Fuzzy pattern recognition technique for crack propagation on earplate connection of guyed mast under wind load

2017 ◽  
Vol 24 (11) ◽  
pp. e2010 ◽  
Author(s):  
Xueliang Wang ◽  
Weilian Qu ◽  
Hui Liu ◽  
Juan M. Caicedo ◽  
Xiaoli Wang ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Crack Propagation ◽  
Wind Load ◽  
Pattern Recognition Technique ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern ◽  
Guyed Mast ◽  
Recognition Technique

Multi-Axle Moving Train Loads Identification by Using Fuzzy Pattern Recognition Technique

2010 ◽  
Vol 29-32 ◽  
pp. 1307-1312 ◽  
Author(s):  
Yi Wang ◽  
Wei Lian Qu
Keyword(s):  
Pattern Recognition ◽  
Measurement Noise ◽  
Moving Loads ◽  
Recognition Method ◽  
Pattern Recognition Technique ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern ◽  
Moving Train ◽  
Recognition Technique ◽  
Design Construction

Identification of multi-axle moving loads on bridge is very important for bridge design, construction, and maintenance in engineering field. It is complicated and time consuming to identify the multi-axle moving train loads with general identification methods and far away from practical practice. Based on the theory of fuzzy pattern recognition, the fuzzy pattern recognition method for multi-axle moving train loads identification on bridge is presented in this paper. The multi-axle moving loads pattern library on a simply supported bridge is established with numerical methods. Effect of measurement noise on the proposed method is investigated in three situations. The results show that the proposed identification method has a certain resistance to measurement noise and can realize moving train loads identification with high accuracy.

Monitoring Drilling Wear States by a Fuzzy Pattern Recognition Technique

1988 ◽  
Vol 110 (3) ◽  
pp. 297-300 ◽  
Author(s):  
P. G. Li ◽  
S. M. Wu
Keyword(s):  
Pattern Recognition ◽  
Pattern Recognition Technique ◽  
New Approach ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern ◽  
On Line ◽  
Tool Replacement ◽  
Simulation Results ◽  
Recognition Technique ◽  
Fuzzy C Means Algorithm

This paper introduces a new approach for on-line monitoring of drill wear states by using a fuzzy C-means algorithm. Experimental and simulation results have shown that drill wear conditions can be represented by four fuzzy grades. They are: “initial,” “small,” “normal,” and “severe.” The grade “severe” is proposed to be used as the prediction of tool replacement. This fuzzy technique is more adequate than conventional pattern recognition technqiues.

A Variant Group Assignment Three Dimensional Model Using Pattern Recognition Technique

2019 ◽  
Vol 10 (6) ◽  
pp. 1382-1394
Author(s):  
R. Vijayalakshmi ◽  
V. K. Soma Sekhar Srinivas ◽  
E. Manjoolatha ◽  
G. Rajeswari ◽  
M. Sundaramurthy
Keyword(s):  
Pattern Recognition ◽  
Three Dimensional ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
Pattern Recognition Technique ◽  
Group Assignment ◽  
Recognition Technique

False color data imaging: A new pattern recognition technique for analyzing chromatographic profile data

1990 ◽  
Vol 41 (3) ◽  
pp. 288-295 ◽  
Author(s):  
Barry K. Lavine ◽  
Robert K. Vander Meer ◽  
Laurence Morel ◽  
Robert W. Gunderson ◽  
Jian Hwa Han ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Profile Data ◽  
Pattern Recognition Technique ◽  
False Color ◽  
Chromatographic Profile ◽  
Color Data ◽  
Recognition Technique

scholarly journals P-Path Minimum Distance Connectivity from Head Quarter to the Cities

2013 ◽  
Vol 4 (2) ◽  
pp. 280-294
Author(s):  
Revathi P ◽  
Suresh Babu C ◽  
Purusotham S ◽  
Sundara Murthy M
Keyword(s):  
Pattern Recognition ◽  
Minimum Distance ◽  
Search Algorithm ◽  
Distance Matrix ◽  
Pattern Recognition Technique ◽  
Individual Factor ◽  
Linear Polynomial ◽  
Higher Dimensional ◽  
Combinatorial Programming ◽  
Recognition Technique

Many Combinatorial programming problems are NP-hard (Non Linear Polynomial), and we consider one of them called P path minimum distance connectivity from head quarter to the cities. Let there be n cities and the distance matrix D(i, j, k) is given from ithcity to jthcity using kthfacility. There can be an individual factor which influences the distances/cost and that factor is represented as a facility k. We consider m<n cities are in cluster and to connect all the cities in subgroup (cluster) from others by using same facility k. The problem is to find minimum distance to connect all the cities from head quarter (say 1) threw p-paths subject to the above considerations. For this problem we developed a Pattern Recognition Technique based Lexi Search Algorithm, we programmed the proposed algorithm using C. we compared with the existed models and conclude that it suggested for solving the higher dimensional problems.

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