Granular Computing Models for Knowledge Uncertainty

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 知识不确定性问题的粒计算模型 DOI: 10.3724/SP.J.1001.2011.03954 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(61073146); 重庆市自然科学基金(2008BA2017); 重庆市杰出青年科学基金(2008BA2041) Granular Computing Models for Knowledge Uncertainty Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:知识不仅是构成人类认知能力的重要基石,也是智能科学研究的基础问题之一.随着智能科学技术研究的发展,知识的不确定性研究受到人们的普遍关注.知识的不确定性来源于知识本身的不确定性以及受外界(客观世界)影响而导致的不确定性.从粒计算模型的角度分析了模糊集理论模型、粗糙集理论模型、商空间理论模型以及其他扩展粒计算模型中知识的不确定性问题,并对知识不确定性问题的研究工作进行了讨论和总结,对有待研究的重要问题进行了展望. Abstract:Knowledge is not only an important cornerstone that constructs the cognitive ability in human beings, but is also one of the basic issues in intelligence science. With the development of intelligence science and technology, the study of knowledge uncertainty is attracting more and more attention. Knowledge uncertainty includes the inherent uncertainty of knowledge itself and the effect of external influence on knowledge. In the view of granular computing (GrC), the knowledge uncertainties of the fuzzy set theory model, the rough set theory model, the quotient space theory model, and some other related granular computing models are studied in this paper. The state-of-the-art and key issues of knowledge uncertainty are discussed. 参考文献 相似文献 引证文献