Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
A Computer-Aided Diagnostic System to Detect Polyp in Computed Tomographic Colonography Images Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Short-Term Wind Speed Forecasting Based on PSO-ELM

Authors : Ai Li, Xiong Wei

Published in: Innovative Computing

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In view of the low prediction accuracy of short-term wind speed, for ELM, the connection weight and hidden layer threshold of input layer and hidden layer were randomly generated, which led to the decrease of network generalization ability and the distortion of evaluation result caused by over-fitting, a forecasting method based on particle swarm combined extremely learning machine (PSO-ELM) was proposed. The example analysis showed that the model had high prediction accuracy and could effectively track the variation of wind speed.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Computer-Aided Inspection and Quality Control System for Automotive Parts
next chapter Practice of Informatization and Flipped Classroom in Technical Courses
Literature
1.
Ling, Jin, Meiqin Mao, Fugen Li, et al. 2017. Research on methods and application of short-term wind speed forecasting. Journal of Hefei University of Technology (Natural Science) 40 (11): 1502–1506.
2.
Meng, Anbo, Jiafei Ge, Hao Yin, et al. 2016. Wind speed forecasting based on wavelet packet decomposition and artificial neural networks trained by crisscross optimization algorithm. Energy Conversion and Management 114: 75–88.CrossRef
3.
Lu, Jing, and Ming Zeng. 2019. Adaboost_GRNN combination forecasting model for short-term wind speed. Proceedings of the CSU-EPSA 4: 70–76.
4.
Yang, Mao, and Qiongqiong YANG. 2018. Review of modeling of wind speed-power characteristic curve for wind turbine. Electric Power Automation Equipment 38 (2): 34–43.
5.
Chen, Ning, Yusheng Xue, Jie Ding, et al. 2017. Ultra-short term wind speed prediction using spatial correlation. Automation of Electric Power Systems 41 (12): 124–130.
6.
Fan, Lei, Zhinong Wei, Huijie Li, et al. 2017. Short-term wind speed interval prediction based on VMD and BA-RVM algorithm. Electric Power Automation Equipment 37 (1): 93–100.
7.
Wang, Jing, and Weide Li. 2018. Ultra-short-term forecasting of wind speed based on CEEMD and GWO. Power System Protection and Control 46 (9): 69–74.
8.
Lu, Siyuan, Zhihai Lu, Shuihua Wang, et al. 2018. Overview of extreme learning machine. Measurement & Control Technology 37 (10): 3–9.
9.
Liu, Yun, Quanxing Liu, Ming Yin, et al. 2019. Dynamic performance optimization of dry gas seal based on particle swarm optimization and projection tracking analysis. Engineering Science and Technology 51 (1): 248–255.
10.
Metadata
Title
Short-Term Wind Speed Forecasting Based on PSO-ELM
Authors
Ai Li
Xiong Wei
Copyright Year
2020
Publisher
Springer Singapore
Book
Innovative Computing

Print ISBN: 978-981-15-5958-7

Electronic ISBN: 978-981-15-5959-4

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-5959-4_130

Premium Partner

    Image Credits