Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Water level prediction method based on improved VMD-QR-ELM hybrid model

A VMD-QR-ELM, hybrid model technology, applied in forecasting, computational models, instruments, etc., can solve problems such as complexity, poor model generalization ability, and reduced model efficiency.

Pending Publication Date: 2021-04-30
NORTH CHINA UNIV OF WATER RESOURCES & ELECTRIC POWER
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The prediction model based on time series analysis, especially the intelligent model based on neural network, because of its complex network structure, the efficiency of the model is reduced, and the generalization ability of the model is poor.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Water level prediction method based on improved VMD-QR-ELM hybrid model
  • Water level prediction method based on improved VMD-QR-ELM hybrid model
  • Water level prediction method based on improved VMD-QR-ELM hybrid model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0064] Before explaining the method of the present invention, the relevant content of the extreme learning machine is firstly introduced.

[0065] Extreme Learning Machine (Extreme Learning Machine, ELM) is a machine learning method based on feedforward neural network (Feedforward Neuron Network, FNN). Different from artificial neural network, the weight of the hidden layer nodes of extreme learning machine is artificially given. , and no updates are required,...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a water level prediction method based on an improved VMD-QR-ELM hybrid model, and relates to the technical field of water level prediction. Orthogonal triangular matrix factorization (QR) is applied to extreme learning, and then QR type extreme learning is constructed on the basis. then variational mode decomposition (VMD) is improved through extreme value extension so as to solve an endpoint effect existing in a VMD method, finally, QR-ELM and the improved variational mode decomposition are deeply fused, and the parallel VMDQRELM hybrid model is constructed based on a parallel computing thought. Compared with a traditional extreme learning model (ELM), the water level prediction model based on the parallel VMD-QR-ELM has the advantages that the accuracy is improved by 2.05 times, the credibility is improved by 1.56 times, and the efficiency of a serial model is improved by 5.56 times.

Description

technical field [0001] The invention relates to the technical field of water level prediction, in particular to a water level prediction method based on an improved VMD-QR-ELM hybrid model. Background technique [0002] Water level is a key link in the water cycle, so it is of great significance to predict it accurately and efficiently. With more and more extreme weather, water level fluctuations in changing environments are increasing, which brings new challenges to water level forecasting. [0003] At present, data-driven water level forecasting models are mainly divided into two approaches: time series analysis and causal relationship analysis, such as improving the SCS-CN method; using GRU and LSTM networks for short-term water level forecasting; calibrating the curve number water level forecasting model; using Mann-Kendall method and wavelet analysis method to analyze water level data; water level forecasting method based on random forest algorithm; water level forecas...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06Q10/04G06Q50/26G06N20/00
CPCG06Q10/04G06Q50/26G06N20/00
Inventor 刘扬王立虎杨礼波刘雪梅
Owner NORTH CHINA UNIV OF WATER RESOURCES & ELECTRIC POWER
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com