Concrete structure durability prediction method based on random forest and intelligent algorithm

A technology of concrete structure and random forest, applied in the direction of neural learning methods, calculations, calculation models, etc., can solve the problems of large dispersion of experimental observation data, long experimental period, unreliable prediction results, etc., to solve the problem of unstable prediction results, The effect of solving computational complexity and good anti-interference ability

Active Publication Date: 2020-11-24
HUAZHONG UNIV OF SCI & TECH
View PDF4 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, many experts at home and abroad have conducted relevant research on the impermeability of concrete, but most of the research generally uses traditional experimental methods, and traditional experimental methods are affected by factors such as randomness of measurement data and systematic errors. There are many uncertainties in the permeation laws of the country. Using general statistical methods, the discreteness of experimental observation data is large, which often causes distortion of analysis results. Moreover, traditional experimental methods are often a long-term and complicated process, and the experimental period is long. Huge workload and relatively low research efficiency
[0004] With the continuous advancement of computer technology, some experts have also begun to turn their attention to the field of intelligent algorithms, trying to

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
  • Concrete structure durability prediction method based on random forest and intelligent algorithm
  • Concrete structure durability prediction method based on random forest and intelligent algorithm
  • Concrete structure durability prediction method based on random forest and intelligent algorithm

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0076] Example 1

[0077] The method for predicting the impermeability of concrete structures based on random forest-based least squares support vector machines proposed in the present invention mainly includes the following steps:

[0078] (1) Sample data collection of influencing factor index system

[0079] Based on cement strength, cement dosage, fly ash dosage, water reducing agent dosage, fine aggregate dosage, coarse aggregate dosage, concrete strength, sand ratio, water-binder ratio, water dosage, alkali content, mud content, needles, flakes There are a total of 14 factors, including the total content and average particle size of particles, as input variables, and the chloride ion diffusion coefficient of concrete as output variables. 33 sets of monitored data are selected as the original training number set. The data are shown in Table 1:

[0080] Table 1 sample data

[0081]

[0082] (2) Random forest feature selection

[0083] Divide all data samples into two parts: a trainin...

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 belongs to the technical field of concrete structure impermeability prediction, and particularly discloses a method for predicting durability of a concrete structure based on a random forest and an intelligent algorithm. The method comprises the following steps: constructing a concrete impermeability index system, establishing an original sample set, taking the training number set asthe input of a random forest regression model; carrying out importance evaluation on influence factors of the impermeability index system; selecting an influence factor set with the minimum error ofthe random forest regression model; taking the optimal characteristic variable set as an input variable of the least squares support vector machine model, taking a concrete chloride ion diffusion coefficient prediction result as an output variable, training the least squares support vector machine model, and then verifying the prediction result of the trained least squares support vector machine model by adopting the test number set; and analyzing the prediction result, and verifying the effect of predicting the impermeability of the concrete structure by the least square support vector machine model. The method is high in prediction speed and accurate and reliable in prediction result.

Description

technical field [0001] The invention belongs to the technical field of predicting the impermeability of concrete structures, and more specifically relates to a method for predicting the durability of concrete structures based on random forests and intelligent algorithms. Background technique [0002] In recent years, in actual engineering, the incidents of structural damage due to insufficient durability of concrete have occurred frequently. As a widely used building material, the durability of concrete has attracted more and more attention at home and abroad. The early durability of concrete is generally reflected by indicators such as frost resistance, impermeability, and erosion resistance, among which impermeability is one of the important indicators reflecting the durability of concrete. Therefore, it is necessary to quickly and effectively predict the early impermeability of concrete It has important engineering application value. [0003] At present, many experts at ...

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): G06Q10/06G06F30/13G06F30/20G06N3/00G06N3/08
CPCG06N3/006G06N3/084G06Q10/06393G06F30/13G06F30/20
Inventor 吴贤国杨赛陈彬王堃宇陈虹宇吴霁峰张浩蔚王雷徐文胜吴克宝
Owner HUAZHONG UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products