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/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

The power system reliability is an important index to evaluate the ability of power supply. According to thecharacteristics of the practical grid operation, this paper trains and sets up power grid reliability predicting model,based on relevance vector machine, taking the load supplying capacity of power grid and natural calamities asinput variables, and the outage time of power grid failure affecting the reliability of the power supply as outputvariables. In the modeling process, through principal component analysis of the training sample set of relevancevector machine, the input factor number of sample is improved, the input number of network is reduced, thenetwork structure is simplified, and the predicting accuracy is increased. Simulation results are provided to verifythe effectiveness of the proposed algorithm, which show that it provides a new way for power system reliabilitypredicting.

A Novel Power System Reliability Predicting Model Based on PCA and RVM