Large-Scale Machine Learning in the Earth Sciences

Name: Large-Scale Machine Learning in the Earth Sciences
Author: Ashok N. Srivastava (u. a.)
ISBN: 9781498703871

Ashok N. Srivastava (u. a.)

Language: English

Published by Chapman and Hall/CRC, 2017

1498703879 / 9781498703871

Series: Book 45 of 56 - Chapman & Hall/CRC Data Mining and Knowledge Discovery

Hardcover
New

See all details

Seller: preigu, Osnabrück, Germanypreigu

5-star seller

AbeBooks seller since August 5, 2024

View this seller's items

Hardcover

Condition: New

£ 207.14

£ 59.99 shipping

Ships from Germany to U.S.A.

Quantity: 5 available

Add to basket

Save for laterCreate a Want for similar items

Item description from seller

Seller Inventory # 109463900

Contact seller about this item

Report this item

Title: Large-Scale Machine Learning in the Earth Sciences
Author: Ashok N. Srivastava (u. a.)
Publisher: Chapman and Hall/CRC
Publication year: 2017
Condition: Neu
Binding: Buch
Language: English
ISBN 10: 1498703879
ISBN 13: 9781498703871
Item weight: 650 grams
Dimensions: 260 x 183 x 17 mm
Series: Book 45 of 56: Chapman & Hall/CRC Data Mining and Knowledge Discovery
Seller catalogs: Bücher

From the Foreword:

"While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok

Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest…I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences."

--Vipin Kumar, University of Minnesota

Large-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science.

Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored.

The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth.

The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book.

"Synopsis" may belong to another edition of this title.

About the Author

Ashok N. Srivastava, Ph.D. is the VP of Data and Artificial Intelligence Systems and the Chief Data Scientist at Verizon. He leads a new research and development center in Palo Alto focusing on building products and technologies powered by big data, large-scale machine learning, and analytics. He is an Adjunct Professor at Stanford University in the Electrical Engineering Department and is the Editor-in-Chief of the AIAA Journal of Aerospace Information Systems. Dr. Srivastava is a Fellow of the IEEE, the American Association for the Advancement of Science (AAAS), and the American Institute of Aeronautics and Astronautics (AIAA).

He is the author of over 100 research articles, has edited 4 books, has 5 patents awarded, and over 30 under file. He has won numerous awards including the IEEE Computer Society Technical Achievement Award for "pioneering contributions to intelligent information systems," the NASA Exceptional Achievement Medal for contributions to state-of-the-art data mining and analysis, the NASA Honor Award for Outstanding Leadership, the NASA Distinguished Performance Award, several NASA Group Achievement Awards, the Distinguished Engineering Alumni Award from UC Boulder, the IBM Golden Circle Award, and the Department of Education Merit Fellowship.

Dr. Ramakrishna Nemani is a senior Earth scientist with the NASA Advanced Supercomputing division at Ames Research Center, California, USA. He leads NASA's efforts in ecological forecasting to understand the impacts of the impending climatic changes on Earth’s ecosystems and in collaborative computing, bringing scientists together with big data and supercomputing to provide insights into how our planet is changing and the forces underlying such changes.

He has published over 190 papers on a variety of topics including remote sensing, global ecology, ecological forecasting, climatology and scientific computing with over 28000 citations. He served on the science teams of several missions including Landsat-8, NPP, EOS/MODIS, ALOS-2 and GCOM-C. He has received numerous awards from NASA including the exceptional scientific achievement medal in 2008, exceptional achievement medal in 2011, outstanding leadership medal in 2012 and eight group achievement awards.

Karsten Steinhaeuser, Ph.D. is a Research Scientist affiliated with the Department of Computer Science & Engineering at the University of Minnesota and a Data Scientist with Progeny Systems Corporation. His research centers around data mining and machine learning, in particular construction and analysis of complex networks, with applications in diverse domains including climate, ecology, social networks, time series analysis, and computer vision. He is actively involved in shaping an emerging research area called climate informatics, which lies at the intersection of computer science and climate sciences, and his interests are more generally in interdisciplinary research and scientific problems relating to climate and sustainability.

Dr. Steinhaeuser has been awarded one patent and has authored several book chapters as well as numerous peer reviewed articles and papers on these topics. His work has been recognized with multiple awards including two Oak Ridge National Laboratory Significant Event Awards for "Novel Analyses of the Simulation Results from the CCSM 3.0 Climate Model" and "Science Support for a Climate Change War Game and Follow-Up Support to the US Department of Defense."

"About the title" may belong to another edition of this title.

preigu

Osnabrück, Germany

5-star seller

AbeBooks seller since August 5, 2024

Shipping rates from Germany to U.S.A.

Item	60 to 60 business days	60 to 60 business days
First item	£ 59.99	£ 59.99

Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

Paypal

Store description

preigu betreibt einen Onlineversandhandel mit über 1 Mio. Produkten in verschiedenen Sortimenten. Das Kernsortiment besteht aus Büchern, Medien und Spielwaren. Ein gelungenes Einkaufserlebnis ist das Ziel einer jeden Bestellung bei preigu, denn der Kunde und seine Zufriedenheit stehen an erster Stelle. preigu setzt daher auf einen kompetenten Kundenservice, funktionierende Prozesse und schnelle Reaktion.

Specialty

Bücher, Spielwaren

Seller's business information

preigu GmbH & Co. KG

Lengericher Landstraße 19
Osnabrück, Germany 49078

Contact sellerView this seller's itemsView seller's storefront

Terms of sale

About Us

Legal website operator identification:

preigu GmbH & Co. KG
Lengericher Landstr. 19
49078 Osnabrück
Germany

Telephone: +49 (0) 541 / 580 72 84
Email: mail@preigu.de

VAT No: DE 455 380 498
AG Osnabrück - HRA 209647

PhG: preigu Verwaltung GmbH
AG Osnabrück - HRB 221793
CEO: Ansas Meyer

We are neither willing nor obliged to participate in dispute resolution proceedings before consumer arbitration boards.

We are a member of the initiative "FairCommerce" since 30.11.2016.
For more information, see: https://www.haendlerbund.de/de/haendlerbund/interessenvertretung/faircommerce

Right of withdrawal

Instructions for revocation

Right of withdrawal for the sale of goods

Revocation right for consumers
(A ‘consumer' is any natural person who concludes a legal transaction which, to an overwhelming extent, cannot be attributed to either his commercial or independent professional activities.)

Instructions for revocation

Revocation right
You have the right to revoke this contract within 14 days without specifying any reasons.
The revocation period is 14 days with effect from the day,

on which you or a third party nominated by you, which is not the carrier, had taken possession of the products, provided you had ordered one or more products within the scope of a standard order and this/these product/products is/are delivered uniformly;
on which you or a third party nominated by you, which is not the carrier, had taken possession of the last product, provided you had ordered several products within the scope of a standard order and these products are delivered separately;
on which you or a third party nominated by you, which is not the carrier, had taken possession of the last part delivery or the last unit, provided you had ordered a product, which is delivered in several part deliveries or units;

To exercise your right of withdrawal, you must inform us (preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, Telephone number: +49 (0) 541 / 580 72 84, E-Mail address: mail@preigu.de) by means of a clear declaration (e.g. a letter sent by post, or an e-mail) of your decision to withdraw from this contract. You can use the attached model withdrawal form for this purpose, which is, however, not mandatory.

You can also exercise your right of withdrawal online by clicking on a button labelled accordingly (such as ‘Withdraw from contract' or similar) on the AbeBooks/ZVAB website. If you use this online function, you will immediately receive a confirmation of receipt on a durable medium (e.g. via email) containing information on the content of the withdrawal notice, as well as the date and time of its receipt.

In order to safeguard the revocation period, it is sufficient that you send the notification about the exercise of the revocation right before the expiry of the revocation period.

Consequences of the revocation

If you revoke this contract, we shall repay all the payments, which we received from you, including the delivery costs (with the exception of additional costs, which arise from that fact that you selected a form of delivery other than the most reasonable standard delivery offered by us), immediately and at the latest within 14 days from the day on which we received the notification about the revocation of this contract from you. We use the same means of payment, which you had originally used during the original transaction, for this repayment unless expressly agreed otherwise with you; you will not be charged any fees owing to this repayment.

We can refuse the repayment until the products are returned to us or until you have furnished evidence that you have sent the products back to us, depending on whichever is earlier.

You must return or transfer the products to us immediately and, in any case, at the latest within 14 days with effect from the day on which you inform us of the revocation of this contract. The deadline is maintained if you send the products before the expiry of the 14 day deadline.

You bear the direct costs for returning the products.

You must pay for any depreciation of the products only if this depreciation can be attributed to any handling with you that was not necessary for checking the condition, features and functionality of the products.

Criteria for exclusion or expiry

The revocation right is not available for contracts

for delivery of products, which are not prefabricated and for whose manufacturing an individual selection or stipulation by the consumer is important or which are clearly tailored to the personal requirements of the consumer;
for delivery of products, which can spoil quickly or whose use-by date would be exceeded quickly;
for delivery of alcoholic drinks, whose price was agreed at the time of concluding the contract, which however can be delivered 30 days after the conclusion of the contract at the earliest and whose current value depends on the fluctuations in the market, on which the entrepreneur has no influence;
for delivery of newspapers, periodicals or magazines with the exception of subscription contracts. The revocation right expires prematurely in case of contracts
for delivery of sealed products, which are not suitable for return for reasons of health protection or hygiene if their seal has been removed after the delivery;
for delivery of products if they have been mixed inseparably with other goods after the delivery, owing to their condition;
for delivery of sound or video recording or computer software in a sealed package if the seal has been removed after the delivery.

Specimen - revocation form

(If you wish to revoke the contract, please fill up this form and send it back to us.)

To preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, Email address: mail@preigu.de :
I/we () herewith revoke the contract concluded by me/ us () regarding the purchase of the following products ()/
the provision of the following service ()
Ordered on ()/ received on ()
Name of the consumer(s)
Address of the consumer(s)
Signature of the consumer(s) (only in case of a notification on paper)
Date

(*) Cross out the incorrect option.