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 communication fault analysis, mining history alarm data to acquire correlation knowledge has become an inevitable trend. Owing to low efficiency of traditional alarm preprocessing methods, a new preprocessing optimization method is proposed. The quality of alarm sequence partition is evaluated by difference alarm time segment using sliding time window, and the optimal partition based on double constraint and K-average is introduce to extract the alarm transactions by sliding time window so as to acquire better preprocessing results. The performance simulation indicates that this method has higher preprocessing efficiency of alarm sequence and overcomes the problem that the traditional methods are not fully applicable to the alarm sequence, which provides support for the analysis of the follow-up alarm data.

A Data Preprocessing Optimization Method based on Sliding Time Window in Communication Alarm Events