English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper, for determining recognition target class problem in inaccurate or imprecise environments, we designed triangular fuzzy number pattern recognition algorithm based on closeness degree. Firstly, the attribute values of each standard test set and the sample set are converted into triangular fuzzy numbers. Secondly, the EW-type closeness formula is used to calculate closeness degree between the attributes of each standard set and sample set, and establish the relative closeness degree matrix. Thirdly, the target identification of class model is determined based on the relative closeness degree matrix. By identifying 20 kinds of perfume test data sets with the tag to verify the validity and rationality of the proposed algorithm. Keywords—EW-type closeness degree; triangular fuzzy numbers; relative approach degree; pattern recognition

Pattern Recognition Algorithm Based on Closeness Degree of Triangle Fuzzy Number