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

Fuzzy concept related parallel generating method based on load balancing

A fuzzy concept and load balancing technology, applied in fuzzy logic-based systems, concurrent instruction execution, machine execution devices, etc., can solve problems such as high time complexity and long time consumption

Inactive Publication Date: 2013-09-25
ZHENGZHOU UNIV
View PDF3 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a parallel generation method based on load balancing of fuzzy concepts, using parallel computing technology and computing load balancing method to solve the problem of high time complexity and long time consumption in the process of fuzzy concept construction

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
  • Fuzzy concept related parallel generating method based on load balancing
  • Fuzzy concept related parallel generating method based on load balancing
  • Fuzzy concept related parallel generating method based on load balancing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0079] Table 1 Fuzzy form background

[0080]

[0081] Let the background K of the fuzzy form be the content in Table 1, the truth value set L={0,0.5,1}, run on a dual-core CPU, that is, D=2.

[0082] 1. Initial search interval set E={[0,242]};

[0083] 2. The entire search space can be regarded as a 3-fork complete search tree with a height of 5; the path prefix is ​​checked from level 0 (i=0);

[0084] 3. According to the calculation load measurement method provided by the present invention, the calculation load Q 0 =3;

[0085] 4. The range of subtasks is CPU 0:[0,2], CPU 1:[2,3];

[0086] 5. According to the task allocation method provided by the present invention, each CPU obtains sub-search intervals as follows:

[0087] E sub 0 = { [ 0,161 ] } ; E sub 1 = [ 1...

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 fuzzy concept related parallel generating method based on load balancing. The fuzzy concept related parallel generating method includes the following steps: (1) generating a fuzzy formal background according to a dataset to be processed and an accuracy requirement, (2) initializing a global section set according to the fuzzy formal background, namely (a formula), (3) carrying out breadth-first traversal from top to bottom on an ||L|| complete search tree of a high order ||Y||, regarding i as the current height, (4) calculating total loads Qi under the current height i by a root node processor according to a global search section set E, a first formula and a second formula, (5) assigning a subtask range (Blow, Bup)of each node in a balanced mode according to the number D of processors which can be governed under the current parallel calculation environment, a fifth formula, a sixth formula and a seventh formula, (6) enabling each processor to obtain a partial task section set, and regarding Esub as the partial task sections. According to the fuzzy concept related parallel generating method based on load balancing, the parallel calculation technology and a load balancing calculating method are used for solving the problems that in a fuzzy concept building process, the time complexity is excessively high and consumed time is excessively long.

Description

technical field [0001] The invention belongs to the technical fields of pattern recognition, machine learning and data mining, and in particular relates to a method for generating complete fuzzy form concepts, in particular to a parallel generation method for fuzzy concepts based on load balancing. Background technique [0002] Traditional formal concept analysis methods have certain limitations, and can only deal with formal contexts with Boolean-type attribute values. However, the complexity and diversity of the real world make it difficult to express many things with precise and definite concepts. For example, the height, fat and thinness of a person are difficult to express with definite concepts. Although the fuzzy form background can be transformed into a Boolean form background by using scale technology, this method requires human participation and selection of an appropriate scale, which leads to information being easily affected by subjective factors and resulting ...

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): G06F9/38G06F9/50G06N7/02
Inventor 张卓杜鹃王黎明柴玉梅
Owner ZHENGZHOU 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