reasoning of typhoon disasters ontology model and mining the hidden impact factors of typhoon disasters or the information of disaster chains. Finally, an Ontology-driven Typhoon Disasters Expert System (Onto-TDES) was built. The experimental results show that the mechanism can solve the lack of semantic-driven processes and intelligent reasoning preliminarily, and improve the intelligent level of the management and prediction of the typhoon disasters.

Key words: ontology modeling, semantic network, typhoon disaster, expert system

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