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Pattern Recognition and Artificial Intelligence  2022, Vol. 35 Issue (9): 816-826    DOI: 10.16451/j.cnki.issn1003-6059.202209005
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Concept-Cognitive Learning Model Based on Decision Significance
WANG Qijun1, LIN Yidong1, LIN Menglei1,2, KOU Yi1
1. School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000;
2. Institute of Meteorological Big Data-Digital Fujian, Minnan Normal University, Zhangzhou 363000

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Abstract  

Concept-cognitive learning is a concept learning method that simulates human cognitive process based on formal concept analysis. Most of the current concept-cognitive learning methods only consider conceptual similarity and ignore the influence of prior decision information, resulting in the loss of practical details. To solve this problem, a concept-cognitive learning model based on decision significance is put forward for concept classification in a dynamic environment by extracting prior decision information to describe the significance of decision making. The neighborhood granule is constructed by cosine similarity, and the progressive process of concept cognition is discussed. For the dynamic environment, the decision significance and confidence degree are proposed to design the computational method of concept classification with the consideration of the validity of the a priori decision information. The effectiveness and superiority of the proposed method are verified by simulation experiments.

Key wordsConcept-Cognitive Learning      Fuzzy Concept      Decision Significance      Progressive Fuzzy Concept     
Received: 27 July 2022     
ZTFLH: TP 182  
Fund:

Supported by National Natural Science Foundation of China(No.12201284), Natural Science Foundation of Fujian Province(No.2022J05169,B12127), President Foundation of Minnan Normal University(No.L22130)

Corresponding Authors: LIN Menglei, master, professor. His research interests include uncertain theories and application.   
About author:: WANG Qijun, master student. Her research interests include granular computing and concept-cognitive learning. LIN Yidong, Ph.D., associate professor. His research interests include uncertain theories and application. KOU Yi, master student. His research interests include granular computing and machine learning.
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WANG Qijun
LIN Yidong
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KOU Yi
Cite this article:   
WANG Qijun,LIN Yidong,LIN Menglei等. Concept-Cognitive Learning Model Based on Decision Significance[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(9): 816-826.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202209005      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I9/816
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