For a degradable structural system with fuzzy failure region, a moment method based on fuzzy reliability sensitivity algorithm is presented. According to the value assignment of performance function, the integral regi...For a degradable structural system with fuzzy failure region, a moment method based on fuzzy reliability sensitivity algorithm is presented. According to the value assignment of performance function, the integral region for calculating the fuzzy failure probability is first split into a series of subregions in which the membership function values of the performance function within the fuzzy failure region can be approximated by a set of constants. The fuzzy failure probability is then transformed into a sum of products of the random failure probabilities and the approximate constants of the membership function in the subregions. Furthermore, the fuzzy reliability sensitivity analysis is transformed into a series of random reliability sensitivity analysis, and the random reliability sensitivity can be obtained by the constructed moment method. The primary advantages of the presented method include higher efficiency for implicit performance function with low and medium dimensionality and wide applicability to multiple failure modes and nonnormal basic random variables. The limitation is that the required computation effort grows exponentially with the increase of dimensionality of the basic random vari- able; hence, it is not suitable for high dimensionality problem. Compared with the available methods, the presented one is pretty competitive in the case that the dimensionality is lower than 10. The presented examples are used to verify the advantages and indicate the limitations.展开更多
A new numerical technique named as fuzzy finite difference method is proposed to solve the heat conduction problems with fuzzy uncertainties in both the phys- ical parameters and initial/boundary conditions. In virtue...A new numerical technique named as fuzzy finite difference method is proposed to solve the heat conduction problems with fuzzy uncertainties in both the phys- ical parameters and initial/boundary conditions. In virtue of the level-cut method, the difference discrete equations with fuzzy parameters are equivalently transformed into groups of interval equations. New stability analysis theory suited to fuzzy difference schemes is developed. Based on the parameter perturbation method, the interval ranges of the uncertain temperature field can be approximately predicted. Subsequently, fuzzy solutions to the original difference equations are obtained by the fuzzy resolution theorem. Two numerical examples are given to demonstrate the feasibility and efficiency of the presented method for solving both steady-state and transient heat conduction problems.展开更多
Homotopy Analysis Method(HAM)is semi-analytic method to solve the linear and nonlinear mathematical models which can be used to obtain the approximate solution.The HAM includes an auxiliary parameter,which is an effic...Homotopy Analysis Method(HAM)is semi-analytic method to solve the linear and nonlinear mathematical models which can be used to obtain the approximate solution.The HAM includes an auxiliary parameter,which is an efficient way to examine and analyze the accuracy of linear and nonlinear problems.The main aim of this work is to explore the approximate solutions of fuzzy Volterra integral equations(both linear and nonlinear)with a separable kernel via HAM.This method provides a reliable way to ensure the convergence of the approximation series.A new general form of HAM is presented and analyzed in the fuzzy domain.A qualitative convergence analysis based on the graphical method of a fuzzy HAM is discussed.The solutions sought by the proposed method show that the HAM is easy to implement and computationally quite attractive.Some solutions of fuzzy second kind Volterra integral equations are solved as numerical examples to show the potential of the method.The results also show that HAM provides an easy way to control and modify the convergence area in order to obtain accurate solutions.展开更多
In this paper, the fuzzy-set-based structural possibility theory is investigated, and this theory can be used to deal with the subjective uncertainties in the design of engineering structures. Furthermore, a comprehen...In this paper, the fuzzy-set-based structural possibility theory is investigated, and this theory can be used to deal with the subjective uncertainties in the design of engineering structures. Furthermore, a comprehensive model of structural safety assessment, which can merge subjective uncertainties with objective uncertainties, is presented. In this model, the fuzziness of stress-strength inference model, safety margin functions of single or multiple limit-state, structural failure state and the final assessment result are taken into account. This continuous model can be transformed into an equivalent model of probability-based and solved by the present structural reliability analysis method and parallel algorithm. An example is given to show the main idea of the method presented in this paper.展开更多
An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variat...An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.展开更多
Principal Component Analysis(PCA)is one of the most important feature extraction methods,and Kernel Principal Component Analysis(KPCA)is a nonlinear extension of PCA based on kernel methods.In real world,each input da...Principal Component Analysis(PCA)is one of the most important feature extraction methods,and Kernel Principal Component Analysis(KPCA)is a nonlinear extension of PCA based on kernel methods.In real world,each input data may not be fully assigned to one class and it may partially belong to other classes.Based on the theory of fuzzy sets,this paper presents Fuzzy Principal Component Analysis(FPCA)and its nonlinear extension model,i.e.,Kernel-based Fuzzy Principal Component Analysis(KFPCA).The experimental results indicate that the proposed algorithms have good performances.展开更多
An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service.This paper aims to explore a technical method for determining and screening evaluation indicators.Based on public ...An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service.This paper aims to explore a technical method for determining and screening evaluation indicators.Based on public satisfaction survey data obtained in Wafangdian,China in 2010,this study investigates the suitability of fuzzy clustering analysis method in establishing an evaluation index.Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators,correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer,then one indicator could be removed,or the two indicators merged.For evaluation indicators in different sub-evaluation layers,although clustering reveals attribute correlations,these indicators may not be substituted for one another.Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.展开更多
A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is perform...A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.展开更多
On the process of power system black start after an accident, it can help to optimize the resources allocation and accelerate the recovery process that decomposing the power system into several independent partitions ...On the process of power system black start after an accident, it can help to optimize the resources allocation and accelerate the recovery process that decomposing the power system into several independent partitions for parallel recovery. On the basis of adequate consideration of fuzziness of black-start zone partitioning, a new algorithm based on fuzzy clustering analysis is presented. Characteristic indexes are extracted fully and accurately. The raw data matrix is made up of the electrical distance between every nodes and blackstart resources. Closure transfer method is utilized to get the dynamic clustering. The availability and feasibility of the proposed algorithm are verified on the New-England 39 bus system at last.展开更多
The fractional-order Boussinesq equations(FBSQe)are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave.The fuzzy ...The fractional-order Boussinesq equations(FBSQe)are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave.The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method.It also occurs on the sea floor as opposed to at the functionality.A set of dynamical partial differential equations(PDEs)in this article exemplify an unconfined aquifer flow implication.Thismethodology can accurately simulate climatological intrinsic waves,so the ripples are spread across a large demographic zone.The Aboodh transform merged with the mechanism of Adomian decomposition is implemented to obtain the fuzzified FBSQe in R,R^(n) and(2nth)-order involving generalized Hukuhara differentiability.According to the system parameter,we classify the qualitative features of the Aboodh transform in the fuzzified Caputo and Atangana-Baleanu-Caputo fractional derivative formulations,which are addressed in detail.The illustrations depict a comparison analysis between the both fractional operators under gH-differentiability,as well as the appropriate attributes for the fractional-order and unpredictability factorsσ∈[0,1].A statistical experiment is conducted between the findings of both fractional derivatives to prevent changing the hypothesis after the results are known.Based on the suggested analyses,hydrodynamic technicians,as irrigation or aquifer quality experts,may be capable of obtaining an appropriate storage intensity amount,including an unpredictability threshold.展开更多
To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers ...To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.展开更多
The plunger component is a key part of the plunger pump in the aircraft hydraulic system.Neck-spinning process is commonly used to fabricate plunger components,of which the quality of the spinning process significantl...The plunger component is a key part of the plunger pump in the aircraft hydraulic system.Neck-spinning process is commonly used to fabricate plunger components,of which the quality of the spinning process significantly affects the performance of plunger pumps.One of the bottlenecks faced by the industry in the spinning process is to choose a suitable neck-spinning process so as to ensure the quality of plunger components.It is necessary to propose a reliable method to optimize the process parameters which affect the neck-spinning quality of plunger components.In this study,a calculable finite element analysis(FEA)model is established to simulate the threeroller neck-spinning process of the plunger component,which includes six typical slipper structures,two roller structures,and two spinning parameters.The FEA model is then validated by comparing the simulated spinning forces with the corresponding experimental results.The influence of the process conditions on the neck-spinning quality is investigated.And the orthogonal simulation results are analyzed by a combination of range method and fuzzy mathematical analysis method to recommend a reasonable slipper structure,roller structure and neck-spinning parameters.This study provides a promising method to improve the manufacturing quality of the typical plunger components.展开更多
The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluatio...The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluation method can consider these two uncertainties to produce more objective and reasonable evaluation results. In this paper, we propose a combination evaluation method with two main parts:(1) the use of fuzzy comprehensive evaluation and gray correlation analysis as submodels with which to consider the fuzzy and gray uncertainties and(2) the establishment of a combination model based on minimum bias squares. In addition, using this method, we evaluate the water quality of a ditch in a typical rice–wheat system of Yixing city in the Taihu Lake Basin during three rainfall events. The results show that the ditch water quality is not good and we found the chemical oxygen demand to be the key indicator that affects water quality most significantly. The proposed combination evaluation method is more accurate and practical than single-factor evaluation methods in that it considers the uncertainties of fuzziness and grayness.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
In view of the current and predictable energy shortage and environmental concerns, the exploitation of renewable energy sources offers great potential to meet increasing energy demands and to decrease depend- ence on ...In view of the current and predictable energy shortage and environmental concerns, the exploitation of renewable energy sources offers great potential to meet increasing energy demands and to decrease depend- ence on fossil fuels. However, introducing these sources will be more attractive provided they operate in conjunction with energy storage systems (ESS). Furthermore, effective energy storage management is essential to achieve a balance between power quality, efficiency, costs and environmental constraints. This paper presents a method based on the analytic hierarchy process and fuzzy multi-rules and multi-sets. By exploiting a multiple criteria analysis, the proposed methods evaluate the operation of storage energy systems such as: pumped hydro and compressed air energy storage, H2, flywheel, super-capacitors and lithium-ion storage as well as NaS advanced batteries and VRB flow battery. The main objective of the study is to find the most appropriate ESS consistent with a power quality priority. Several parameters are used for the investigation: efficiency, load management, technical maturity, costs, environmental impact and power quality.展开更多
Based on the fundamental principles of total amount control of water use, the harmony theory was used in this study to develop a concept of the degree of harmony of total amount control of water use. Based on this con...Based on the fundamental principles of total amount control of water use, the harmony theory was used in this study to develop a concept of the degree of harmony of total amount control of water use. Based on this concept, the harmoniousness of total amount control of water use was analyzed in terms of the supply and demand of water resources, water resources management, water use benefits, and water-saving level. An evaluation index system of the degree of harmony of total amount control of water use was established, and a method for calculation of the degree of harmony of total amount control of water use was developed based on the analytic hierarchy process （AHP） and fuzzy comprehensive analysis （FCA） methods. The new evaluation index system was applied to a certain area in Jiangsu Province, China. The degree of harmony of total amount control of water use over this area was calculated for different years. Results indicate that the evaluation index system and calculation method proposed in this study are feasible, and such a harmoniousness analysis can provide scientific references for the strict water resources management system that will be implemented in China in the near future.展开更多
With the deepening of economic globalization,China’s economy and the global economy are becoming increasingly interdependent and closely linked,resulting in a more complex environment for domestic enterprises and hei...With the deepening of economic globalization,China’s economy and the global economy are becoming increasingly interdependent and closely linked,resulting in a more complex environment for domestic enterprises and heightened financial risks.To enhance the risk resilience of enterprises,the research methods for assessing financial risks are becoming more diverse.Traditional financial risk analysis methods,such as the single-argument model,have certain limitations in the practical application of enterprise financial risk evaluation.These methods cannot overcome the restrictions of time,region,and industry,and their application value is not fully realized.To better assist enterprises in addressing the complexities of financial risks,fuzzy hierarchical analysis is applied to the traditional hierarchical analysis method under fuzzy optimization conditions.This method focuses on indices of measurable comparability,facilitating a more reasonable and objective financial risk evaluation of enterprises,especially when comparing different companies in the new energy vehicle industry and conducting a longitudinal comparison of Company A.Fuzzy hierarchical analysis integrates qualitative judgment with quantitative analysis,using triangular fuzzy numbers to generate a judgment matrix.The results are transformed into an objective fuzzy set,enabling the quantification and structuring of complex system indicators and improving the rationality and accuracy of the enterprise’s financial risk evaluation.展开更多
基金Foundation items： National Natural Science Foundation of China （NSFC 10572117） National High-tech Research and Development Program （2007AA04Z401）+1 种基金 New Century Program for Excellent Talents of Ministry of Education of China （NCET-05-0868） Aeronautical Science Foundation of China （2007ZA53012）
文摘For a degradable structural system with fuzzy failure region, a moment method based on fuzzy reliability sensitivity algorithm is presented. According to the value assignment of performance function, the integral region for calculating the fuzzy failure probability is first split into a series of subregions in which the membership function values of the performance function within the fuzzy failure region can be approximated by a set of constants. The fuzzy failure probability is then transformed into a sum of products of the random failure probabilities and the approximate constants of the membership function in the subregions. Furthermore, the fuzzy reliability sensitivity analysis is transformed into a series of random reliability sensitivity analysis, and the random reliability sensitivity can be obtained by the constructed moment method. The primary advantages of the presented method include higher efficiency for implicit performance function with low and medium dimensionality and wide applicability to multiple failure modes and nonnormal basic random variables. The limitation is that the required computation effort grows exponentially with the increase of dimensionality of the basic random vari- able; hence, it is not suitable for high dimensionality problem. Compared with the available methods, the presented one is pretty competitive in the case that the dimensionality is lower than 10. The presented examples are used to verify the advantages and indicate the limitations.
基金supported by the National Special Fund for Major Research Instrument Development(2011YQ140145)111 Project(B07009)+1 种基金the National Natural Science Foundation of China(11002013)Defense Industrial Technology Development Program(A2120110001 and B2120110011)
文摘A new numerical technique named as fuzzy finite difference method is proposed to solve the heat conduction problems with fuzzy uncertainties in both the phys- ical parameters and initial/boundary conditions. In virtue of the level-cut method, the difference discrete equations with fuzzy parameters are equivalently transformed into groups of interval equations. New stability analysis theory suited to fuzzy difference schemes is developed. Based on the parameter perturbation method, the interval ranges of the uncertain temperature field can be approximately predicted. Subsequently, fuzzy solutions to the original difference equations are obtained by the fuzzy resolution theorem. Two numerical examples are given to demonstrate the feasibility and efficiency of the presented method for solving both steady-state and transient heat conduction problems.
基金Dr.Ali Jameel and Noraziah Man are very grateful to the Ministry of Higher Education of Malaysia for providing them with the Fundamental Research Grant Scheme(FRGS)S/O No.14188 that supported this research.
文摘Homotopy Analysis Method(HAM)is semi-analytic method to solve the linear and nonlinear mathematical models which can be used to obtain the approximate solution.The HAM includes an auxiliary parameter,which is an efficient way to examine and analyze the accuracy of linear and nonlinear problems.The main aim of this work is to explore the approximate solutions of fuzzy Volterra integral equations(both linear and nonlinear)with a separable kernel via HAM.This method provides a reliable way to ensure the convergence of the approximation series.A new general form of HAM is presented and analyzed in the fuzzy domain.A qualitative convergence analysis based on the graphical method of a fuzzy HAM is discussed.The solutions sought by the proposed method show that the HAM is easy to implement and computationally quite attractive.Some solutions of fuzzy second kind Volterra integral equations are solved as numerical examples to show the potential of the method.The results also show that HAM provides an easy way to control and modify the convergence area in order to obtain accurate solutions.
文摘In this paper, the fuzzy-set-based structural possibility theory is investigated, and this theory can be used to deal with the subjective uncertainties in the design of engineering structures. Furthermore, a comprehensive model of structural safety assessment, which can merge subjective uncertainties with objective uncertainties, is presented. In this model, the fuzziness of stress-strength inference model, safety margin functions of single or multiple limit-state, structural failure state and the final assessment result are taken into account. This continuous model can be transformed into an equivalent model of probability-based and solved by the present structural reliability analysis method and parallel algorithm. An example is given to show the main idea of the method presented in this paper.
基金The National Natural Science Foundation of China under contract No.51379002the Fundamental Research Funds for the Central Universities of China under contract Nos 3132016322 and 3132016314the Applied Basic Research Project Fund of the Chinese Ministry of Transport of China under contract No.2014329225010
文摘An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.
文摘Principal Component Analysis(PCA)is one of the most important feature extraction methods,and Kernel Principal Component Analysis(KPCA)is a nonlinear extension of PCA based on kernel methods.In real world,each input data may not be fully assigned to one class and it may partially belong to other classes.Based on the theory of fuzzy sets,this paper presents Fuzzy Principal Component Analysis(FPCA)and its nonlinear extension model,i.e.,Kernel-based Fuzzy Principal Component Analysis(KFPCA).The experimental results indicate that the proposed algorithms have good performances.
基金National Science Foundation of China(91637105,41775048 and 41475041)National Key R&D Program of China(2018YFC1507800)Research on Tourism Traffic Meteorological Service Products in Heilongjiang Province(HQZD2017004)
文摘An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service.This paper aims to explore a technical method for determining and screening evaluation indicators.Based on public satisfaction survey data obtained in Wafangdian,China in 2010,this study investigates the suitability of fuzzy clustering analysis method in establishing an evaluation index.Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators,correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer,then one indicator could be removed,or the two indicators merged.For evaluation indicators in different sub-evaluation layers,although clustering reveals attribute correlations,these indicators may not be substituted for one another.Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.
文摘A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.
文摘On the process of power system black start after an accident, it can help to optimize the resources allocation and accelerate the recovery process that decomposing the power system into several independent partitions for parallel recovery. On the basis of adequate consideration of fuzziness of black-start zone partitioning, a new algorithm based on fuzzy clustering analysis is presented. Characteristic indexes are extracted fully and accurately. The raw data matrix is made up of the electrical distance between every nodes and blackstart resources. Closure transfer method is utilized to get the dynamic clustering. The availability and feasibility of the proposed algorithm are verified on the New-England 39 bus system at last.
文摘The fractional-order Boussinesq equations(FBSQe)are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave.The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method.It also occurs on the sea floor as opposed to at the functionality.A set of dynamical partial differential equations(PDEs)in this article exemplify an unconfined aquifer flow implication.Thismethodology can accurately simulate climatological intrinsic waves,so the ripples are spread across a large demographic zone.The Aboodh transform merged with the mechanism of Adomian decomposition is implemented to obtain the fuzzified FBSQe in R,R^(n) and(2nth)-order involving generalized Hukuhara differentiability.According to the system parameter,we classify the qualitative features of the Aboodh transform in the fuzzified Caputo and Atangana-Baleanu-Caputo fractional derivative formulations,which are addressed in detail.The illustrations depict a comparison analysis between the both fractional operators under gH-differentiability,as well as the appropriate attributes for the fractional-order and unpredictability factorsσ∈[0,1].A statistical experiment is conducted between the findings of both fractional derivatives to prevent changing the hypothesis after the results are known.Based on the suggested analyses,hydrodynamic technicians,as irrigation or aquifer quality experts,may be capable of obtaining an appropriate storage intensity amount,including an unpredictability threshold.
文摘To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.
基金the National Natural Science Foundation of China for Creative Research Groups(Grant No.51921003)。
文摘The plunger component is a key part of the plunger pump in the aircraft hydraulic system.Neck-spinning process is commonly used to fabricate plunger components,of which the quality of the spinning process significantly affects the performance of plunger pumps.One of the bottlenecks faced by the industry in the spinning process is to choose a suitable neck-spinning process so as to ensure the quality of plunger components.It is necessary to propose a reliable method to optimize the process parameters which affect the neck-spinning quality of plunger components.In this study,a calculable finite element analysis(FEA)model is established to simulate the threeroller neck-spinning process of the plunger component,which includes six typical slipper structures,two roller structures,and two spinning parameters.The FEA model is then validated by comparing the simulated spinning forces with the corresponding experimental results.The influence of the process conditions on the neck-spinning quality is investigated.And the orthogonal simulation results are analyzed by a combination of range method and fuzzy mathematical analysis method to recommend a reasonable slipper structure,roller structure and neck-spinning parameters.This study provides a promising method to improve the manufacturing quality of the typical plunger components.
基金supported by the National Key Research and Development Program of China (No. 2017YFC0405006)the Innovative Research Groups of the National Natural Science Foundation of China (No. 51621092)the Natural Science Foundation of Tianjin (No. 16JCYBJC23100)
文摘The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluation method can consider these two uncertainties to produce more objective and reasonable evaluation results. In this paper, we propose a combination evaluation method with two main parts:(1) the use of fuzzy comprehensive evaluation and gray correlation analysis as submodels with which to consider the fuzzy and gray uncertainties and(2) the establishment of a combination model based on minimum bias squares. In addition, using this method, we evaluate the water quality of a ditch in a typical rice–wheat system of Yixing city in the Taihu Lake Basin during three rainfall events. The results show that the ditch water quality is not good and we found the chemical oxygen demand to be the key indicator that affects water quality most significantly. The proposed combination evaluation method is more accurate and practical than single-factor evaluation methods in that it considers the uncertainties of fuzziness and grayness.
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.
文摘In view of the current and predictable energy shortage and environmental concerns, the exploitation of renewable energy sources offers great potential to meet increasing energy demands and to decrease depend- ence on fossil fuels. However, introducing these sources will be more attractive provided they operate in conjunction with energy storage systems (ESS). Furthermore, effective energy storage management is essential to achieve a balance between power quality, efficiency, costs and environmental constraints. This paper presents a method based on the analytic hierarchy process and fuzzy multi-rules and multi-sets. By exploiting a multiple criteria analysis, the proposed methods evaluate the operation of storage energy systems such as: pumped hydro and compressed air energy storage, H2, flywheel, super-capacitors and lithium-ion storage as well as NaS advanced batteries and VRB flow battery. The main objective of the study is to find the most appropriate ESS consistent with a power quality priority. Several parameters are used for the investigation: efficiency, load management, technical maturity, costs, environmental impact and power quality.
文摘Based on the fundamental principles of total amount control of water use, the harmony theory was used in this study to develop a concept of the degree of harmony of total amount control of water use. Based on this concept, the harmoniousness of total amount control of water use was analyzed in terms of the supply and demand of water resources, water resources management, water use benefits, and water-saving level. An evaluation index system of the degree of harmony of total amount control of water use was established, and a method for calculation of the degree of harmony of total amount control of water use was developed based on the analytic hierarchy process （AHP） and fuzzy comprehensive analysis （FCA） methods. The new evaluation index system was applied to a certain area in Jiangsu Province, China. The degree of harmony of total amount control of water use over this area was calculated for different years. Results indicate that the evaluation index system and calculation method proposed in this study are feasible, and such a harmoniousness analysis can provide scientific references for the strict water resources management system that will be implemented in China in the near future.
文摘With the deepening of economic globalization,China’s economy and the global economy are becoming increasingly interdependent and closely linked,resulting in a more complex environment for domestic enterprises and heightened financial risks.To enhance the risk resilience of enterprises,the research methods for assessing financial risks are becoming more diverse.Traditional financial risk analysis methods,such as the single-argument model,have certain limitations in the practical application of enterprise financial risk evaluation.These methods cannot overcome the restrictions of time,region,and industry,and their application value is not fully realized.To better assist enterprises in addressing the complexities of financial risks,fuzzy hierarchical analysis is applied to the traditional hierarchical analysis method under fuzzy optimization conditions.This method focuses on indices of measurable comparability,facilitating a more reasonable and objective financial risk evaluation of enterprises,especially when comparing different companies in the new energy vehicle industry and conducting a longitudinal comparison of Company A.Fuzzy hierarchical analysis integrates qualitative judgment with quantitative analysis,using triangular fuzzy numbers to generate a judgment matrix.The results are transformed into an objective fuzzy set,enabling the quantification and structuring of complex system indicators and improving the rationality and accuracy of the enterprise’s financial risk evaluation.
