Research on adaptive conversion of AI language based on rough set

被引：0
作者：
Fang, Yuping [1 ]
Fang, Da [2 ]
机构：
[1] Yunnan Normal Univ, Coll Vocat & Tech Educ, Kunming 653000, Yunnan, Peoples R China
[2] Yunnan Normal Univ, Progaganda Dept, Kunming 653000, Yunnan, Peoples R China
来源：
INTERNATIONAL JOURNAL OF BIOMETRICS | 2022年 / 14卷 / 3-4期
关键词：
rough set; AI language; adaptive conversion; feature selection; redundant information deleting;
D O I：
10.1504/IJBM.2022.124672
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In order to solve the problems of high complexity and low computational efficiency in traditional artificial intelligence (AI) language conversion methods, an adaptive AI language conversion method based on rough set is proposed. AI language preprocessing is realised by pre-emphasising, adding window, frame processing and endpoint detection. The attribute reduction algorithm based on rough set theory is used to select the features of AI language. The dimension of input feature vector is reduced. The experimental results show that after feature extraction, the computational efficiency is obviously improved, and the efficiency of the proposed method is the highest, averaging close to 100%. Compared with the traditional method, the complexity of the proposed method is lower, and the average complexity is 1.68% during the ten experimental iterations. This method simplifies the adaptive conversion process of AI language and has high computational efficiency.
引用
收藏
页码：285 / 302
页数：18
相关论文
共 50 条
[41]   Research on the Rough Set Attribute Reduction Algorithm Based on Significance of Attributes [J].
Chen, Rongbao ;
Ma, Wuyong ;
Xiao, Benxian ;
Cao, Zipei .
2016 UKACC 11TH INTERNATIONAL CONFERENCE ON CONTROL (CONTROL), 2016,
[42]   Research on Fault Diagnosis Method Based on CBR and Rough Set Theory [J].
Yuan, Chun-fei ;
Cai, Jing ;
Xu, Yi-ming .
PROGRESS IN CIVIL ENGINEERING, PTS 1-4, 2012, 170-173 :3644-+
[43]   Research of Customer Classification Based on Rough Set Using Rosetta Software [J].
Shen, Liangzhong ;
Chen, Shenkai .
PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE ON COMMUNICATION, ELECTRONICS AND AUTOMATION ENGINEERING, 2013, 181 :837-843
[44]   The Research on Mobile TV Customer Satisfaction Degree Based on Rough Set [J].
Liang, Zhengli ;
Wu, Jian ;
Yu, Keyao .
2015 8TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1, 2015, :340-345
[45]   Research of Component Integration Knowledge Acquirement Method Based on Rough Set [J].
Xue Junfang ;
Wan Yuntao ;
Zheng Lei .
PROCEEDINGS OF THE 2015 4TH INTERNATIONAL CONFERENCE ON SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, 2016, 43 :171-176
[46]   The research of object selection method based on rough set in map generalization [J].
Li, Wenjing ;
Long, Yi ;
Lin, Zhiyong .
GEOINFORMATICS 2007: CARTOGRAPHIC THEORY AND MODELS, 2007, 6751
[47]   Research on Supply Chain Performance Evaluation Based on Rough set and SVM [J].
Yuan, Xiu-e ;
Shi, Meng-wei ;
Song, Chun-mei .
IEEC 2009: FIRST INTERNATIONAL SYMPOSIUM ON INFORMATION ENGINEERING AND ELECTRONIC COMMERCE, PROCEEDINGS, 2009, :276-+
[48]   Research on Improved Weighted Fuzzy Clustering Algorithm Based on Rough Set [J].
Li Jian-guo ;
Gao Jing-wei .
2009 INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND TECHNOLOGY, VOL II, PROCEEDINGS, 2009, :98-+
[49]   One Research of Clustering Algorithm Based on Rough Set and Genetic Algorithm [J].
Wei, Haixin ;
Li, Xiuqing .
PROCEEDINGS OF 2012 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2012), 2012, :1643-1646
[50]   Research on Customer Value' Data Mining Model Based on Rough Set [J].
He, Weihong ;
Zhong, Jiaming ;
Liu, Zhihui .
2009 INTERNATIONAL CONFERENCE ON E-BUSINESS AND INFORMATION SYSTEM SECURITY, VOLS 1 AND 2, 2009, :490-+
12345