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

A hybrid test online model updating method based on an LSSVM

A mixed test and model update technology, which is applied in character and pattern recognition, special data processing applications, instruments, etc., can solve the problems of less research on online model update, poor generalization, and low calculation efficiency of mixed tests, and achieve accurate Prediction of resilience, high prediction accuracy, and effects of improved accuracy

Active Publication Date: 2019-06-14
SOUTHEAST UNIV
View PDF5 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] There are few studies on the online model update of hybrid experiments based on intelligent algorithms, and the model update algorithm based on the traditional BP neural network algorithm is prone to local minima and overfitting, poor generalization, and low computational efficiency

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
  • A hybrid test online model updating method based on an LSSVM
  • A hybrid test online model updating method based on an LSSVM
  • A hybrid test online model updating method based on an LSSVM

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0052] The present invention will be further described below in conjunction with accompanying drawing.

[0053] In order to solve the model accuracy problem of the numerical substructure in the seismic hybrid test, realize the online model update of the numerical substructure constitutive model, so as to realize the purpose of accurately predicting the restoring force of the numerical substructure, the embodiment of the present invention provides a method based on LSSVM Online model update method for mixed experiments, see figure 2 .

[0054] Support vector machine is a machine learning method suitable for small samples, which can be applied to the regression problem of any nonlinear function relationship. SVM does not have problems such as randomness of training results and over-learning, and has better generalization. Least squares support vector machine (LSSVM) is improved and developed on the basis of SVM. Different from the inequality constraint optimization in SVM, LS...

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

A hybrid test online model updating method based on the LSSVM comprises the steps of collecting the offline samples of a nonlinear structure constitutive model, and constructing a training sample set;optimizing constitutive model parameters according to the training sample set, training a model by using the current model parameters and the selected sample set, and taking the trained model as a structure prediction model; after a motion equation of the whole structure of the hybrid test is established, adopting a numerical integration algorithm to solve the target displacement of the test substructure of the i-th step of the hybrid test and the target displacement of the numerical substructure; and deleting the first sample in the current training sample set, and adding the sample of the test substructure in the step, thereby updating the training sample set, and then obtaining an updated structure prediction model. According to the method, the initial model of the nonlinear structureis established based on the big data, then the model training sample set is continuously updated online, the model parameters are optimized, the constitutive model is updated online in real time, andtherefore the purpose of accurately predicting the numerical value substructure restoring force is achieved.

Description

technical field [0001] The invention relates to an anti-seismic test method in the field of civil engineering, in particular to an online model update method for a hybrid test based on LSSVM. Background technique [0002] In the field of civil engineering, commonly used seismic test methods mainly include: pseudo-static test, shaking table test and pseudo-dynamic test. Pseudo-static test is to carry out low-cycle and cyclic loading on the specimen according to a certain load control or displacement control mode, so that the specimen is elastically stressed until it is destroyed, thereby obtaining the constitutive model of the restoring force of the structure or structural components. Its advantages are simple, economical and practical, but it cannot truly simulate the dynamic response of the structure under earthquake action. The earthquake simulation shaking table test can reproduce the dynamic effect of the earthquake on the structure, but it is limited by the tonnage of ...

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): G06F17/50G06K9/62
Inventor 王燕华吕静
Owner SOUTHEAST UNIV
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