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

Extreme Learning Machine (ELM) and its variants have been gaining attention due to high training speed, ease of implementation and minimal human intervention comparing to classical iterative training algorithms for feedforward networks. In this paper is proposed a variant of ELM in which the input vectors are transformed in vectors with high dimensionality by a non -linear map, and the hidden layer weights and biases are analytically calculated for the maximum extraction of information of the data resulting of the non-linear map. The experiments carried out have shown that the proposed variant, properly designed, can outperform conventional ELM in certain applications.

Variante de Extreme Learning Machine com Mapa Não Linear Adicional e Cálculo Analítico dos Parâmetros da Camada Oculta