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 view of the low information transmission efficiency and tendency to fall into local optimal solution of the problems of traditional particle swarm optimization (PSO), an improved bidirectional information transmission block factor based multi-population PSO(BFM-PSO) is proposed. We use the improved BFM-PSO algorithm to optimize SVM penalty factor C and the radius s of the radial basis function. Tests In a number of public data sets show that SVM optimized by the improved BFM-PSO can effectively improve the classification accuracy.

Block Factor Based Multi-population PSO and Its Application in SVM