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计算机工程 ›› 2012, Vol. 38 ›› Issue (14): 287-289. doi: 10.3969/j.issn.1000-3428.2012.14.085

• 开发研究与设计技术 • 上一篇    下一篇

农业领域本体概念的云化方法研究

叶 琼,李绍稳,张友华,刘 恺   

  1. (安徽农业大学信息与计算机学院农业信息学安徽省重点实验室,合肥 230036)
  • 收稿日期:2011-12-13 出版日期:2012-07-20 发布日期:2012-07-20
  • 作者简介:叶 琼(1987-),女,硕士研究生,主研方向:人工智能,云模型;李绍稳,教授、博士生导师;张友华,教授;刘 恺,硕士研究生
  • 基金资助:
    国家自然科学基金资助项目(30800663, 30971691);国家“十一五”科技支撑计划基金资助重点项目(2009BADC4B02, 20 09BADA6B02)

Research on Cloudization Method of Agriculture Domain Ontology Concept

YE Qiong, LI Shao-wen, ZHANG You-hua, LIU Kai   

  1. (Anhui Provincial Key Laboratory of Agricultural Informatics, School of Information & Computer, Anhui Agricultural University, Hefei 230036, China)
  • Received:2011-12-13 Online:2012-07-20 Published:2012-07-20

摘要: 农业领域本体知识中存在许多模糊概念不能用现有本体语言表示。为此,运用云模型,提出一种农业本体知识中概念的云化方法。设计农业领域概念的提取方法、划分方法及云化方法,并通过实例验证云化方法的有效性。实验结果表明,该方法以云图的形式代替具体确定的数值,能表示不确定的概念,体现出数据的随机性和概念的模糊性,有助于表现农业知识的客观性。

关键词: 农业领域本体, 不确定性, 云模型, 云发生器, 云化

Abstract: In agriculture domain ontology knowledge, many fuzzy concept can not use the existing ontology language to express. This paper proposes a kind of method for cloudization of the concepts in agricultural ontology knowlegde through the use of cloud model. It designs the extraction method, partition method and cloudization method, demonstrates the effectiveness of this approch through the instances. Experimental results show that this method not only can replace specific quantitative values with the form of cloud chart which express uncertain concepts, but also can embody the randomness of the data and fuzziness of the concepts, which helps to reflect the objectivity of the agricultural knowledge.

Key words: agriculture domain ontology, uncertainty, cloud model, Cloud Generator(CG), cloudization

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