Water scarcity and environment deterioration have become main constraints to sustainable economic and social development.Scientifically assessing Water Resources Carrying Capacity(WRCC)is essential for the optimal all...Water scarcity and environment deterioration have become main constraints to sustainable economic and social development.Scientifically assessing Water Resources Carrying Capacity(WRCC)is essential for the optimal allocation of regional water resources.The hilly area at the northern foot of Yanshan Mountains is a key water conservation zone and an important water source for Beijing,Tianjin and Hebei.Grasping the current status and temporal trends of water quality and WRCC in representative small watersheds within this region is crucial for supporting rational water resources allocation and environment protection efforts.This study focuses on Pingquan City,a typical watershed in northern Hebei Province.Firstly,evaluation index systems for surface water quality,groundwater quality and WRCC were estab-lished based on the Pressure-State-Response(PSR)framework.Then,comprehensive evaluations of water quality and WRCC at the sub-watershed scale were conducted using the Varying Fuzzy Pattern Recogni-tion(VFPR)model.Finally,the rationality of the evaluation results was verified,and future scenarios were projected.Results showed that:(1)The average comprehensive evaluation scores for surface water and groundwater quality in the sub-watersheds were 1.44 and 1.46,respectively,indicating that both met the national Class II water quality standard and reflected a high-quality water environment.(2)From 2010 to 2020,the region's WRCC steadily improved,with scores rising from 2.99 to 2.83 and an average of 2.90,suggesting effective water resources management in Pingquan City.(3)According to scenario-based predic-tion,WRCC may slightly decline between 2025 and 2030,reaching 2.92 and 2.94,respectively,relative to 2020 levels.Therefore,future efforts should focus on strengthening scientific management and promoting the efficient use of water resources.Proactive measures are necessary to mitigate emerging contradiction and ensure the long-term stability and sustainability of the water resources system in the region.The evalua-tion system and spatiotemporal evolution patterns proposed in this study can provide a scientific basis for refined water resource management and ecological conservation in similar hilly areas.展开更多
The concept of the degree of similarity between interval-valued intuitionistic fuzzy sets （IVIFSs） is introduced, and some distance measures between IVIFSs are defined based on the Hamming distance, the normalized H...The concept of the degree of similarity between interval-valued intuitionistic fuzzy sets （IVIFSs） is introduced, and some distance measures between IVIFSs are defined based on the Hamming distance, the normalized Hamming distance, the weighted Hamming distance, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance, etc. Then, by combining the Hausdorff metric with the Hamming distance, the Euclidean distance and their weighted versions, two other similarity measures between IVIFSs, i. e., the weighted Hamming distance based on the Hausdorff metric and the weighted Euclidean distance based on the Hausdorff metric, are defined, and then some of their properties are studied. Finally, based on these distance measures, some similarity measures between IVIFSs are defined, and the similarity measures are applied to pattern recognitions with interval-valued intuitionistic fuzzy information.展开更多
For the problems occurring in a least square method model, a fuzzy model, and a neural network model for flatness pattern recognition, a fuzzy neural network model for flatness pattern recognition with only three-inpu...For the problems occurring in a least square method model, a fuzzy model, and a neural network model for flatness pattern recognition, a fuzzy neural network model for flatness pattern recognition with only three-input and three output signals was proposed with Legendre orthodoxy polynomial as basic pattern, based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm. The model not only had definite physical meanings in its inner nodes, but also had strong self-adaptability, anti interference ability, high recognition precision, and high velocity, thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient, practical, and novel method for flatness pattern recognition.展开更多
A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference cha...A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference characteristics.However,it suffers from heavy computational overhead and large execution time.The paper,therefore,uses a novel fast discrete sparse S-transform(SST)suitable for extracting time frequency response to monitor non-stationary signal parameters,which can be ultimately used for disturbance detection,and their pattern classification.From the sparse S-transform matrix,some relevant features have been extracted which are used to distinguish among different non-stationary signals by a fuzzy decision tree based classifier.This algorithm is robust under noisy conditions.Various power quality as well as chirp signals have been simulated and tested with the proposed technique in noisy conditions as well.Some real time mechanical faulty signals have been collected to demonstrate the efficiency of the proposed algorithm.All the simulation results imply that the proposed technique is very much efficient.展开更多
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
In order to recognize the jamming pattern in anti-jamming, a novel fuzzy jamming recognition method based on statistic parameters of received signal’s power spectral density (PSD) is proposed. It exploits PSD’s shap...In order to recognize the jamming pattern in anti-jamming, a novel fuzzy jamming recognition method based on statistic parameters of received signal’s power spectral density (PSD) is proposed. It exploits PSD’s shape factor and skewness of received signal as classified characters of jamming pattern. After the mean center and variance of each jamming pattern are calculated by using some jamming samples, an exponential fuzzy membership function is used to calculate the membership value of the recognized sample. Finally, the jamming pattern of received signal is recognized by the maximum membership principle. The simulation results show that the proposed algorithm can recognize common eight jamming patterns accurately.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
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
Reliability parameter selection is very important in the period of equipment project design and demonstration. In this paper, the problem in selecting the reliability parameters and their number is proposed. In order ...Reliability parameter selection is very important in the period of equipment project design and demonstration. In this paper, the problem in selecting the reliability parameters and their number is proposed. In order to solve this problem, the thought of text mining is used to extract the feature and curtail feature sets from text data firstly, and frequent pattern tree （FPT） of the text data is constructed to reason frequent item-set between the key factors by frequent patter growth （FPC） algorithm. Then on the basis of fuzzy Bayesian network （FBN） and sample distribution, this paper fuzzifies the key attributes, which forms associated relationship in frequent item-sets and their main parameters, eliminates the subjective influence factors and obtains condition mutual information and maximum weight directed tree among all the attribute variables. Furthermore, the hybrid model is established by reason fuzzy prior probability and contingent probability and concluding parameter learning method. Finally, the example indicates the model is believable and effective.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
This paper combines fuzzy set theory with ART neural net-work , and demonstrates some important properties of the fuzzy ART neural net-work algorithm. The results from application on a ball bearing diagnosis indicat...This paper combines fuzzy set theory with ART neural net-work , and demonstrates some important properties of the fuzzy ART neural net-work algorithm. The results from application on a ball bearing diagnosis indicate that a fuzzy ART neural net-work has an effect of fast stable recognition for fuzzy patterns.展开更多
The choice of a fuzzy partitioning is crucial to the performance of a fuzzy system based on if-then rules. However, most of the existing methods are complicated or lead ,o too many subspaces, which is unfit for the ap...The choice of a fuzzy partitioning is crucial to the performance of a fuzzy system based on if-then rules. However, most of the existing methods are complicated or lead ,o too many subspaces, which is unfit for the applications of pattern classification. A simple but effective clustering approach is proposed in this paper, which obtains a set of compact subspaces and is applicable for classification problems with higher dimensional feature. Its effectiveness is demonstrated by the experimental results.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
This paper introduces concepts of symptom vector and fuzzy symptom vector forspacecraft condition recognition and fault diagnosis,defines an operator and suggests a fuzzy pat-tern recognition method of fault diagnosis...This paper introduces concepts of symptom vector and fuzzy symptom vector forspacecraft condition recognition and fault diagnosis,defines an operator and suggests a fuzzy pat-tern recognition method of fault diagnosis for spacecraft.This method is verified by examples andresults are checked from an expert system.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
The tectonic stress patterns were determined by a fuzzy comprehensive assessment method. Data of in-situ survey and fault information were utilized in the method. First, by making pressure and tension in the direction...The tectonic stress patterns were determined by a fuzzy comprehensive assessment method. Data of in-situ survey and fault information were utilized in the method. First, by making pressure and tension in the directions of along-river, cross-river, shear clockwise, and shear counterclockwise , 26 types of tectonic stress patterns were presented. And the stress vector of each pattern was obtained with FE software by taking unit displacement as boundary load. Then, by taking the 26 types of tectonic stress patterns as index set and 3 main stresses as factor set and choosing various operators, comparison of directions of computational stress vector and survey stress vector was made and the most possible tectonic stress pattern was obtained. Taking the 26 types of tectonic stress patterns as index set and strike angle as factor set, comparison of relationships between formation of fault and tectonic stress was made,and the tectonic stress patterns were assessed with known fault information. By summarizing the above assessment results, the most impossible tectonic stress pattern was obtained . Finally an engineering case was quoted to validate that the method is more feasible and reliable than traditional empirical method.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
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
Basic block is the foundation of clothing construction design because it is the media between body and clothes and the fitness of clothes should be based on the accuracy of basic block. That needs us to recognize body...Basic block is the foundation of clothing construction design because it is the media between body and clothes and the fitness of clothes should be based on the accuracy of basic block. That needs us to recognize body not to record it. This paper reports the Algorithm of woman body fuzzy pattern recognition. It is organized in three sections:(i) extracting woman body feature; (ii) establishing membership functions of feature indexes;(iii) presenting an Algorithm for woman body fuzzy pattern recognition by example.展开更多
基金financially supported by China Geological Survey Project(No.DD20220954)Open Funding Project of the Key Laboratory of Groundwater Sciences and Engineering,Ministry of Natural Resources(No.SK202301-4)+2 种基金Science and Technology Innovation Foundation of Comprehensive Survey&Command Center for Natural Resources(No.KC20240003)Yanzhao Shanshui Science and Innovation Fund of Langfang Integrated Natural Resources Survey Center,China Geological Survey(No.YZSSJJ202401-001)Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements(No.2022KFKTC009).
文摘Water scarcity and environment deterioration have become main constraints to sustainable economic and social development.Scientifically assessing Water Resources Carrying Capacity(WRCC)is essential for the optimal allocation of regional water resources.The hilly area at the northern foot of Yanshan Mountains is a key water conservation zone and an important water source for Beijing,Tianjin and Hebei.Grasping the current status and temporal trends of water quality and WRCC in representative small watersheds within this region is crucial for supporting rational water resources allocation and environment protection efforts.This study focuses on Pingquan City,a typical watershed in northern Hebei Province.Firstly,evaluation index systems for surface water quality,groundwater quality and WRCC were estab-lished based on the Pressure-State-Response(PSR)framework.Then,comprehensive evaluations of water quality and WRCC at the sub-watershed scale were conducted using the Varying Fuzzy Pattern Recogni-tion(VFPR)model.Finally,the rationality of the evaluation results was verified,and future scenarios were projected.Results showed that:(1)The average comprehensive evaluation scores for surface water and groundwater quality in the sub-watersheds were 1.44 and 1.46,respectively,indicating that both met the national Class II water quality standard and reflected a high-quality water environment.(2)From 2010 to 2020,the region's WRCC steadily improved,with scores rising from 2.99 to 2.83 and an average of 2.90,suggesting effective water resources management in Pingquan City.(3)According to scenario-based predic-tion,WRCC may slightly decline between 2025 and 2030,reaching 2.92 and 2.94,respectively,relative to 2020 levels.Therefore,future efforts should focus on strengthening scientific management and promoting the efficient use of water resources.Proactive measures are necessary to mitigate emerging contradiction and ensure the long-term stability and sustainability of the water resources system in the region.The evalua-tion system and spatiotemporal evolution patterns proposed in this study can provide a scientific basis for refined water resource management and ecological conservation in similar hilly areas.
基金The National Natural Science Foundation of China (No70571087)the National Science Fund for Distinguished Young Scholarsof China (No70625005)
文摘The concept of the degree of similarity between interval-valued intuitionistic fuzzy sets （IVIFSs） is introduced, and some distance measures between IVIFSs are defined based on the Hamming distance, the normalized Hamming distance, the weighted Hamming distance, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance, etc. Then, by combining the Hausdorff metric with the Hamming distance, the Euclidean distance and their weighted versions, two other similarity measures between IVIFSs, i. e., the weighted Hamming distance based on the Hausdorff metric and the weighted Euclidean distance based on the Hausdorff metric, are defined, and then some of their properties are studied. Finally, based on these distance measures, some similarity measures between IVIFSs are defined, and the similarity measures are applied to pattern recognitions with interval-valued intuitionistic fuzzy information.
基金Item Sponsored by National Natural Science Foundation of China and Shanghai Baosteel Group Co(50675186)Provincial Natural Science Foundation of Hebei Province of China(E2006001038)
文摘For the problems occurring in a least square method model, a fuzzy model, and a neural network model for flatness pattern recognition, a fuzzy neural network model for flatness pattern recognition with only three-input and three output signals was proposed with Legendre orthodoxy polynomial as basic pattern, based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm. The model not only had definite physical meanings in its inner nodes, but also had strong self-adaptability, anti interference ability, high recognition precision, and high velocity, thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient, practical, and novel method for flatness pattern recognition.
文摘A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference characteristics.However,it suffers from heavy computational overhead and large execution time.The paper,therefore,uses a novel fast discrete sparse S-transform(SST)suitable for extracting time frequency response to monitor non-stationary signal parameters,which can be ultimately used for disturbance detection,and their pattern classification.From the sparse S-transform matrix,some relevant features have been extracted which are used to distinguish among different non-stationary signals by a fuzzy decision tree based classifier.This algorithm is robust under noisy conditions.Various power quality as well as chirp signals have been simulated and tested with the proposed technique in noisy conditions as well.Some real time mechanical faulty signals have been collected to demonstrate the efficiency of the proposed algorithm.All the simulation results imply that the proposed technique is very much efficient.
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.
基金Sponsored by National Nature Science Foundation of China ( 61072078)China Postdoctoral Science Foundation Funded Project ( 20090461426)Jiangsu Planned Projects for Postdoctoral Research Funds ( 0902039C)
文摘In order to recognize the jamming pattern in anti-jamming, a novel fuzzy jamming recognition method based on statistic parameters of received signal’s power spectral density (PSD) is proposed. It exploits PSD’s shape factor and skewness of received signal as classified characters of jamming pattern. After the mean center and variance of each jamming pattern are calculated by using some jamming samples, an exponential fuzzy membership function is used to calculate the membership value of the recognized sample. Finally, the jamming pattern of received signal is recognized by the maximum membership principle. The simulation results show that the proposed algorithm can recognize common eight jamming patterns accurately.
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.
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.
基金the Weapon Equipment Beforehand Research Foundation of China(No.9140A19030314JB35275)the Army Technology Element Foundation of China(No.A157167)
文摘Reliability parameter selection is very important in the period of equipment project design and demonstration. In this paper, the problem in selecting the reliability parameters and their number is proposed. In order to solve this problem, the thought of text mining is used to extract the feature and curtail feature sets from text data firstly, and frequent pattern tree （FPT） of the text data is constructed to reason frequent item-set between the key factors by frequent patter growth （FPC） algorithm. Then on the basis of fuzzy Bayesian network （FBN） and sample distribution, this paper fuzzifies the key attributes, which forms associated relationship in frequent item-sets and their main parameters, eliminates the subjective influence factors and obtains condition mutual information and maximum weight directed tree among all the attribute variables. Furthermore, the hybrid model is established by reason fuzzy prior probability and contingent probability and concluding parameter learning method. Finally, the example indicates the model is believable and effective.
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.
文摘This paper combines fuzzy set theory with ART neural net-work , and demonstrates some important properties of the fuzzy ART neural net-work algorithm. The results from application on a ball bearing diagnosis indicate that a fuzzy ART neural net-work has an effect of fast stable recognition for fuzzy patterns.
文摘The choice of a fuzzy partitioning is crucial to the performance of a fuzzy system based on if-then rules. However, most of the existing methods are complicated or lead ,o too many subspaces, which is unfit for the applications of pattern classification. A simple but effective clustering approach is proposed in this paper, which obtains a set of compact subspaces and is applicable for classification problems with higher dimensional feature. Its effectiveness is demonstrated by the experimental results.
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 National Natural Science Foundation of China and National Project No.863
文摘This paper introduces concepts of symptom vector and fuzzy symptom vector forspacecraft condition recognition and fault diagnosis,defines an operator and suggests a fuzzy pat-tern recognition method of fault diagnosis for spacecraft.This method is verified by examples andresults are checked from an expert system.
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.
文摘The tectonic stress patterns were determined by a fuzzy comprehensive assessment method. Data of in-situ survey and fault information were utilized in the method. First, by making pressure and tension in the directions of along-river, cross-river, shear clockwise, and shear counterclockwise , 26 types of tectonic stress patterns were presented. And the stress vector of each pattern was obtained with FE software by taking unit displacement as boundary load. Then, by taking the 26 types of tectonic stress patterns as index set and 3 main stresses as factor set and choosing various operators, comparison of directions of computational stress vector and survey stress vector was made and the most possible tectonic stress pattern was obtained. Taking the 26 types of tectonic stress patterns as index set and strike angle as factor set, comparison of relationships between formation of fault and tectonic stress was made,and the tectonic stress patterns were assessed with known fault information. By summarizing the above assessment results, the most impossible tectonic stress pattern was obtained . Finally an engineering case was quoted to validate that the method is more feasible and reliable than traditional empirical method.
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Basic block is the foundation of clothing construction design because it is the media between body and clothes and the fitness of clothes should be based on the accuracy of basic block. That needs us to recognize body not to record it. This paper reports the Algorithm of woman body fuzzy pattern recognition. It is organized in three sections:(i) extracting woman body feature; (ii) establishing membership functions of feature indexes;(iii) presenting an Algorithm for woman body fuzzy pattern recognition by example.
