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

Evolutionary algorithms (EAs) provide unique advantages for optimizing neuralnetworks in complex search spaces. This paper introduces a new web platform,NeuroEvo (neuroevo.io), that allows users to interactively design and trainneural network classifiers using evolutionary and particle swarm algorithms.The classification problem and training data are provided by the user and, uponcompletion of the training process, the best classifier is made available todownload and implement in Python, Java, and JavaScript. NeuroEvo is acloud-based application that leverages GPU parallelization to improve the speedwith which the independent evolutionary steps, such as mutation, crossover, andfitness evaluation, are executed across the population. This paper outlines thetraining algorithms and opportunities for users to specify design decisions andhyperparameter settings. The algorithms described in this paper are also madeavailable as a Python package, neuroevo (PyPI:https://pypi.org/project/neuroevo/).

NeuroEvo: A Cloud-based Platform for Automated Design and Training of Neural Networks using Evolutionary and Particle Swarm Algorithms