| Title |
Incremental Attribute Reduction Algorithm for Smart City Local Area Communication Systems Based on Similarity Relation |
| ID_Doc |
41951 |
| Authors |
Jing, L |
| Title |
Incremental Attribute Reduction Algorithm for Smart City Local Area Communication Systems Based on Similarity Relation |
| Year |
2023 |
| Published |
Journal Of Testing And Evaluation, 51, 3 |
| DOI |
10.1520/JTE20220086 |
| Abstract |
The wide application of local area communication system brings comprehensive data informa-tion but also increases the difficulty of data mining and analysis. Therefore, the data mining preprocessing link-attribute reduction is studied. The research is divided into three parts: first, the method of distinguished matrix fast calculating is used for discerning the core attributes of a data set; second, the k-nearest neighbor algorithm is used to calculate the attribute as well as the similarity coefficient between condition attributes, and to finish at the beginning of attribute reduction; and third, the global optimization ability of particle swarm algorithm im-plementation attribute reduction is used again to complete local area communication system incremental attribute reduction targets. The results show that compared with the three pre-vious reduction algorithms, the proposed algorithm has the least number of attributes and the least number of iterations, which proves the reduction degree and efficiency of the proposed method. |
| Author Keywords |
similarity relation; local area communication system; attribute reduction; particle swarm; optimization; k-nearest neighbor algorithm |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000883083500001 |
| WoS Category |
Materials Science, Characterization & Testing |
| Research Area |
Materials Science |
| PDF |
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