000 -LEADER |
fixed length control field |
02784nam a22004575i 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
OSt |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20140310154015.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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130321s2013 xxk| s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781447149682 |
|
978-1-4471-4968-2 |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
HD9502-9502.5 |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
333.79 |
Edition number |
23 |
|
Classification number |
338.926 |
Edition number |
23 |
264 #1 - |
-- |
London : |
-- |
Springer London : |
-- |
Imprint: Springer, |
-- |
2013. |
912 ## - |
-- |
ZDB-2-ENE |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Hong, Wei-Chiang. |
Relator term |
author. |
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
Title |
Intelligent Energy Demand Forecasting |
Medium |
[electronic resource] / |
Statement of responsibility, etc |
by Wei-Chiang Hong. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
XIII, 189 p. 70 illus. |
Other physical details |
online resource. |
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
Title |
Lecture Notes in Energy, |
International Standard Serial Number |
2195-1284 ; |
Volume number/sequential designation |
10 |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
1.Introduction -- 2.Modeling for Energy Demand Forecasting -- 3.Evolutionary Algorithms in SVR’s Parameters Determination -- 4.Chaos/Cloud Theories to Avoid Trapping into Local Optimum -- 5.Recurrent/Seasonal Mechanism to Improve the Accurate Level of Forecasting. |
520 ## - SUMMARY, ETC. |
Summary, etc |
As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand. Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms. Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Computer simulation. |
|
Topical term or geographic name as entry element |
Electric engineering. |
|
Topical term or geographic name as entry element |
Engineering economy. |
|
Topical term or geographic name as entry element |
Energy. |
|
Topical term or geographic name as entry element |
Energy Policy, Economics and Management. |
|
Topical term or geographic name as entry element |
Energy Technology. |
|
Topical term or geographic name as entry element |
Simulation and Modeling. |
|
Topical term or geographic name as entry element |
Energy Economics. |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Display text |
Printed edition: |
International Standard Book Number |
9781447149675 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-1-4471-4968-2 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
|
Item type |
E-Book |