Intelligent Energy Demand Forecasting / Lecture Notes in Energy Bd.10 (PDF)
48 DeutschlandCard Punkte sammeln
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
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.
Dr. Hong serves as the program committee of various international conferences including premium ones such as IEEE CEC, IEEE CIS, IEEE ICNSC, IEEE SMC, IEEE CASE, and IEEE SMCia, etc.. In May 2012, his paper had been evaluated as "Top Cited Article 2007-2011" by Elsevier Publisher (Netherlands). In Sep. 2012, once again, his paper had been indexed in ISI Essential Science Indicator database as Highly Cited Papers, in the meanwhile, he also had been awarded as the Model Teacher Award by Taiwan PrivateEducation Association.
Dr. Hong is a senior member of IIE and IEEE. He is indexed in the list of Who's Who in the World (25th-30th Editions), Who's Who in Asia (2nd
- Autor: Wei-Chiang Hong
- 2013, 2013, 189 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 1447149688
- ISBN-13: 9781447149682
- Erscheinungsdatum: 12.03.2013
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 5.15 MB
- Ohne Kopierschutz
- Vorlesefunktion
Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
---|
Schreiben Sie einen Kommentar zu "Intelligent Energy Demand Forecasting / Lecture Notes in Energy Bd.10".
Kommentar verfassen