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Group Decision Making Based fuzzy pattern recognition Model for Lectotype Optimization of Offshore Platforms 1

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海洋工程：英文版 2003年第1期17卷 1-10页

作者：王建明陈守煜伏广涛侯召成 School of Civil and Hydraulic Engineering Dalian University of Technology

This paper develops a fuzzy pattern recognition model for group decision making to solve the problem of lectotype optimization of offshore platforms. The lack of data and the inexact or incomplete information for criteria are the main cause of uncertainty in the evaluation process, therefore it is necessary to integrate the judgments from different decision makers with different experience, knowledge and preference. This paper first uses a complementary principle based pairwise comparison method to obtain the subjective weight of the criteria from each decision maker. A fuzzy pattern recognition model is then developed to integrate the judgments from all the decision makers and the information from the criteria, under the supervision of the subjective weights. Finally a case study is given to show the efficiency and robustness of the proposed model.

关键词： offshore platform lectotype optimization group decision making fuzzy pattern recognition

Air Target fuzzy pattern recognition Threat-Judgment Model

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Journal of Systems Engineering and Electronics 2003年第1期14卷 41-46页

作者： Tong Youtang & Wang JianmingDalian University of Technology, Dalian 110624, P. R. China Dalian Naval Academy, Dalian 116018, P. R. China Dalian University of Technology Dalian 110624 P. R. China Dalian Universiry of Technology Dahan 110624 P. R. China Dalian Universiry of Technology Dahan 110624 P. R. China

Threat-judgment is a complicated fuzzy inference problem. Up to now no relevant unified theory and measur-ing standard have been developed. It is very difficult to establish a threat-judgment model with high reliability in the airdefense system for the naval warships. Air target threat level judgment is an important component in naval warship com-bat command decision-making systems. According to the threat level judgment of air targets during the air defense of sin-gle naval warship, a fuzzy pattern recognition model for judging the threat from air targets is established. Then an algo-rithm for identifying the parameters in the model is presented. The model has an adaptive feature and can dynamicallyupdate its parameters according to the state change of the attacking targets and the environment. The method presentedhere can be used for the air defense system threat judgment in the naval warships.

关键词： Air targets Threat judgment fuzzy pattern recognition fuzzy sets

Investigation and Application of Automatic Fingerprint Identification Based on fuzzy pattern recognition

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Journal of Beijing Institute of Technology 2004年第S1期13卷 49-53页

作者：杨阳康景利郭银景唐富华 School of Mechatronics Engineering Beijing Institute of Technology Beijing 100081China

Fingerprint image is a typical non-restraint image that has some uncertainty, which makes it difficult to perform identification using classical approach. Therefore, fuzzy pattern recognition is applied to match individual query by searching the entire template database. The fuzzy maximum subordinate principle is used to solve shift matching. Through experimenting and analyzing, the approximate principle fuzzy method is employed by selecting fuzzy characteristics and determining the similarity function to achieve the further accuracy. Theoretical and experimental results show this approach is effective and reasonable.

关键词： fuzzy pattern recognition fingerprint identification maximum subordinate principle approximate principle

Fabric Wrinkle Grade Assessment Based on fuzzy pattern recognition

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Journal of Donghua University(English Edition) 2006年第6期23卷 33-35页

作者：杨晓波 College of Information Zhejiang University of Finance & Economics

The basic principle of fuzzy pattern recognition is brief introduced firstly in this paper, which mainly includes fuzzy rules and fuzzy inference system. Then, the algorithm procedure of fuzzy pattern recognition is proposed. Finally, the application of Mamdani fuzzy model is introduced to evaluate fabric wrinkle grade in detail, and used the correlation coefficient between subject and object evaluation to verify the reliability of fuzzy pattern recognition. It shows the method of fuzzy pattern recognition needs not a large number of testing data and the accuracy of evaluation is up to 97.38%.

关键词： fuzzy pattern recognition fuzzy inference. wrinkle grade.

fuzzy pattern recognition System for Detection of Alga Distribution

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Semiconductor Photonics and Technology 2001年第2期7卷 80-83页

作者： ZHANG Shu-qing (School of Electr. Eng., Yanshan University, Qinhuangdao 066004, CHN) 燕山大学电气工程学院河北秦皇岛 066004

To realize the on-line measurement and make analysis on the density of algae and their cluster distribution, the fluorescent detection and fuzzy pattern recognition techniques are used. The principle of fluorescent fi... 详细信息

关键词： Algae Fluorescent fiber-optic detection fuzzy pattern recognition

Assessment of Structural Damage Condition Based on fuzzy pattern recognition

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International Journal of Plant Engineering and Management 2008年第1期13卷 10-19页

作者： WU Zi-yan ZHANG Yu School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi＇an 710072 P. R. China

This paper presents a new method of damage condition assessment that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness that are statistically nondescribable. In this method, healthy observations are used to construct a fury set representing sound performance characteristics. Additionally, the bounds on the similarities among the structural damage states are prescribed by using the state similarity matrix. Thus, an optimal group fuzzy sets representing damage states such as little, moderate, and severe damage can be inferred as an inverse problem from healthy observations only. The optimal group of damage fuzzy sets is used to classify a set of observations at any unknown state of damage using the principles of fitzzy pattern recognition based on an approximate principle . This method can be embedded into the system of Structural Health Monitoring （SHM） to give advice about structural maintenance and life predictio comes from Reference [ 9 ] for damage pattern recognition is presented n. Finally, a case and discussed. The study, which compared result illustrates our method is more effective and general, so it is very practical in engineering.

关键词： damage condition assessment fuzzy pattern recognition state similarity matrix approximate principle structural health monitoring

Structural Stress Identification Using fuzzy pattern recognition and Information Fusion Technique

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Journal of Civil Engineering and Architecture 2012年第4期6卷 479-488页

作者： Jun Teng Ting Zhang Wei Lu Shenzhen Graduate School Harbin Institute of Technology

In order to ensure the service security of space structures under wind load, the stress identification method based on the combination of fuzzy pattern recognition and information fusion technique is proposed, in which the measurements of limited strain sensors arranged on the structure are used. Firstly, the structure is divided into several regions according to the similarity and the most unfavorable region is selected to be the key region for stress identification, while the different numbers of the strain sensors are located on the key region and the normal regions; secondly, the different stress distributions of the key region are obtained based on the measurements of the strain sensors located on the key region and the normal regions separately, in which the fuzzy pattern recognition is used to identify the different stress distributions; thirdly, the stress distributions obtained by the measurements of sensors in normal regions are selected to calculate the synthesized stress distribution of the key region by D-S evidence theory; fourthly, the weighted fusion algorithm is used to assign the different fusion coefficients to the selected stress distributions obtained by the measurements of the normal regions and the key region, while the synthesized stress distribution of the key region can be obtained. Numerical study on a lattice shell model is carried out to validate the reliability of the proposed stress identification method. The simulated results indicate that the method can improve identification accuracy and be effective by different noise disturbing.

关键词： Stress identification fuzzy pattern recognition information fusion technique

Research of Ultrasonic Detection for Bonding Quality of Thin Plate Based on fuzzy pattern recognition

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Research of Ultrasonic Detection for Bonding Quality of Thin...

A Prototype for Diagnosis of Psoriasis in Traditional Chinese Medicine

The 2011 International Conference on Smart Materials and Nanotechnology in Engineering (ICSMCE2011)

作者： Wang Xiao-juan Zhang Ze Wang Hai-tao College of Electronic Information Engineering Inner Mongolia University

The application of fuzzy pattern recognition to ultrasonic detection for bonding quality of thin composite plate is studiedIn this paper, firstly, the fuzzy membership function between each characteristic and bonding quality is established by BP neural networkSimulation results show that this method is convenient, simple, and it conforms to the practical applicationAccordingly,the fuzzy subsets of standard modules and unknown bonding quality modules are establishedSecondly, the fuzzy pattern recognition algorithm, which is designed by the nearest principle as the judging standard to judge bonding quality, is givenExperimental results show that the algorithm is very exact for quantitative recognition of bonding quality.

关键词： Ultrasonic detection Membership function fuzzy pattern recognition Approach degree Nearest principle

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Computers, Materials & Continua 2022年第12期73卷 5197-5217页

作者： Hai Long Zhe Wang Yidi Cui Junhui Wang Bo Gao Chao Chen Yan Zhu Heinrich Herre Institute of Medical Informatics Statistics and EpidemiologyUniversity of LeipzigLeipzig04107Germany Zhejiang Academy of Traditional Chinese Medicine Hangzhou310007China Tongde Hospital of Zhejiang Province Hangzhou310007China Guang’anmen Hospital China Academy of Chinese Medical SciencesBeijing100053China Institute of Information on Traditional Chinese Medicine China Academy of Chinese Medical SciencesBeijing100700China

Psoriasis is a chronic,non-communicable,painful,disfiguring and disabling disease for which there is no cure,with great negative impact on patients’quality of life(QoL).Diagnosis and treatment with traditional Chinese medical technique based on syndrome differentiation has been used in practice for a long time and proven effective,though,up to now,there are only a few available studies about the use of semantic technologies and the knowledge systems that use Traditional Chinese Medicine(TCM)-syndrome differentiation for information retrieval and automated *** this paper we use semantic techniques based on ontologies to develop a prototypical system for the diagnosis of *** this purpose,a domain ontology is developed for syndrome differentiation of psoriasis vulgaris(PV).This ontology is founded on an adapted version of the general formal ontology(GFO),with the evidence-based clinical practice guideline of TCM for psoriasis vulgaris(Guideline 2013)as the primary data *** implemented prototype,called ONTOPV,contains this domain ontology and is aimed at a decision support system for diagnosis and treatment of *** system uses a case-database for Case Based Reasoning(CBR),combined with fuzzy pattern *** results show that the ONTOPV realizes the basic functionalities of data collection,querying,browsing and navigation,and supports rule-based knowledge reasoning,and integrates fuzzy pattern *** can provide users with clinical decision support for TCM syndrome differentiation in diagnosis of psoriasis.

关键词： Clinical guideline knowledge base GFO ontology TCM CBR fuzzy pattern recognition psoriasis vulgaris