[1]陈应生,李进金.动态多尺度决策信息系统局部最优尺度的更新规律[J].华侨大学学报(自然科学版),2024,45(6):800-807.[doi:10.11830/ISSN.1000-5013.202306028]
 CHEN Yingsheng,LI Jinjin.Updating Law of Local Optimal Scale of Dynamic Multi-Scale Decision Information System[J].Journal of Huaqiao University(Natural Science),2024,45(6):800-807.[doi:10.11830/ISSN.1000-5013.202306028]
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动态多尺度决策信息系统局部最优尺度的更新规律()
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《华侨大学学报(自然科学版)》[ISSN:1000-5013/CN:35-1079/N]

卷:
第45卷
期数:
2024年第6期
页码:
800-807
栏目:
出版日期:
2024-11-15

文章信息/Info

Title:
Updating Law of Local Optimal Scale of Dynamic Multi-Scale Decision Information System
文章编号:
1000-5013(2024)06-0800-08
作者:
陈应生1 李进金12
1. 华侨大学 数学科学学院, 福建 泉州 362021;2. 闽南师范大学 数学与统计学院, 福建 漳州 363000
Author(s):
CHEN Yingsheng1 LI Jinjin12
1. School of Mathematical Sciences, Huaqiao University, Quanzhou 362021, China; 2. School of Mathematics Sciences and Statistics, Minnan Normal University, Zhangzhou 363000, China
关键词:
粒计算 多尺度决策信息系统 局部最优尺度选择 不确定性 动态更新
Keywords:
granular computing multi-scale decision information system local optimal scale selection uncertainty dynamic update
分类号:
TP18
DOI:
10.11830/ISSN.1000-5013.202306028
文献标志码:
A
摘要:
在对象动态增加的情况下,对多尺度决策信息系统(MDIS)保持局部决策类不确定性的最优尺度更新规律进行研究。首先,介绍决策信息系统和多尺度决策信息系统决策类不确定性的基本知识,以及MDIS保持局部决策类不确定性的最优尺度定义。然后,在增加一个对象的条件下,分析MDIS局部决策类不确定性的更新规律。最后,采用增量学习方法,给出增加一个对象条件下MDIS局部最优尺度不变和变大的充分必要条件。结果表明:文中方法可以快速地确定更新系统局部最优尺度。
Abstract:
Research on the updating law of optimal scale of multi-scale decision information system(MDIS)to keep local decision class uncertainty under the condition of dynamic increase of objects. Firstly, the basic knowledge of decision class uncertainty of decision information system and multi-scale decision information system are introduced, and the definition of optimal scale of MDIS to keep local decision class uncertainty is given. Then, the updating law of local decision class uncertainty of MDIS is analyzed under the condition of adding one object. Finally, using the incremental learning method, the sufficient and necessary conditions are given for the local optimal scale of MDIS to remain invariant or increase under the condition of adding an object. The results show that the proposed method can quickly determine the local optimal scale of the update system.

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备注/Memo

备注/Memo:
收稿日期: 2023-06-28
通信作者: 李进金(1960-),男,教授,博士,博士生导师,主要从事一般拓扑学与不确定性分析的研究。E-mail:jinjinlimnu@126.com。
基金项目: 国家自然科学基金资助项目(12271191, 11871259); 福建省自然科学基金资助项目(2022J01306)https://hdxb.hqu.edu.cn/
更新日期/Last Update: 2024-11-20