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

This paper presents the results obtained by using software in the public domain that, through Data Mining and Neural Networks with Bayesian training, can lay the foundation to select the most appropriate natural inflow forecast used in the PREVIVAZ stochastic modeling system. This technique utilizes forecast and observed information on precipitation, as well as natural inflow data recorded over the weeks that precede the actual forecast target for the Foz do Areia and Salto Santiago hydroelectric plants located in the Iguaçu River Basin. The results obtained indicate that the using these tools can provide a simple and efficient solution to reduce natural inflow forecast errors on a weekly forecast basis for the Iguaçu River Basin

rbrh

Aplicação das Técnicas de Mineração de Dados como Complemento às Previsões Estocásticas Univariadas de Vazão Natural: Estudo de Caso para a Bacia do Rio Iguaçu