By Ashok N. Srivastava,Ramakrishna Nemani,Karsten Steinhaeuser
From the Foreword:
"While large-scale desktop studying and knowledge mining have significantly impacted quite a number advertisement purposes, their use within the box of Earth sciences continues to be within the early phases. This publication, edited via Ashok
Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as a very good source for someone drawn to the possibilities and demanding situations for the computer studying neighborhood in interpreting those info units to reply to questions of pressing societal interest…I desire that this publication will motivate extra machine scientists to target environmental purposes, and Earth scientists to hunt collaborations with researchers in laptop studying and knowledge mining to improve the frontiers in Earth sciences."
--Vipin Kumar, collage of Minnesota
Large-Scale desktop studying within the Earth Sciences presents researchers and practitioners with a huge review of a few of the major demanding situations within the intersection of Earth technological know-how, computing device technology, data, and similar fields. It explores a variety of issues and gives a compilation of modern examine within the software of laptop studying within the box of Earth Science.
Making predictions in line with observational facts is a topic of the publication, and the ebook comprises chapters at the use of community technology to appreciate and notice teleconnections in severe weather and climate occasions, in addition to utilizing established estimation in excessive dimensions. using ensemble desktop studying types to mix predictions of worldwide weather versions utilizing details from spatial and temporal styles can be explored.
The moment a part of the booklet encompasses a dialogue on statistical downscaling in weather with cutting-edge scalable computer studying, in addition to an outline of how you can comprehend and are expecting the proliferation of organic species because of adjustments in environmental stipulations. the matter of utilizing large-scale laptop studying to check the formation of tornadoes can be explored in depth.
The final a part of the publication covers using deep studying algorithms to categorise pictures that experience very excessive solution, in addition to the unmixing of spectral indications in distant sensing photographs of land disguise. The authors additionally practice long-tail distributions to geoscience assets, within the ultimate bankruptcy of the book.
Read or Download Large-Scale Machine Learning in the Earth Sciences (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) PDF
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Extra resources for Large-Scale Machine Learning in the Earth Sciences (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Large-Scale Machine Learning in the Earth Sciences (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) by Ashok N. Srivastava,Ramakrishna Nemani,Karsten Steinhaeuser