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 crit...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.展开更多
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 indiv...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.展开更多
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 whic...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.展开更多
From the perspective of geological zone selection for coalbed methane(CBM) development, the evaluation parameters(covering geological conditions and production conditions) of geological sweetspot for CBM development a...From the perspective of geological zone selection for coalbed methane(CBM) development, the evaluation parameters(covering geological conditions and production conditions) of geological sweetspot for CBM development are determined, and the evaluation index system of geological sweetspot for CBM development is established. On this basis, the fuzzy pattern recognition(FPR) model of geological sweetspot for CBM development is built. The model is applied to evaluate four units of No.3 Coal Seam in the Fanzhuang Block, southern Qinshui Basin, China. The evaluation results are consistent with the actual development effect and the existing research results, which verifies the rationality and reliability of the FPR model. The research shows that the proposed FPR model of geological sweetspot for CBM development does not involve parameter weighting which leads to uncertainties in the results of the conventional models such as analytic hierarchy process and multi-level fuzzy synthesis judgment, and features a simple computation without the construction of multi-level judgment matrix. The FPR model provides reliable results to support the efficient development of CBM.展开更多
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 reliabili...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.展开更多
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 p...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%.展开更多
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...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 fiber-optic detection is given as well as the method of fuzzy feature extraction using a class of neural network.展开更多
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, ...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.展开更多
Fuzzy pattern recognition has been employed to identify some atlas and images of the unevenness of carbide in tool steel. Three models have been constructed. These models were based on fuzzy mathematics theory, as wel...Fuzzy pattern recognition has been employed to identify some atlas and images of the unevenness of carbide in tool steel. Three models have been constructed. These models were based on fuzzy mathematics theory, as well as fuzzy pattern recognition method. Distribution rule of the unevenness of eutectic carbide in ledeburite steel is proposed in these models respectively.展开更多
Water quality assessment of lakes is important to determine functional zones of water use.Considering the fuzziness during the partitioning process for lake water quality in an arid area,a multiplex model of fuzzy clu...Water quality assessment of lakes is important to determine functional zones of water use.Considering the fuzziness during the partitioning process for lake water quality in an arid area,a multiplex model of fuzzy clustering with pattern recognition was developed by integrating transitive closure method,ISODATA algorithm in fuzzy clustering and fuzzy pattern recognition.The model was applied to partition the Ulansuhai Lake,a typical shallow lake in arid climate zone in the west part of Inner Mongolia,China and grade the condition of water quality divisions.The results showed that the partition well matched the real conditions of the lake,and the method has been proved accurate in the application.展开更多
The risk recognition model for preventing and monitoring the Coronary Heart Diseases (CHD) in the aged is proposed, which is based on the testing results of four indexes and includes Low Density Lipoprotein (LDL), Tot...The risk recognition model for preventing and monitoring the Coronary Heart Diseases (CHD) in the aged is proposed, which is based on the testing results of four indexes and includes Low Density Lipoprotein (LDL), Total Cholesterol (TC), Triglyceridemia (TG)and age. Some people who took the health checkup in Shanghai Xinhua Hospital are classified into 3 groups,and each group is associated with prevalence risk of contracting CHD. Then the fuzzy recognition method is applied to evaluate the risk of CHD. The accuracy rate is up to 85%. The model is applicable to not only analysis of risk in medical but also analysis of risk in finance, insurance and some other fields.展开更多
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 Chines...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 reasoning.In this paper we use semantic techniques based on ontologies to develop a prototypical system for the diagnosis of Psoriasis.For 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 sources.The implemented prototype,called ONTOPV,contains this domain ontology and is aimed at a decision support system for diagnosis and treatment of PV.This system uses a case-database for Case Based Reasoning(CBR),combined with fuzzy pattern recognition.Experimental 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 recognition.It can provide users with clinical decision support for TCM syndrome differentiation in diagnosis of psoriasis.展开更多
Chinese stock market is a developing one. In the present stages, to control scientifically the expansion speed and avoid drastic fluctuations is an important problem. Through analysis of plenty of data of SSE(Shanghai...Chinese stock market is a developing one. In the present stages, to control scientifically the expansion speed and avoid drastic fluctuations is an important problem. Through analysis of plenty of data of SSE(Shanghai Stock Exchange) Index and relevant economic quotas, we find that the problem of predicting SSE Index is a typical multi variable, nonlinear one. On the basis of the analysis, we apply the technology of fuzzy pattern recognition, to the optimum pattern division of SSE Index's time alignments from Jan. of 1993 to Dec. of 1997, and get a balanced pattern of the stock index fluctuation. At the same time, by using database technology, we find the optimum expansion speed of Shanghai stock, which can make SSE Index fluctuate steadily within the balanced area. We verified this model with the latest data and found it coincides with the reality perfectly. So it has the practical value and provides the policy makers with a scientific basis in controlling the expansion pace.展开更多
Phase Doppler anemometry(PDA) is very sensitive to the shape of testing particles, which is based on sphericity assumption and Mie’s theory. In practice, there exists effectiveness of non sphericity and the response ...Phase Doppler anemometry(PDA) is very sensitive to the shape of testing particles, which is based on sphericity assumption and Mie’s theory. In practice, there exists effectiveness of non sphericity and the response of PDA system deviates from the theoretical prediction. In this paper, the statistic characteristics of PDA signal are analyzed and a method of identifying and quantifying irregular particles is proposed. It is concluded that phase difference of PDA signal for irregular particles is an unbiased estimation for spherical particles.展开更多
文摘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.
文摘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.
文摘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.
基金Key Project of China National Natural Science Foundation (42230814,52234002)Research Program Foundation of Key Laboratory of Tectonics and Petroleum Resources (China University of Geosciences),Ministry of Education (TPR-2022-17)。
文摘From the perspective of geological zone selection for coalbed methane(CBM) development, the evaluation parameters(covering geological conditions and production conditions) of geological sweetspot for CBM development are determined, and the evaluation index system of geological sweetspot for CBM development is established. On this basis, the fuzzy pattern recognition(FPR) model of geological sweetspot for CBM development is built. The model is applied to evaluate four units of No.3 Coal Seam in the Fanzhuang Block, southern Qinshui Basin, China. The evaluation results are consistent with the actual development effect and the existing research results, which verifies the rationality and reliability of the FPR model. The research shows that the proposed FPR model of geological sweetspot for CBM development does not involve parameter weighting which leads to uncertainties in the results of the conventional models such as analytic hierarchy process and multi-level fuzzy synthesis judgment, and features a simple computation without the construction of multi-level judgment matrix. The FPR model provides reliable results to support the efficient development of CBM.
基金This project was supported by the National Defense Foundation of China(40108070103)
文摘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.
基金Supported by the Research Fund for the Doctorial Program of Higher Education of China (No.99025508)
文摘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%.
文摘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 fiber-optic detection is given as well as the method of fuzzy feature extraction using a class of neural network.
基金This paper is supported by the National High Technology Research and Development Program ("863" Program) of China under Grant No.2006AA04Z437
文摘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.
文摘Fuzzy pattern recognition has been employed to identify some atlas and images of the unevenness of carbide in tool steel. Three models have been constructed. These models were based on fuzzy mathematics theory, as well as fuzzy pattern recognition method. Distribution rule of the unevenness of eutectic carbide in ledeburite steel is proposed in these models respectively.
基金Supported by the National Natural Science Foundation of China (No.50269001, 50569002, 50669004)Natural Science Foundation of Inner Mongolia (No.200208020512, 200711020604)The Key Scientific and Technologic Project of the 10th Five-Year Plan of Inner Mongolia (No.20010103)
文摘Water quality assessment of lakes is important to determine functional zones of water use.Considering the fuzziness during the partitioning process for lake water quality in an arid area,a multiplex model of fuzzy clustering with pattern recognition was developed by integrating transitive closure method,ISODATA algorithm in fuzzy clustering and fuzzy pattern recognition.The model was applied to partition the Ulansuhai Lake,a typical shallow lake in arid climate zone in the west part of Inner Mongolia,China and grade the condition of water quality divisions.The results showed that the partition well matched the real conditions of the lake,and the method has been proved accurate in the application.
基金Projects supported by Swiss Re-Fudan Research FoundationShanghai Key-point Science & Constructive project
文摘The risk recognition model for preventing and monitoring the Coronary Heart Diseases (CHD) in the aged is proposed, which is based on the testing results of four indexes and includes Low Density Lipoprotein (LDL), Total Cholesterol (TC), Triglyceridemia (TG)and age. Some people who took the health checkup in Shanghai Xinhua Hospital are classified into 3 groups,and each group is associated with prevalence risk of contracting CHD. Then the fuzzy recognition method is applied to evaluate the risk of CHD. The accuracy rate is up to 85%. The model is applicable to not only analysis of risk in medical but also analysis of risk in finance, insurance and some other fields.
基金This work was partially supported by the National Natural Science Foundation of China(No.82174534)the China Academy of Chinese Medical Sciences Innovation Fund(No.CI2021A05306)the Fundamental Research Funds for the Central Public Welfare Research Institutes(Nos.ZZ13-YQ-021,ZZ13-YQ-126,ZZ150314).
文摘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 reasoning.In this paper we use semantic techniques based on ontologies to develop a prototypical system for the diagnosis of Psoriasis.For 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 sources.The implemented prototype,called ONTOPV,contains this domain ontology and is aimed at a decision support system for diagnosis and treatment of PV.This system uses a case-database for Case Based Reasoning(CBR),combined with fuzzy pattern recognition.Experimental 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 recognition.It can provide users with clinical decision support for TCM syndrome differentiation in diagnosis of psoriasis.
文摘Chinese stock market is a developing one. In the present stages, to control scientifically the expansion speed and avoid drastic fluctuations is an important problem. Through analysis of plenty of data of SSE(Shanghai Stock Exchange) Index and relevant economic quotas, we find that the problem of predicting SSE Index is a typical multi variable, nonlinear one. On the basis of the analysis, we apply the technology of fuzzy pattern recognition, to the optimum pattern division of SSE Index's time alignments from Jan. of 1993 to Dec. of 1997, and get a balanced pattern of the stock index fluctuation. At the same time, by using database technology, we find the optimum expansion speed of Shanghai stock, which can make SSE Index fluctuate steadily within the balanced area. We verified this model with the latest data and found it coincides with the reality perfectly. So it has the practical value and provides the policy makers with a scientific basis in controlling the expansion pace.
文摘Phase Doppler anemometry(PDA) is very sensitive to the shape of testing particles, which is based on sphericity assumption and Mie’s theory. In practice, there exists effectiveness of non sphericity and the response of PDA system deviates from the theoretical prediction. In this paper, the statistic characteristics of PDA signal are analyzed and a method of identifying and quantifying irregular particles is proposed. It is concluded that phase difference of PDA signal for irregular particles is an unbiased estimation for spherical particles.