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

Non-Gaussian fluctuating wind speed prediction method based on a hybrid intelligent algorithm

A technology of pulsating wind speed and intelligent algorithm, applied in the direction of calculation, calculation model, special data processing application, etc., can solve problems such as deformation or collapse of building surface materials, fatigue damage of external components and appendages, damage of building structural components, etc., to achieve The effect of good fit, good learning and generalization ability, and strong accuracy

Pending Publication Date: 2021-05-28
LIAONING TECHNICAL UNIVERSITY
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the uneven distribution of positive and negative wind pressure areas on the top of the large-span structure, the pulsating wind will cause the building structure to vibrate when it is severe, and the shedding of the surface wind pressure vortex will cause deformation vibration, and in extreme cases, it will cause deformation or collapse of the building surface material Serious damage such as severe damage; structural dynamic displacement exceeding a certain limit will cause damage to building structural components; large surface vibrations will cause fatigue damage to external components and appendages

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
  • Non-Gaussian fluctuating wind speed prediction method based on a hybrid intelligent algorithm
  • Non-Gaussian fluctuating wind speed prediction method based on a hybrid intelligent algorithm
  • Non-Gaussian fluctuating wind speed prediction method based on a hybrid intelligent algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] The specific implementation of the present invention will be described in detail below in conjunction with the accompanying drawings. As a part of this specification, the principles of the present invention will be described through examples. Other aspects, features and advantages of the present invention will become clear through the detailed description. In the referenced drawings, the same reference numerals are used for the same or similar components in different drawings.

[0067] Such as Figure 1 to Figure 16 As shown, the standard cuckoo algorithm of the present invention randomly generates and allocates the initial nest position, and the calculation result depends on the initial random nest position, which is not conducive to the convergence of the algorithm and affects the final result. Use the method of chaos theory mapping reverse learning to initialize the generation and distribution of the cuckoo nest position, replace the random generation and distributio...

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 non-Gaussian fluctuating wind speed prediction method based on a hybrid intelligent algorithm. The method comprises the following steps: generating a large-span spherical roof structure spatial point non-Gaussian fluctuating wind speed sample through JT transformation and AR model simulation, and dividing the non-Gaussian fluctuating wind speed of each spatial point into a training set and a test set, and performing normalization processing before each simulation test; respectively deducing kernel parameter combinations consisting of kernel parameters and penalty factors searched based on cuckoo and particle swarm intelligent algorithms; by using a CS+PSO-LSSVM learning machine, transforming a non-Gaussian fluctuating wind speed training set sample into a kernel function matrix, mapping the kernel function matrix to a high-latitude feature space, then inputting the sample data and mapping it to a high-dimensional feature space through a nonlinear function; testing multiple linear algorithms on the kernel function matrix optimized by a hybrid intelligent algorithm, and acquiring a non-linear model of the non-Gaussian fluctuating wind speed training sample; and predicting the non-Gaussian fluctuating wind speed test set sample by using the non-linear model.

Description

technical field [0001] The invention belongs to the technical field of wind speed prediction, in particular to a method for predicting non-Gaussian fluctuating wind speed based on a hybrid intelligent algorithm. Background technique [0002] With the rapid development of science and technology, it is also constantly affecting the transformation of the concept of the construction industry and the innovation of technology. As a large-span structure, it is widely used among many building structures, and its structure is complex and the characteristics of the construction environment are changeable. It has attracted the attention of people from all walks of life, and overseas scholars are striving to pursue the goals of light weight, high flexibility and low damping for long-span structures. The main problems faced in structural wind engineering are the wind-induced dynamic response due to the large span and high flexibility of the structure, as well as improving the estimation,...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/13G06F30/28G06N3/00
CPCG06F30/13G06F30/28G06N3/006
Inventor 路明璟孙芳锦
Owner LIAONING TECHNICAL UNIVERSITY
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