Predicting the Future Big Data and Machine Learning

Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information,...

Full description

Saved in:
Bibliographic Details
Other Authors: Sánchez Lasheras, Fernando (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:DOAB: download the publication
DOAB: description of the publication
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000naaaa2200000uu 4500
001 doab_20_500_12854_68909
005 20210501
003 oapen
006 m o d
007 cr|mn|---annan
008 20210501s2020 xx |||||o ||| 0|eng d
020 |a books978-3-03936-620-0 
020 |a 9783039366194 
020 |a 9783039366200 
040 |a oapen  |c oapen 
024 7 |a 10.3390/books978-3-03936-620-0  |c doi 
041 0 |a eng 
042 |a dc 
072 7 |a TBX  |2 bicssc 
100 1 |a Sánchez Lasheras, Fernando  |4 edt 
700 1 |a Sánchez Lasheras, Fernando  |4 oth 
245 1 0 |a Predicting the Future  |b Big Data and Machine Learning 
260 |a Basel, Switzerland  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2020 
300 |a 1 electronic resource (148 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information, has meant that machine learning and Big Data have an important presence in the field of Energy. This Special Issue entitled "Predicting the Future-Big Data and Machine Learning" is focused on applications of machine learning methodologies in the field of energy. Topics include but are not limited to the following: big data architectures of power supply systems, energy-saving and efficiency models, environmental effects of energy consumption, prediction of occupational health and safety outcomes in the energy industry, price forecast prediction of raw materials, and energy management of smart buildings. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by/4.0/ 
546 |a English 
650 7 |a History of engineering & technology  |2 bicssc 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/2676  |7 0  |z DOAB: download the publication 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/68909  |7 0  |z DOAB: description of the publication