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 the existing techniques of Artificial Intelligence, two Artificial Neural Networks (ANN) were selected and adapted to fit one of the elements that define a Non-Uniform Rational B-Spline (NURBS) and thus obtaining an appropriate modeling of the NURBS. The selected elements were the checkpoints. The ANN used were the Radial Basis Function and the Kohonen model or Self-Organizing Maps. Based on the analysis of the results and characterization of the ANN the Radial Basis Function had a more appropriate and optimum performance for a large number of data, which is a disadvantage of the Self-Organizing Maps. In this model, additional processes must be done to determine the winning neuron and the weights must be refitted.

Una Técnica de Inteligencia Artificial para el Ajuste de uno de los Elementos que Definen una B-Spline Racional No Uniforme (NURBS)