NLU Meghalaya Library

Online Public Access Catalogue (OPAC)

Artificial intelligence for renewable energy systems / (Record no. 12871)

MARC details
000 -LEADER
fixed length control field 05231cam a2200529 i 4500
001 - CONTROL NUMBER
control field on1301543087
003 - CONTROL NUMBER IDENTIFIER
control field OCoLC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240523125543.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cnu|||unuuu
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220303s2022 nju ob 001 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency DG1
Language of cataloging eng
Description conventions rda
-- pn
Transcribing agency DG1
Modifying agency OCLCO
-- ORMDA
-- OCLCF
-- UKAHL
-- N$T
-- OCLCQ
-- OCLCO
-- OCLCQ
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781119761686
Qualifying information (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1119761689
Qualifying information (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781119761723
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1119761727
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781119761693
Qualifying information (print)
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1002/9781119761686
Source of number or code doi
029 1# - OTHER SYSTEM CONTROL NUMBER (OCLC)
OCLC library identifier AU@
System control number 000071250414
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1301543087
037 ## - SOURCE OF ACQUISITION
Stock number 9781119761693
Source of stock number/acquisition O'Reilly Media
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TJ808
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 621.042
Edition number 23
049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
245 00 - TITLE STATEMENT
Title Artificial intelligence for renewable energy systems /
Statement of responsibility, etc. edited by Ajay Kumar Vyas [and more].
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Hoboken, NJ :
Name of producer, publisher, distributor, manufacturer Wiley ;
Place of production, publication, distribution, manufacture Beverly, MA :
Name of producer, publisher, distributor, manufacturer Scrivener Publishing,
Date of production, publication, distribution, manufacture, or copyright notice 2022.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Front Matter -- Analysis of Six-Phase Grid Connected Synchronous Generator in Wind Power Generation / Arif Iqbal, Girish Kumar Singh -- Artificial Intelligence as a Tool for Conservation and Efficient Utilization of Renewable Resource / N Vinay, Ajay Sudhir Bale, Subhashish Tiwari, Chithra R Baby -- Artificial Intelligence-Based Energy-Efficient Clustering and Routing in IoT-Assisted Wireless Sensor Network / Nitesh Chouhan -- Artificial Intelligence for Modeling and Optimization of the Biogas Production / Narendra Khatri, Kamal Kishore Khatri -- Battery State-of-Charge Modeling for Solar PV Array Using Polynomial Regression / Siddhi Vinayak Pandey, Jeet Patel, Harsh S Dhiman -- Deep Learning Algorithms for Wind Forecasting: An Overview / M Lydia, G Edwin Prem Kumar -- Deep Feature Selection for Wind Forecasting-I / C Ramakrishnan, S Sridhar, Kusumika Krori Dutta, R Karthick, C Janamejaya -- Deep Feature Selection for Wind Forecasting-II / S Oswalt Manoj, JP Ananth, Balan Dhanka, Maharaja Kamatchi -- Data Falsification Detection in AMI: A Secure Perspective Analysis / VV Vineeth, S Sophia -- Forecasting of Electricity Consumption for G20 Members Using Various Machine Learning Techniques / Jaymin Suhagiya, Deep Raval, Siddhi Vinayak Pandey, Jeet Patel, Ayushi Gupta, Akshay Srivastava -- Use of Artificial Intelligence (AI) in the Optimization of Production of Biodiesel Energy / Manvinder Singh Pahwa, Manish Dadhich, Jaskaran Singh Saini, Dinesh Kumar Saini -- Index -- Also of Interest
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
588 0# - SOURCE OF DESCRIPTION NOTE
Source of description note Online resource; title from PDF title page (John Wiley, viewed March 3, 2022).
520 ## - SUMMARY, ETC.
Summary, etc. ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today's world, this book was designed to enhance the reader's knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.
590 ## - LOCAL NOTE (RLIN)
Local note John Wiley and Sons
Provenance (VM) [OBSOLETE] Wiley Online Library: Complete oBooks
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Renewable energy sources
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence
General subdivision Engineering applications.
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element �Energies renouvelables
General subdivision Informatique.
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Intelligence artificielle
General subdivision Applications en ing�enierie.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence
General subdivision Engineering applications
Source of heading or term fast
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Renewable energy sources
General subdivision Data processing
Source of heading or term fast
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Vyas, Ajay Kumar,
Relator term editor.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://onlinelibrary.wiley.com/doi/book/10.1002/9781119761686">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119761686</a>
938 ## -
-- Askews and Holts Library Services
-- ASKH
-- AH39675783
938 ## -
-- EBSCOhost
-- EBSC
-- 3163884
994 ## -
-- 92
-- INLUM

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