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

Optimized and improved fuzzy regression model construction method based on nondominated sorting genetic algorithm II (NSGA- II)

A technology of regression model and construction method, applied in the direction of fuzzy logic-based systems, pulse technology, logic circuits, etc., can solve problems such as redundancy of former parts

Inactive Publication Date: 2013-07-10
NANJING UNIV OF SCI & TECH
View PDF0 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The above technologies have optimized the fuzzy regression model, which has improved the interpretability of the model to varying degrees, but the redundancy of fuzzy rules and their antecedents still exists.

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
  • Optimized and improved fuzzy regression model construction method based on nondominated sorting genetic algorithm II (NSGA- II)
  • Optimized and improved fuzzy regression model construction method based on nondominated sorting genetic algorithm II (NSGA- II)
  • Optimized and improved fuzzy regression model construction method based on nondominated sorting genetic algorithm II (NSGA- II)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0092] In the following embodiments, the number of fuzzy rules, the total number of rule antecedents and the mean square error are selected to evaluate the regression effect of the model.

[0093] Generally speaking, the smaller the mean square error, the higher the accuracy of the fuzzy regression model, the smaller the number of fuzzy rules and the total number of antecedents of the rules, and the better the interpretability of the fuzzy regression model.

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 an optimized and improved fuzzy regression model construction method based on a nondominated sorting genetic algorithm II (NSGA-II). The optimized and improved fuzzy regression model construction method based on the NAGA-II reduces fuzzy sets, fuzzy rule and redundancy of antecedent of the fuzzy rule, and improves explanatory of a fuzzy regression model. The optimized and improved fuzzy regression model construction method based on the NSGA-II comprises the following steps: firstly an initial fuzzy regression model is constructed by a triangle subordinate function and a WM (WangandMendel) algorithm; and then based on a NSGA-II optimized fuzzy regression model, the redundancy of the fuzzy rule is simultaneously deleted by selecting the fuzzy rule and the antecedent of the fuzzy rule, thereby improving accuracy and explanatory of the fuzzy regression model.

Description

technical field [0001] The present invention relates to the technical field of data mining and artificial intelligence, in particular to an optimized and improved fuzzy regression model construction method based on the second-generation non-dominated sorting genetic algorithm (Non-dominated sorting genetic algorithm II, NSGA-II). Background technique [0002] The knowledge expression form and reasoning mechanism of the fuzzy regression model conform to human thinking habits, and its structure and fuzzy set membership function parameters have obvious physical meaning. People can gain insight into the internal operation mechanism of regression models through easy-to-understand fuzzy rules, that is, interpretability is the most prominent feature of fuzzy regression models. [0003] With the increase of the dimension and complexity of the regression problem, there are mainly the following problems in the construction of the fuzzy regression model using the traditional method, wh...

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): G06N7/02
Inventor 邢宗义季海燕刘萍李建伟冒玲丽郭翔
Owner NANJING UNIV OF SCI & TECH
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