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

This survey focuses on the current problems in Earth systems science wheremachine learning algorithms can be applied. It provides an overview of previouswork, ongoing work at the Ministry of Earth Sciences, Gov. of India, and futureapplications of ML algorithms to some significant earth science problems. Weprovide a comparison of previous work with this survey, a mind map ofmultidimensional areas related to machine learning and a Gartner's hype cyclefor machine learning in Earth system science (ESS). We mainly focus on thecritical components in Earth Sciences, including atmospheric, Ocean,Seismology, and biosphere, and cover AI/ML applications to statisticaldownscaling and forecasting problems.

Machine learning for Earth System Science (ESS): A survey, status and future directions for South Asia