[1]徐健锋,何宇凡,汤涛,等.概率粗糙集三支决策在线快速计算算法研究[J].智能系统学报,2018,13(05):741-750.[doi:10.11992/tis.201706047]
 XU Jianfeng,HE Yufan,TANG Tao,et al.Research on a fast online computing algorithm based on three-way decisions with probabilistic rough sets[J].CAAI Transactions on Intelligent Systems,2018,13(05):741-750.[doi:10.11992/tis.201706047]
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概率粗糙集三支决策在线快速计算算法研究(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第13卷
期数:
2018年05期
页码:
741-750
栏目:
出版日期:
2018-09-05

文章信息/Info

Title:
Research on a fast online computing algorithm based on three-way decisions with probabilistic rough sets
作者:
徐健锋12 何宇凡1 汤涛1 赵志宾12
1. 南昌大学 软件工程系, 江西 南昌 330029;
2. 同济大学 计算机科学与技术系, 上海 201804
Author(s):
XU Jianfeng12 HE Yufan1 TANG Tao1 ZHAO Zhibin12
1. Department of Software Engineering, Nanchang University, Nanchang 330029, China;
2. Department of Computer Science and Technology, Tongji University, Shanghai 201804, China
关键词:
三支决策粗糙集条件概率在线计算不确定动态计算粒计算
Keywords:
three-way decisionsrough setsconditional probabilityonline computinguncertaindynamic calculationgranular computing
分类号:
TP181
DOI:
10.11992/tis.201706047
摘要:
随着大数据和物联网技术的不断发展,动态在线计算已经成为了一种常见的计算模式,在动态在线计算中进行不确定问题的推理和求解是一项具有挑战性的新议题。概率粗糙集三支决策理论是一种处理不确定性知识挖掘的有效工具,根据在线计算模式中数据同步增减的动态特点,提出了一种概率粗糙集三支决策的在线计算方法。首先,以内存滑动窗口模式对在线动态计算的数据变化特点进行理论建模;然后,根据上述模型中在线计算的数据变化模式,推导出不同类型数据变化模式下的三支决策条件概率及三支区域的变化规律;最后,提出了一种新型在线快速计算算法,其获取的三支决策规则与经典概率三支决策算法是等效的。通过与经典三支决策计算算法的多组对比实验,验证了提出的在线快速计算算法的高效性与稳定性。
Abstract:
With the continuous development of big data and IoT (Internet of Things), dynamic online computation has become a common computing pattern; however the field of dynamic online computation faces challenges in deducing and solving uncertainty problems. A three-way decision theory with probabilistic rough set method is an efficient tool for mining uncertain knowledge; thus a dynamic online computing approach of three-way decision theory with probabilistic rough set is proposed in this paper, in accordance with the features of data dynamic synchronization. First, a data model is established to describe the inherent features of dynamic online computation via memory sliding window mode. In terms of the variational features of dynamic online computation of the above model, a three-way decision conditional probability and the change rule of three-way area are deduced as diverse variational patterns of data. Finally, a novel algorithm of online rapid computation is proposed. The obtained three-way decision rule is identical with the three-way decision algorithm of classic probability. By comparison with the classic three-way decision algorithm through multiple experiments, the proposed online rapid computation algorithm is confirmed to have high efficiency and stability.

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备注/Memo

备注/Memo:
收稿日期:2017-06-12。
基金项目:国家自然科学基金项目(61763031,61673301);上海市自然科学基金项目(14ZR1442600);江西省研究生创新专项资金项目(YC2016-S053).
作者简介:徐健锋,男,1973年生,副教授,博士研究生,计算机学会会员,主要研究方向为数据挖掘、粗糙集、机器学习。主持国家自然基金项目1项,参与国家自然科学基金项目2项;何宇凡,男,1994年生, 硕士研究生,主要研究方向为三支决策、粗糙集、粒计算、机器学习;汤涛,男,1993年生,硕士研究生,主要研究方向为粗糙集、粒计算、机器学习。
通讯作者:徐健锋.E-mail:jianfeng_x@ncu.edu.cn.
更新日期/Last Update: 2018-10-25