Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast (Record no. 65791)

MARC details
000 -LEADER
fixed length control field 03501naaaa2200637uu 4500
001 - CONTROL NUMBER
control field https://directory.doabooks.org/handle/20.500.12854/76485
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220220044329.0
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number books978-3-0365-0863-4
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783036508627
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783036508634
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.3390/books978-3-0365-0863-4
Terms of availability doi
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title English
042 ## - AUTHENTICATION CODE
Authentication code dc
072 #7 - SUBJECT CATEGORY CODE
Subject category code GP
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code TB
Source bicssc
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Gómez Vela, Francisco A.
Relationship edt
245 10 - TITLE STATEMENT
Title Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Basel, Switzerland
Name of publisher, distributor, etc. MDPI - Multidisciplinary Digital Publishing Institute
Date of publication, distribution, etc. 2021
300 ## - PHYSICAL DESCRIPTION
Extent 1 electronic resource (100 p.)
506 0# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Open Access
Source of term star
Standardized terminology for access restriction Unrestricted online access
520 ## - SUMMARY, ETC.
Summary, etc. The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such big data give rise to a number of opportunities and challenges for informed decision making. In recent years, researchers have been working very actively in order to come up with effective and powerful techniques in order to deal with the huge amount of data available. Such approaches can be used in the context of energy production and consumption considering the amount of data produced by all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high-performance computing, or data visualization are being successfully applied to energy demand forecasting. In light of the above, this Special Issue collects the latest research on relevant topics, in particular in energy demand forecasts, and the use of advanced optimization methods and big data techniques. Here, by energy, we mean any kind of energy, e.g., electrical, solar, microwave, or wind
540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE
Terms governing use and reproduction Creative Commons
Use and reproduction rights https://creativecommons.org/licenses/by/4.0/
Source of term cc
-- https://creativecommons.org/licenses/by/4.0/
546 ## - LANGUAGE NOTE
Language note English
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Research & information: general
Source of heading or term bicssc
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Technology: general issues
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Uncontrolled term deep learning
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Uncontrolled term energy demand
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Uncontrolled term temporal convolutional network
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Uncontrolled term time series forecasting
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Uncontrolled term time series
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Uncontrolled term forecasting
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Uncontrolled term exponential smoothing
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Uncontrolled term electricity demand
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Uncontrolled term residential building
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Uncontrolled term energy efficiency
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Uncontrolled term clustering
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Uncontrolled term decision tree
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Uncontrolled term time-series forecasting
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Uncontrolled term evolutionary computation
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Uncontrolled term neuroevolution
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Uncontrolled term photovoltaic power plant
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Uncontrolled term short-term forecasting
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Uncontrolled term data processing
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Uncontrolled term data filtration
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Uncontrolled term k-nearest neighbors
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Uncontrolled term regression
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Uncontrolled term autoregression
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Uncontrolled term n/a
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name García-Torres, Miguel
Relationship edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Divina, Federico
Relationship edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Gómez Vela, Francisco A.
Relationship oth
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name García-Torres, Miguel
Relationship oth
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Divina, Federico
Relationship oth
856 40 - ELECTRONIC LOCATION AND ACCESS
Host name www.oapen.org
Uniform Resource Identifier <a href="https://mdpi.com/books/pdfview/book/3931">https://mdpi.com/books/pdfview/book/3931</a>
Access status 0
Public note DOAB: download the publication
856 40 - ELECTRONIC LOCATION AND ACCESS
Host name www.oapen.org
Uniform Resource Identifier <a href="https://directory.doabooks.org/handle/20.500.12854/76485">https://directory.doabooks.org/handle/20.500.12854/76485</a>
Access status 0
Public note DOAB: description of the publication

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