Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies are presented in order to identify and separate geochemi...Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies are presented in order to identify and separate geochemical anomalies. The U-statistic method is one of the most important structural methods and is a kind of weighted mean that surrounding points of samples are considered in U value determination. However, it is able to separate the different anomalies based on only one variable. The main aim of the presented study is development of this method in a multivariate mode. For this purpose, U-statistic method should be combined with a multivariate method which devotes a new value to each sample based on several variables. Therefore, at the first step, the optimum p is calculated in p-norm distance and then U-statistic method is applied on p-norm distance values of the samples because p-norm distance is calculated based on several variables. This method is a combination of efficient U-statistic method and p-norm distance and is used for the first time in this research. Results show that p-norm distance of p=2(Euclidean distance) in the case of a fact that Au and As can be considered optimized p-norm distance with the lowest error. The samples indicated by the combination of these methods as anomalous are more regular, less dispersed and more accurate than using just the U-statistic or other nonstructural methods such as Mahalanobis distance. Also it was observed that the combination results are closely associated with the defined Au ore indication within the studied area. Finally, univariate and bivariate geochemical anomaly maps are provided for Au and As, which have been respectively prepared using U-statistic and its combination with Euclidean distance method.展开更多
The aim of this paper is to discuss the approximate rea- soning problems with interval-valued fuzzy environments based on the fully implicational idea. First, this paper constructs a class of interval-valued fuzzy imp...The aim of this paper is to discuss the approximate rea- soning problems with interval-valued fuzzy environments based on the fully implicational idea. First, this paper constructs a class of interval-valued fuzzy implications by means of a type of impli- cations and a parameter on the unit interval, then uses them to establish fully implicational reasoning methods for interval-valued fuzzy modus ponens （IFMP） and interval-valued fuzzy modus tel- lens （IFMT） problems. At the same time the reversibility properties of these methods are analyzed and the reversible conditions are given. It is shown that the existing unified forms of α-triple I （the abbreviation of triple implications） methods for FMP and FMT can be seen as the particular cases of our methods for IFMP and IFMT.展开更多
The basic"current"statistical model and adaptive Kalman filter algorithm can not track a weakly maneuvering target precisely,though it has good estimate accuracy for strongly maneuvering target.In order to s...The basic"current"statistical model and adaptive Kalman filter algorithm can not track a weakly maneuvering target precisely,though it has good estimate accuracy for strongly maneuvering target.In order to solve this problem,a novel nonlinear fuzzy membership function was presented to adjust the upper and lower limit of target acceleration adaptively,and then the validity of the new algorithm for feeblish maneuvering target was proved in theory.At last,the computer simulation experiments indicated that the new algorithm has a great advantage over the basic"current"statistical model and adaptive algorithm.展开更多
Cables that have been in service for over 20 years in Shanghai, a city with abundant surface water, failed more frequently and induced different cable accidents. This necessitates researches on the insulation aging st...Cables that have been in service for over 20 years in Shanghai, a city with abundant surface water, failed more frequently and induced different cable accidents. This necessitates researches on the insulation aging state of cables working in special circumstances. We performed multi-parameter tests with samples from about 300 cable lines in Shanghai. The tests included water tree investigation, tensile test, dielectric spectroscopy test, thermogravimetric analysis (TGA), fourier transform infrared spectroscopy (FTIR), and electrical aging test. Then, we carried out regression analysis between every two test parameters. Moreover, through two-sample t-Test and analysis of va- riance (ANOVA) of each test parameter, we analyzed the influences of cable-laying method and sampling section on the degradation of cable insulation respectively. Furthermore, the test parameters which have strong correlation in the regression analysis or significant differ- ences in the t-Test or ANOVA analysis were determined to be the ones identifying the XLPE cable insulation aging state. The thresholds for distinguishing insulation aging states had been also obtained with the aid of statistical analysis and fuzzy clustering. Based on the fuzzy in- ference, we established a cable insulation aging diagnosis model using the intensity transfer method. The results of regression analysis indicate that the degradation of cable insulation accelerates as the degree of in-service aging increases. This validates the rule that the in- crease of microscopic imperfections in solid material enhances the dielectric breakdown strength. The results of the two-sample t-Test and the ANOVA indicate that the direct-buried cables are more sensitive to insulation degradation than duct cables. This confirms that the tensile strength and breakdown strength are reliable functional parameters in cable insulation evaluations. A case study further indicates that the proposed diagnosis model based on the fuzzy inference can reflect the comprehensive aging state of cable insulation well, and that the cable service time has no correlation with the insulation aging state.展开更多
The fuzzy integration evaluation method （FIEM） is studied in order to select the best orbital elements from the multi-group initial orbits determined by a satellite TT＆C （Tracking, Telemetry and Control） center w...The fuzzy integration evaluation method （FIEM） is studied in order to select the best orbital elements from the multi-group initial orbits determined by a satellite TT＆C （Tracking, Telemetry and Control） center with all kinds of data sources. By employing FIEM together with the experience of TT＆C experts, the index system to evaluate the selection of the best initial orbits is established after the data sources and orbit determination theories are studied. Besides, the concrete steps in employing the method are presented. Moreover, by taking the objects to be evaluated as evaluation experts, the problem of how to generate evaluation matrices is solved. Through practical application, the method to select the best initial orbital elements has been proved to be flexible and effective The originality of the method is to find a new evaluation criterion （comparing the actually tracked orbits） replacing the traditional one （comparing the nominal orbits） for selecting the best orbital elements.展开更多
An extended compromise ratio method（CRM） based on fuzzy distances is developed to solve fuzzy multi-attribute group decision making problems in which weights of attributes and ratings of alternatives on attributes a...An extended compromise ratio method（CRM） based on fuzzy distances is developed to solve fuzzy multi-attribute group decision making problems in which weights of attributes and ratings of alternatives on attributes are expressed with values of linguistic variables parameterized using triangular fuzzy numbers.A compromise solution is determined by introducing the ranking index based on the concept that the chosen alternative should be as close as possible to the positive ideal solution and as far away from the negative ideal solution as possible simultaneously.This proposed method is compared with other existing methods to show its feasibility and effectiveness and illustrated with an example of the military route selection problem as one of the possible applications.展开更多
The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, d...The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, data with noise, data with mixture of heterogeneous cluster prototypes, asymmetric data, etc. Based on the Mercer kernel, FKCM clustering algorithm is derived from FCM algorithm united with kernel method. The results of experiments with the synthetic and real data show that the FKCM clustering algorithm is universality and can effectively unsupervised analyze datasets with variform structures in contrast to FCM algorithm. It is can be imagined that kernel-based clustering algorithm is one of important research direction of fuzzy clustering analysis.展开更多
The selection of refracturing candidate is one of the most important jobs faced by oilfield engineers. However, due to the complicated multi-parameter relationships and their comprehensive influence, the selection of ...The selection of refracturing candidate is one of the most important jobs faced by oilfield engineers. However, due to the complicated multi-parameter relationships and their comprehensive influence, the selection of refracturing candidate is often very difficult. In this paper, a novel approach combining data analysis techniques and fuzzy clustering was proposed to select refracturing candidate. First, the analysis techniques were used to quantitatively calculate the weight coefficient and determine the key factors. Then, the idealized refracturing well was established by considering the main factors. Fuzzy clustering was applied to evaluate refracturing potential. Finally, reservoirs numerical simulation was used to further evaluate reservoirs energy and material basis of the optimum refracturing candidates. The hybrid method has been successfully applied to a tight oil reservoir in China. The average steady production was 15.8 t/d after refracturing treatment, increasing significantly compared with previous status. The research results can guide the development of tight oil and gas reservoirs effectively.展开更多
Phosphorus is an essential element in agricultural production and chemical industry. However, since the risk of casualties and economic loss by mining accidents, the application of clean and safe production in phospho...Phosphorus is an essential element in agricultural production and chemical industry. However, since the risk of casualties and economic loss by mining accidents, the application of clean and safe production in phosphorus mines encounters great challenges. For this purpose, a man-machine-environment system composed of evaluation indexes was established, and the grading standards of indexes were defined. Firstly, the measurements of 39 qualitative indexes were obtained through the survey data. According to the measured values of 31 quantitative indexes, the measurements of quantitative indexes were calculated by linear measurement function(LM) and other three functions. Then the singleindex measurement evaluation matrixes were established. Secondly, the entropy weight method was used to determine the weights of each index directly. The analytic hierarchy process(AHP) was also applied to calculate the weights of index and index factor hierarchies after the established hierarchical model. The weights of system hierarchies were given by the grid-based fuzzy Borda method(GFB). The comprehensive weights were determined by the combination method of AHP and GFB(CAG). Furthermore, the multi-index comprehensive measurement evaluation vectors were obtained.Thirdly, the vectors were evaluated by the credible degree recognition(CDR) and the maximum membership(TMM)criteria. Based on the above functions, methods, and criteria, 16 combination evaluation methods were recommended.Finally, the clean and safe production grade of Kaiyang phosphate mine in China was evaluated. The results show that the LM-CAG-CDR is the most reasonable method, which can not only determine the clean and safe production grade of phosphorus mines, but also improve the development level of clean and safe mining of phosphorus mines for guidance.In addition, some beneficial suggestions and measures were also proposed to advance the clean and safe production grade of Kaiyang phosphorus mine.展开更多
A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a ...A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.展开更多
Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment,the evaluation information of alternatives given by decision makers is often fuzzy and uncertain.As a generaliz...Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment,the evaluation information of alternatives given by decision makers is often fuzzy and uncertain.As a generalization of intuitionistic fuzzy set(IFSs)and Pythagoras fuzzy set(PFSs),q-rung orthopair fuzzy set(q-ROFS)is more suitable for expressing fuzzy and uncertain information.But,in actual multiple attribute decision making(MADM)problems,the weights of DMs and attributes are always completely unknown or partly known,to date,the maximizing deviation method is a good tool to deal with such issues.Thus,combine the q-ROFS and conventional maximizing deviation method,we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper.Firstly,we briefly introduce the basic concept of q-rung orthopair fuzzy sets(q-ROFSs)and q-rung interval-valued orthopair fuzzy sets(q-RIVOFSs).Then,combine the maximizing deviation method with q-rung orthopair fuzzy information,we establish two new decision making models.On this basis,the proposed models are applied to MADM problems with q-rung orthopair fuzzy information.Compared with existing methods,the effectiveness and superiority of the new model are analyzed.This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers(q-ROFNs)and whose attributes are incomplete.展开更多
Fuzzy comprehensive evaluation method was used to develop a standard model to analyze and evaluate nearness degree of water environment quality at breeding area of Shuidong Bay in China.Results showed that certain env...Fuzzy comprehensive evaluation method was used to develop a standard model to analyze and evaluate nearness degree of water environment quality at breeding area of Shuidong Bay in China.Results showed that certain environment contamination factors in some areas seriously exceeded the standard value and led to the whole water quality at the third class level.The measurements should be taken to promote the sustainable development of breeding area in Shuidong Bay.展开更多
Designing a fuzzy inference system(FIS)from data can be divided into two main phases:structure identification and parameter optimization.First,starting from a simple initial topology,the membership functions and syste...Designing a fuzzy inference system(FIS)from data can be divided into two main phases:structure identification and parameter optimization.First,starting from a simple initial topology,the membership functions and system rules are defined as specific structures.Second,to speed up the convergence of the learning algorithm and lighten the oscillation,an improved descent method for FIS generation is developed.Furthermore, the convergence and the oscillation of the algorithm are system- atically analyzed.Third,using the information obtained from the previous phase,it can be decided in which region of the in- put space the density of fuzzy rules should be enhanced and for which variable the number of fuzzy sets that used to partition the domain must be increased.Consequently,this produces a new and more appropriate structure.Finally,the proposed method is applied to the problem of nonlinear function approximation.展开更多
The distribution of sampling data influences completeness of rule base so that extrapolating missing rules is very difficult. Based on data mining, a self-learning method is developed for identifying fuzzy model and e...The distribution of sampling data influences completeness of rule base so that extrapolating missing rules is very difficult. Based on data mining, a self-learning method is developed for identifying fuzzy model and extrapolating missing rules, by means of confidence measure and the improved gradient descent method. The proposed approach can not only identify fuzzy model, update its parameters and determine optimal output fuzzy sets simultaneously, but also resolve the uncontrollable problem led by the regions that data do not cover. The simulation results show the effectiveness and accuracy of the proposed approach with the classical truck backer-upper control problem verifying.展开更多
This study considers an MHD Jeffery-Hamel nanofluid flow with distinct nanoparticles such as copper,Al_(2)O_(3)and SiO_(2)between two rigid non-parallel plane walls with the fuzzy extension of the generalized dual par...This study considers an MHD Jeffery-Hamel nanofluid flow with distinct nanoparticles such as copper,Al_(2)O_(3)and SiO_(2)between two rigid non-parallel plane walls with the fuzzy extension of the generalized dual parametric homotopy algorithm.The nanofluids have been formulated to enhance the thermophysical characteristics of fluids,including thermal diffusivity,conductivity,convective heat transfer coefficients and viscosity.Due to the presence of distinct nanofluids,a change in the value of volume fraction occurs that influences the velocity profiles of the flow.The short value of nanoparticles volume fraction is considered an uncertain parameter and represented in a triangular fuzzy number range among[0.0,0.1,0.2].A novel generalized dual parametric homotopy algorithm with fuzzy extension is used here to study the fuzzy velocities at various channel positions.Finally,the effectiveness of the proposed approach has been demonstrated through a comparison with the available results in the crisp case.展开更多
文摘Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies are presented in order to identify and separate geochemical anomalies. The U-statistic method is one of the most important structural methods and is a kind of weighted mean that surrounding points of samples are considered in U value determination. However, it is able to separate the different anomalies based on only one variable. The main aim of the presented study is development of this method in a multivariate mode. For this purpose, U-statistic method should be combined with a multivariate method which devotes a new value to each sample based on several variables. Therefore, at the first step, the optimum p is calculated in p-norm distance and then U-statistic method is applied on p-norm distance values of the samples because p-norm distance is calculated based on several variables. This method is a combination of efficient U-statistic method and p-norm distance and is used for the first time in this research. Results show that p-norm distance of p=2(Euclidean distance) in the case of a fact that Au and As can be considered optimized p-norm distance with the lowest error. The samples indicated by the combination of these methods as anomalous are more regular, less dispersed and more accurate than using just the U-statistic or other nonstructural methods such as Mahalanobis distance. Also it was observed that the combination results are closely associated with the defined Au ore indication within the studied area. Finally, univariate and bivariate geochemical anomaly maps are provided for Au and As, which have been respectively prepared using U-statistic and its combination with Euclidean distance method.
基金supported by the National Natural Science Foundation of China(60774100)the Natural Science Foundation of Shandong Province of China(Y2007A15)
文摘The aim of this paper is to discuss the approximate rea- soning problems with interval-valued fuzzy environments based on the fully implicational idea. First, this paper constructs a class of interval-valued fuzzy implications by means of a type of impli- cations and a parameter on the unit interval, then uses them to establish fully implicational reasoning methods for interval-valued fuzzy modus ponens （IFMP） and interval-valued fuzzy modus tel- lens （IFMT） problems. At the same time the reversibility properties of these methods are analyzed and the reversible conditions are given. It is shown that the existing unified forms of α-triple I （the abbreviation of triple implications） methods for FMP and FMT can be seen as the particular cases of our methods for IFMP and IFMT.
文摘The basic"current"statistical model and adaptive Kalman filter algorithm can not track a weakly maneuvering target precisely,though it has good estimate accuracy for strongly maneuvering target.In order to solve this problem,a novel nonlinear fuzzy membership function was presented to adjust the upper and lower limit of target acceleration adaptively,and then the validity of the new algorithm for feeblish maneuvering target was proved in theory.At last,the computer simulation experiments indicated that the new algorithm has a great advantage over the basic"current"statistical model and adaptive algorithm.
基金Project supported by National Natural Science Foundation of China（51277117）, Shang- hai Science and Technology Comrmssion（11 DZ2283000）.
文摘Cables that have been in service for over 20 years in Shanghai, a city with abundant surface water, failed more frequently and induced different cable accidents. This necessitates researches on the insulation aging state of cables working in special circumstances. We performed multi-parameter tests with samples from about 300 cable lines in Shanghai. The tests included water tree investigation, tensile test, dielectric spectroscopy test, thermogravimetric analysis (TGA), fourier transform infrared spectroscopy (FTIR), and electrical aging test. Then, we carried out regression analysis between every two test parameters. Moreover, through two-sample t-Test and analysis of va- riance (ANOVA) of each test parameter, we analyzed the influences of cable-laying method and sampling section on the degradation of cable insulation respectively. Furthermore, the test parameters which have strong correlation in the regression analysis or significant differ- ences in the t-Test or ANOVA analysis were determined to be the ones identifying the XLPE cable insulation aging state. The thresholds for distinguishing insulation aging states had been also obtained with the aid of statistical analysis and fuzzy clustering. Based on the fuzzy in- ference, we established a cable insulation aging diagnosis model using the intensity transfer method. The results of regression analysis indicate that the degradation of cable insulation accelerates as the degree of in-service aging increases. This validates the rule that the in- crease of microscopic imperfections in solid material enhances the dielectric breakdown strength. The results of the two-sample t-Test and the ANOVA indicate that the direct-buried cables are more sensitive to insulation degradation than duct cables. This confirms that the tensile strength and breakdown strength are reliable functional parameters in cable insulation evaluations. A case study further indicates that the proposed diagnosis model based on the fuzzy inference can reflect the comprehensive aging state of cable insulation well, and that the cable service time has no correlation with the insulation aging state.
基金This project was supported by the Evaluate Quality of Satellite TT&C Mission(C0112)
文摘The fuzzy integration evaluation method （FIEM） is studied in order to select the best orbital elements from the multi-group initial orbits determined by a satellite TT＆C （Tracking, Telemetry and Control） center with all kinds of data sources. By employing FIEM together with the experience of TT＆C experts, the index system to evaluate the selection of the best initial orbits is established after the data sources and orbit determination theories are studied. Besides, the concrete steps in employing the method are presented. Moreover, by taking the objects to be evaluated as evaluation experts, the problem of how to generate evaluation matrices is solved. Through practical application, the method to select the best initial orbital elements has been proved to be flexible and effective The originality of the method is to find a new evaluation criterion （comparing the actually tracked orbits） replacing the traditional one （comparing the nominal orbits） for selecting the best orbital elements.
基金supported by the National Natural Science Foundation of China (7087111770571086)
文摘An extended compromise ratio method（CRM） based on fuzzy distances is developed to solve fuzzy multi-attribute group decision making problems in which weights of attributes and ratings of alternatives on attributes are expressed with values of linguistic variables parameterized using triangular fuzzy numbers.A compromise solution is determined by introducing the ranking index based on the concept that the chosen alternative should be as close as possible to the positive ideal solution and as far away from the negative ideal solution as possible simultaneously.This proposed method is compared with other existing methods to show its feasibility and effectiveness and illustrated with an example of the military route selection problem as one of the possible applications.
文摘The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, data with noise, data with mixture of heterogeneous cluster prototypes, asymmetric data, etc. Based on the Mercer kernel, FKCM clustering algorithm is derived from FCM algorithm united with kernel method. The results of experiments with the synthetic and real data show that the FKCM clustering algorithm is universality and can effectively unsupervised analyze datasets with variform structures in contrast to FCM algorithm. It is can be imagined that kernel-based clustering algorithm is one of important research direction of fuzzy clustering analysis.
基金Projects(51204054,51504203)supported by the National Natural Science Foundation of ChinaProject(2016ZX05023-001)supported by the National Science and Technology Major Project of China
文摘The selection of refracturing candidate is one of the most important jobs faced by oilfield engineers. However, due to the complicated multi-parameter relationships and their comprehensive influence, the selection of refracturing candidate is often very difficult. In this paper, a novel approach combining data analysis techniques and fuzzy clustering was proposed to select refracturing candidate. First, the analysis techniques were used to quantitatively calculate the weight coefficient and determine the key factors. Then, the idealized refracturing well was established by considering the main factors. Fuzzy clustering was applied to evaluate refracturing potential. Finally, reservoirs numerical simulation was used to further evaluate reservoirs energy and material basis of the optimum refracturing candidates. The hybrid method has been successfully applied to a tight oil reservoir in China. The average steady production was 15.8 t/d after refracturing treatment, increasing significantly compared with previous status. The research results can guide the development of tight oil and gas reservoirs effectively.
基金Project(51974362) supported by the National Natural Science Foundation of ChinaProject(2282020cxqd055) supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2021-QYC-10050-25631) supported by the Department of Emergency Management of Hunan Province,China。
文摘Phosphorus is an essential element in agricultural production and chemical industry. However, since the risk of casualties and economic loss by mining accidents, the application of clean and safe production in phosphorus mines encounters great challenges. For this purpose, a man-machine-environment system composed of evaluation indexes was established, and the grading standards of indexes were defined. Firstly, the measurements of 39 qualitative indexes were obtained through the survey data. According to the measured values of 31 quantitative indexes, the measurements of quantitative indexes were calculated by linear measurement function(LM) and other three functions. Then the singleindex measurement evaluation matrixes were established. Secondly, the entropy weight method was used to determine the weights of each index directly. The analytic hierarchy process(AHP) was also applied to calculate the weights of index and index factor hierarchies after the established hierarchical model. The weights of system hierarchies were given by the grid-based fuzzy Borda method(GFB). The comprehensive weights were determined by the combination method of AHP and GFB(CAG). Furthermore, the multi-index comprehensive measurement evaluation vectors were obtained.Thirdly, the vectors were evaluated by the credible degree recognition(CDR) and the maximum membership(TMM)criteria. Based on the above functions, methods, and criteria, 16 combination evaluation methods were recommended.Finally, the clean and safe production grade of Kaiyang phosphate mine in China was evaluated. The results show that the LM-CAG-CDR is the most reasonable method, which can not only determine the clean and safe production grade of phosphorus mines, but also improve the development level of clean and safe mining of phosphorus mines for guidance.In addition, some beneficial suggestions and measures were also proposed to advance the clean and safe production grade of Kaiyang phosphorus mine.
基金This project was supported by the National Natural Science Foundation of China (90405011).
文摘A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.
基金supported by the National Natural Science Foundation of China under Grant No.71571128the Humanities and Social Sciences Foundation of Ministry of Education of the People’s Republic of China(No.17XJA630003).
文摘Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment,the evaluation information of alternatives given by decision makers is often fuzzy and uncertain.As a generalization of intuitionistic fuzzy set(IFSs)and Pythagoras fuzzy set(PFSs),q-rung orthopair fuzzy set(q-ROFS)is more suitable for expressing fuzzy and uncertain information.But,in actual multiple attribute decision making(MADM)problems,the weights of DMs and attributes are always completely unknown or partly known,to date,the maximizing deviation method is a good tool to deal with such issues.Thus,combine the q-ROFS and conventional maximizing deviation method,we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper.Firstly,we briefly introduce the basic concept of q-rung orthopair fuzzy sets(q-ROFSs)and q-rung interval-valued orthopair fuzzy sets(q-RIVOFSs).Then,combine the maximizing deviation method with q-rung orthopair fuzzy information,we establish two new decision making models.On this basis,the proposed models are applied to MADM problems with q-rung orthopair fuzzy information.Compared with existing methods,the effectiveness and superiority of the new model are analyzed.This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers(q-ROFNs)and whose attributes are incomplete.
基金Supported by China Postdoctoral Science Foundation (20090460873)
文摘Fuzzy comprehensive evaluation method was used to develop a standard model to analyze and evaluate nearness degree of water environment quality at breeding area of Shuidong Bay in China.Results showed that certain environment contamination factors in some areas seriously exceeded the standard value and led to the whole water quality at the third class level.The measurements should be taken to promote the sustainable development of breeding area in Shuidong Bay.
基金Supported by National Basic Research Program of China(973 Program)(2007CB714006)
文摘Designing a fuzzy inference system(FIS)from data can be divided into two main phases:structure identification and parameter optimization.First,starting from a simple initial topology,the membership functions and system rules are defined as specific structures.Second,to speed up the convergence of the learning algorithm and lighten the oscillation,an improved descent method for FIS generation is developed.Furthermore, the convergence and the oscillation of the algorithm are system- atically analyzed.Third,using the information obtained from the previous phase,it can be decided in which region of the in- put space the density of fuzzy rules should be enhanced and for which variable the number of fuzzy sets that used to partition the domain must be increased.Consequently,this produces a new and more appropriate structure.Finally,the proposed method is applied to the problem of nonlinear function approximation.
基金This project was supported by State Science &Technology Pursuing Project (2001BA204B01) of China and Foundation forUniversity Key Teacher by the Ministry of Education of China.
文摘The distribution of sampling data influences completeness of rule base so that extrapolating missing rules is very difficult. Based on data mining, a self-learning method is developed for identifying fuzzy model and extrapolating missing rules, by means of confidence measure and the improved gradient descent method. The proposed approach can not only identify fuzzy model, update its parameters and determine optimal output fuzzy sets simultaneously, but also resolve the uncontrollable problem led by the regions that data do not cover. The simulation results show the effectiveness and accuracy of the proposed approach with the classical truck backer-upper control problem verifying.
文摘This study considers an MHD Jeffery-Hamel nanofluid flow with distinct nanoparticles such as copper,Al_(2)O_(3)and SiO_(2)between two rigid non-parallel plane walls with the fuzzy extension of the generalized dual parametric homotopy algorithm.The nanofluids have been formulated to enhance the thermophysical characteristics of fluids,including thermal diffusivity,conductivity,convective heat transfer coefficients and viscosity.Due to the presence of distinct nanofluids,a change in the value of volume fraction occurs that influences the velocity profiles of the flow.The short value of nanoparticles volume fraction is considered an uncertain parameter and represented in a triangular fuzzy number range among[0.0,0.1,0.2].A novel generalized dual parametric homotopy algorithm with fuzzy extension is used here to study the fuzzy velocities at various channel positions.Finally,the effectiveness of the proposed approach has been demonstrated through a comparison with the available results in the crisp case.
