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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Problem statement: Accurate weather forecasting plays a vital role for planning day to day&#13; activities. Neural network has been use in numerous meteorological applications including weather&#13; forecasting. Approach: A neural network model has been developed for weather forecasting, based on&#13; various factors obtained from meteorological experts. This study evaluates the performance of Radial&#13; Basis Function (RBF) with Back Propagation (BPN) neural network. The back propagation neural&#13; network and radial basis function neural network were used to test the performance in order to&#13; investigate effective forecasting technique. Results: The prediction accuracy of RBF was 88.49%.&#13; Conclusion: The results indicate that proposed radial basis function neural network is better than back&#13; propagation neural network

An Efficient Weather Forecasting System using Radial Basis Function Neural Network