The concept of b-vex and logarithmic b-vex for fuzzy mappings are introduced by relaxing the definition of convexity of a fuzzy mapping. Most of the basic properties of b-vex fuzzy mapping are discussed and establish...The concept of b-vex and logarithmic b-vex for fuzzy mappings are introduced by relaxing the definition of convexity of a fuzzy mapping. Most of the basic properties of b-vex fuzzy mapping are discussed and established for the nondifferentiable case. Necessary and sufficient conditions for b-vex fuzzy mapping are presented. Sevaral important results are given for nonlinear fuzzy optimization problems assuming that the objective and constraint functions are b-vex fuzzy mappings.展开更多
A class of generalized implicit quasivariational inclusions with fuzzy mappings in Hilbert space is discussed in this paper which proves an existence theorem of the solutions and proposes a new iterative algorithm and...A class of generalized implicit quasivariational inclusions with fuzzy mappings in Hilbert space is discussed in this paper which proves an existence theorem of the solutions and proposes a new iterative algorithm and the convergence of the iterative sequence generated by the new algorithm. These results extend and improve some recent corresponding achievements.展开更多
In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point res...In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point results are established in the framework of metric spaces.Based on the presented work,some examples reflecting decision-making problems related to real life are also solved.The suggested method’s flexibility and efficacy compared to conventional techniques are demonstrated in decision-making situations involving uncertainty,such as choosing the best options in multi-criteria settings.We noted that the presented work combines and generalizes two major concepts,the idea of soft sets and hesitant fuzzy set-valued mapping from the existing literature.展开更多
In this paper,the pointwise characterizations of fuzzy mappings are given. Based of this definition,we give a few of new properties of fuzzy cardinal numbers.
In this paper, a new class of fuzzy mappings called semistrictly convex fuzzy mappings is introduced and we present some properties of this kind of fuzzy mappings. In particular, we prove that a local minimum of a sem...In this paper, a new class of fuzzy mappings called semistrictly convex fuzzy mappings is introduced and we present some properties of this kind of fuzzy mappings. In particular, we prove that a local minimum of a semistrictly convex fuzzy mapping is also a global minimum. We also discuss the relations among convexity, strict convexity and semistrict convexity of fuzzy mapping, and give several sufficient conditions for convexity and semistrict convexity.展开更多
In this paper,a perturbed iterative algorithm for finding approximate solutions of variational inclusions for fuzzy mapping,is presented and a convergence result which includes,as a special case,some known results in ...In this paper,a perturbed iterative algorithm for finding approximate solutions of variational inclusions for fuzzy mapping,is presented and a convergence result which includes,as a special case,some known results in this field,is given.展开更多
Taking into account that fuzzy ontology mapping has wide application and cannot be dealt with in many fields at present,a Chinese fuzzy ontology model and a method for Chinese fuzzy ontology mapping are proposed.The m...Taking into account that fuzzy ontology mapping has wide application and cannot be dealt with in many fields at present,a Chinese fuzzy ontology model and a method for Chinese fuzzy ontology mapping are proposed.The mapping discovery between two ontologies is achieved by computing the similarity between the concepts of two ontologies.Every concept consists of four features of concept name,property,instance and structure.First,the algorithms of calculating four individual similarities corresponding to the four features are given.Secondly,the similarity vectors consisting of four weighted individual similarities are built,and the weights are the linear function of harmony and reliability.The similarity vector is used to represent the similarity relation between two concepts which belong to different fuzzy ontolgoies.Lastly,Support Vector Machine(SVM) is used to get the mapping concept pairs by the similarity vectors.Experiment results are satisfactory.展开更多
In this paper, we first discuss the relationship between the McShane integral and Pettis integral for vector-valued functions. Then by using the embedding theorems for the fuzzy number space E^1, we give a new equival...In this paper, we first discuss the relationship between the McShane integral and Pettis integral for vector-valued functions. Then by using the embedding theorems for the fuzzy number space E^1, we give a new equivalent condition for （K） integrabihty of a fuzzy set-valued mapping F ： [a, b] → E^1.展开更多
We introduced a new class of fuzzy set-valued variational inclusions with (H,η)-monotone mappings. Using the resolvent operator method in Hilbert spaces, we suggested a new proximal point algorithm for finding approx...We introduced a new class of fuzzy set-valued variational inclusions with (H,η)-monotone mappings. Using the resolvent operator method in Hilbert spaces, we suggested a new proximal point algorithm for finding approximate solutions, which strongly converge to the exact solution of a fuzzy set-valued variational inclusion with (H,η)-monotone. The results improved and generalized the general quasi-variational inclusions with fuzzy set-valued mappings proposed by Jin and Tian Jin MM, Perturbed proximal point algorithm for general quasi-variational inclusions with fuzzy set-valued mappings, OR Transactions, 2005, 9(3): 31-38, (In Chinese); Tian YX, Generalized nonlinear implicit quasi-variational inclusions with fuzzy mappings, Computers & Mathematics with Applications, 2001, 42: 101-108.展开更多
By establishing the concepts of fuzzy approaching set and fuzzy approaching functional mapping and making research on them, a new method for time series prediction is introduced.
Up to now, the study on the cardinal number of fuzzy sets has advanced at on pace since it is very hard to give it an appropriate definition. Althrough for it in [1], it is with some harsh terms and is not reasonable ...Up to now, the study on the cardinal number of fuzzy sets has advanced at on pace since it is very hard to give it an appropriate definition. Althrough for it in [1], it is with some harsh terms and is not reasonable as we point out in this paper. In the paper, we give a general definition of fuzzy cardinal numbers. Based on this definition, we not only obtain a large part of results with re spect to cardinal numbers, but also give a few of new properties of fuzzy cardinal numbers.展开更多
Four layer feedforward regular fuzzy neural networks are constructed. Universal approximations to some continuous fuzzy functions defined on F 0 (R) n by the four layer fuzzy neural networks are shown. At f...Four layer feedforward regular fuzzy neural networks are constructed. Universal approximations to some continuous fuzzy functions defined on F 0 (R) n by the four layer fuzzy neural networks are shown. At first,multivariate Bernstein polynomials associated with fuzzy valued functions are empolyed to approximate continuous fuzzy valued functions defined on each compact set of R n . Secondly,by introducing cut preserving fuzzy mapping,the equivalent conditions for continuous fuzzy functions that can be arbitrarily closely approximated by regular fuzzy neural networks are shown. Finally a few of sufficient and necessary conditions for characterizing approximation capabilities of regular fuzzy neural networks are obtained. And some concrete fuzzy functions demonstrate our conclusions.展开更多
In the economic order quantity （EOQ） model, the decision maker has vague information about holding cost, ordering cost and market demand. With these uncertainties characterized as fuzzy variables, a new formula is d...In the economic order quantity （EOQ） model, the decision maker has vague information about holding cost, ordering cost and market demand. With these uncertainties characterized as fuzzy variables, a new formula is developed by analyzing the fuzzy total cost. By comparing with other four EOQ formulas, i.e., using the crisp numbers with the highest membership values in classic EOQ formula, using the expected values of fuzzy parameters in classic EOQ formula, using the fuzzy variables in classic EOQ formula and then calculating the expected value, and calculat- ing EOQ by hybrid intelligent algorithm simulation, the effectiveness of this formula Js illustrated.展开更多
Collaborating with a squad of Unmanned Aerial Vehicles(UAVs)is challenging for a human operator in a cooperative surveillance task.In this paper,we propose a cognitive model that can dynamically adjust the Levels of A...Collaborating with a squad of Unmanned Aerial Vehicles(UAVs)is challenging for a human operator in a cooperative surveillance task.In this paper,we propose a cognitive model that can dynamically adjust the Levels of Autonomy(LOA)of the human-UAVs team according to the changes in task complexity and human cognitive states.Specifically,we use the Situated Fuzzy Cognitive Map(Si FCM)to model the relations among tasks,situations,human states and LOA.A recurrent structure has been used to learn the strategy of adjusting the LOA,while the collaboration task is separated into a perception routine and a control routine.Experiment results have shown that the workload of the human operator is well balanced with the task efficiency.展开更多
In the aluminum reduction process, aluminum uoride (AlF3) is added to lower the liquidus temperature of the electrolyte and increase the electrolytic ef ciency. Making the decision on the amount of AlF3 addi- tion (re...In the aluminum reduction process, aluminum uoride (AlF3) is added to lower the liquidus temperature of the electrolyte and increase the electrolytic ef ciency. Making the decision on the amount of AlF3 addi- tion (referred to in this work as MDAAA) is a complex and knowledge-based task that must take into con- sideration a variety of interrelated functions;in practice, this decision-making step is performed manually. Due to technician subjectivity and the complexity of the aluminum reduction cell, it is dif cult to guarantee the accuracy of MDAAA based on knowledge-driven or data-driven methods alone. Existing strategies for MDAAA have dif culty covering these complex causalities. In this work, a data and knowl- edge collaboration strategy for MDAAA based on augmented fuzzy cognitive maps (FCMs) is proposed. In the proposed strategy, the fuzzy rules are extracted by extended fuzzy k-means (EFKM) and fuzzy deci- sion trees, which are used to amend the initial structure provided by experts. The state transition algo- rithm (STA) is introduced to detect weight matrices that lead the FCMs to desired steady states. This study then experimentally compares the proposed strategy with some existing research. The results of the comparison show that the speed of FCMs convergence into a stable region based on the STA using the proposed strategy is faster than when using the differential Hebbian learning (DHL), particle swarm optimization (PSO), or genetic algorithm (GA) strategies. In addition, the accuracy of MDAAA based on the proposed method is better than those based on other methods. Accordingly, this paper provides a feasible and effective strategy for MDAAA.展开更多
The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to researc...The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to research.So far,there are lots of methods designed for the measurement of situation awareness status,but there is no model that can measure it accurately in real-time,so this work is conducted to deal with such a gap.Firstly,collect the relevant physiological data of operators while they are performing a specific mission,simultaneously,measure their status of situation awareness by using the situation awareness global assessment technique(SAGAT),which is known for accuracy but cannot be used in real-time.And then,after the preprocessing of the raw data,use the physiological data as features,the SAGAT’s results as a label to train a fuzzy cognitive map(FCM),which is an explainable and powerful intelligent model.Also,a hybrid learning algorithm of particle swarm optimization(PSO)and gradient descent is proposed for the FCM training.The final results show that the learned FCM can assess the status of situation awareness accurately in real-time,and the proposed hybrid learning algorithm has better efficiency and accuracy.展开更多
The fuzzy numerical value analysis method is adopted for the first time, which solves the problem of nanometer electro-thermal in filming process, The key technique is embodied by controlling the time distribution, te...The fuzzy numerical value analysis method is adopted for the first time, which solves the problem of nanometer electro-thermal in filming process, The key technique is embodied by controlling the time distribution, temperature and press in the filming process. The concrete technique of filming is showed by establishing the fuzzy mumbership function of above three indexes, which improves the precision of the materials of nanometer electro-thermal in hot-working. At the same time, the principles of the fuzzy relationship mapping inversion （FRMI） is put forward, Therefore, the standardization and continuity can be met.展开更多
Fuzzy cognitive maps （FCM） is a well-established artificial intelligence technique, which can be effectively applied in the domains of performance measurement, decision making and other management science. FCM can b...Fuzzy cognitive maps （FCM） is a well-established artificial intelligence technique, which can be effectively applied in the domains of performance measurement, decision making and other management science. FCM can be a useful tool in a group decision-making environment by using scientifically integrated expert knowledge. The theories of FCM and balance scorecard （BSC） both emphasize cause-and-effect relationships among indicators in a complex system, but few reports have been published addressing the combined application of these two techniques. In this paper we propose a FCM simulation model for the sample performance measurement system of Intemet-based supply chain, which is constructed by BSC theory. We gave examples to explain how FCM can be adapted to execute the causal mechanism of BSC, and also how FCM can support group decision-making and forecasting in performance measurement.展开更多
Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required infor- mation. Information intelligent p...Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required infor- mation. Information intelligent push technology could replace the traditional method to speed up the information retrieval process. The fuzzy cognitive map has strong knowledge representation ability and reasoning capability. Information intelligent push with the basis on fuzzy cognitive map could ab- stract the computer user＇ s operations to a fuzzy cognitive map, and infer the user＇ s operating inten- tions. The reasoning results will be translated into operational events, and drive the computer system to push appropriate information to the user.展开更多
As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabete...As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world.Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it.Among the diabetics,it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2.To avoid this situation,we propose a new fuzzy logic based neural classifier for early detection of diabetes.A set of new neuro-fuzzy rules is introduced with time constraints that are applied for thefirst level classification.These levels are further refined by using the Fuzzy Cognitive Maps(FCM)with time intervals for making thefinal decision over the classification process.The main objective of this proposed model is to detect the diabetes level based on the time.Also,the set of neuro-fuzzy rules are used for selecting the most contributing values over the decision-making process in diabetes prediction.The proposed model proved its efficiency in performance after experiments conducted not only from the repository but also by using the standard diabetic detection models that are available in the market.展开更多
文摘The concept of b-vex and logarithmic b-vex for fuzzy mappings are introduced by relaxing the definition of convexity of a fuzzy mapping. Most of the basic properties of b-vex fuzzy mapping are discussed and established for the nondifferentiable case. Necessary and sufficient conditions for b-vex fuzzy mapping are presented. Sevaral important results are given for nonlinear fuzzy optimization problems assuming that the objective and constraint functions are b-vex fuzzy mappings.
基金Funded by Excellent youth Teacher Foundation of Chongqing Municipal Education Commission (D2005-37).
文摘A class of generalized implicit quasivariational inclusions with fuzzy mappings in Hilbert space is discussed in this paper which proves an existence theorem of the solutions and proposes a new iterative algorithm and the convergence of the iterative sequence generated by the new algorithm. These results extend and improve some recent corresponding achievements.
基金funded by National Science,Research and Innovation Fund(NSRF)King Mongkut's University of Technology North Bangkok with Contract No.KMUTNB-FF-68-B-46.
文摘In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point results are established in the framework of metric spaces.Based on the presented work,some examples reflecting decision-making problems related to real life are also solved.The suggested method’s flexibility and efficacy compared to conventional techniques are demonstrated in decision-making situations involving uncertainty,such as choosing the best options in multi-criteria settings.We noted that the presented work combines and generalizes two major concepts,the idea of soft sets and hesitant fuzzy set-valued mapping from the existing literature.
文摘In this paper,the pointwise characterizations of fuzzy mappings are given. Based of this definition,we give a few of new properties of fuzzy cardinal numbers.
基金Supported by the National Natural Science Foundation of China (Grant No.10271035)the Scientific Research Foundation Project of Inner Mongolian Education Department (Grant No.NJ06088)
文摘In this paper, a new class of fuzzy mappings called semistrictly convex fuzzy mappings is introduced and we present some properties of this kind of fuzzy mappings. In particular, we prove that a local minimum of a semistrictly convex fuzzy mapping is also a global minimum. We also discuss the relations among convexity, strict convexity and semistrict convexity of fuzzy mapping, and give several sufficient conditions for convexity and semistrict convexity.
文摘In this paper,a perturbed iterative algorithm for finding approximate solutions of variational inclusions for fuzzy mapping,is presented and a convergence result which includes,as a special case,some known results in this field,is given.
基金supported by the Natural Science Foundation of Beijing City under Grant No.4123094the Science and Technology Project of Beijing Municipal Commission of Education under Grants No.KM201110028020,No.KM201010028019+1 种基金the National Nature Science Foundation under Grants No.61100205,No.60873001,No.60863011,No.61175068the Fundamental Research Funds for the Central Universities under Grant No.2009RC0212
文摘Taking into account that fuzzy ontology mapping has wide application and cannot be dealt with in many fields at present,a Chinese fuzzy ontology model and a method for Chinese fuzzy ontology mapping are proposed.The mapping discovery between two ontologies is achieved by computing the similarity between the concepts of two ontologies.Every concept consists of four features of concept name,property,instance and structure.First,the algorithms of calculating four individual similarities corresponding to the four features are given.Secondly,the similarity vectors consisting of four weighted individual similarities are built,and the weights are the linear function of harmony and reliability.The similarity vector is used to represent the similarity relation between two concepts which belong to different fuzzy ontolgoies.Lastly,Support Vector Machine(SVM) is used to get the mapping concept pairs by the similarity vectors.Experiment results are satisfactory.
文摘In this paper, we first discuss the relationship between the McShane integral and Pettis integral for vector-valued functions. Then by using the embedding theorems for the fuzzy number space E^1, we give a new equivalent condition for （K） integrabihty of a fuzzy set-valued mapping F ： [a, b] → E^1.
基金the Natural Science Foundation of China (No. 10471151)the Educational Science Foundation of Chongqing (KJ051307).
文摘We introduced a new class of fuzzy set-valued variational inclusions with (H,η)-monotone mappings. Using the resolvent operator method in Hilbert spaces, we suggested a new proximal point algorithm for finding approximate solutions, which strongly converge to the exact solution of a fuzzy set-valued variational inclusion with (H,η)-monotone. The results improved and generalized the general quasi-variational inclusions with fuzzy set-valued mappings proposed by Jin and Tian Jin MM, Perturbed proximal point algorithm for general quasi-variational inclusions with fuzzy set-valued mappings, OR Transactions, 2005, 9(3): 31-38, (In Chinese); Tian YX, Generalized nonlinear implicit quasi-variational inclusions with fuzzy mappings, Computers & Mathematics with Applications, 2001, 42: 101-108.
文摘By establishing the concepts of fuzzy approaching set and fuzzy approaching functional mapping and making research on them, a new method for time series prediction is introduced.
文摘Up to now, the study on the cardinal number of fuzzy sets has advanced at on pace since it is very hard to give it an appropriate definition. Althrough for it in [1], it is with some harsh terms and is not reasonable as we point out in this paper. In the paper, we give a general definition of fuzzy cardinal numbers. Based on this definition, we not only obtain a large part of results with re spect to cardinal numbers, but also give a few of new properties of fuzzy cardinal numbers.
基金This work was supported by National Natural Science Foundation(699740 4 1 699740 0 6)
文摘Four layer feedforward regular fuzzy neural networks are constructed. Universal approximations to some continuous fuzzy functions defined on F 0 (R) n by the four layer fuzzy neural networks are shown. At first,multivariate Bernstein polynomials associated with fuzzy valued functions are empolyed to approximate continuous fuzzy valued functions defined on each compact set of R n . Secondly,by introducing cut preserving fuzzy mapping,the equivalent conditions for continuous fuzzy functions that can be arbitrarily closely approximated by regular fuzzy neural networks are shown. Finally a few of sufficient and necessary conditions for characterizing approximation capabilities of regular fuzzy neural networks are obtained. And some concrete fuzzy functions demonstrate our conclusions.
基金Supported by National Natural Science Foundation of China (No. 70971092)
文摘In the economic order quantity （EOQ） model, the decision maker has vague information about holding cost, ordering cost and market demand. With these uncertainties characterized as fuzzy variables, a new formula is developed by analyzing the fuzzy total cost. By comparing with other four EOQ formulas, i.e., using the crisp numbers with the highest membership values in classic EOQ formula, using the expected values of fuzzy parameters in classic EOQ formula, using the fuzzy variables in classic EOQ formula and then calculating the expected value, and calculat- ing EOQ by hybrid intelligent algorithm simulation, the effectiveness of this formula Js illustrated.
基金supported by the National Natural Science Foundation of China(No.61876187)。
文摘Collaborating with a squad of Unmanned Aerial Vehicles(UAVs)is challenging for a human operator in a cooperative surveillance task.In this paper,we propose a cognitive model that can dynamically adjust the Levels of Autonomy(LOA)of the human-UAVs team according to the changes in task complexity and human cognitive states.Specifically,we use the Situated Fuzzy Cognitive Map(Si FCM)to model the relations among tasks,situations,human states and LOA.A recurrent structure has been used to learn the strategy of adjusting the LOA,while the collaboration task is separated into a perception routine and a control routine.Experiment results have shown that the workload of the human operator is well balanced with the task efficiency.
文摘In the aluminum reduction process, aluminum uoride (AlF3) is added to lower the liquidus temperature of the electrolyte and increase the electrolytic ef ciency. Making the decision on the amount of AlF3 addi- tion (referred to in this work as MDAAA) is a complex and knowledge-based task that must take into con- sideration a variety of interrelated functions;in practice, this decision-making step is performed manually. Due to technician subjectivity and the complexity of the aluminum reduction cell, it is dif cult to guarantee the accuracy of MDAAA based on knowledge-driven or data-driven methods alone. Existing strategies for MDAAA have dif culty covering these complex causalities. In this work, a data and knowl- edge collaboration strategy for MDAAA based on augmented fuzzy cognitive maps (FCMs) is proposed. In the proposed strategy, the fuzzy rules are extracted by extended fuzzy k-means (EFKM) and fuzzy deci- sion trees, which are used to amend the initial structure provided by experts. The state transition algo- rithm (STA) is introduced to detect weight matrices that lead the FCMs to desired steady states. This study then experimentally compares the proposed strategy with some existing research. The results of the comparison show that the speed of FCMs convergence into a stable region based on the STA using the proposed strategy is faster than when using the differential Hebbian learning (DHL), particle swarm optimization (PSO), or genetic algorithm (GA) strategies. In addition, the accuracy of MDAAA based on the proposed method is better than those based on other methods. Accordingly, this paper provides a feasible and effective strategy for MDAAA.
基金supported by the National Natural Science Foundation of China(61305133)the Aeronautical Science Foundation of China grant number 2020Z023053002.
文摘The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to research.So far,there are lots of methods designed for the measurement of situation awareness status,but there is no model that can measure it accurately in real-time,so this work is conducted to deal with such a gap.Firstly,collect the relevant physiological data of operators while they are performing a specific mission,simultaneously,measure their status of situation awareness by using the situation awareness global assessment technique(SAGAT),which is known for accuracy but cannot be used in real-time.And then,after the preprocessing of the raw data,use the physiological data as features,the SAGAT’s results as a label to train a fuzzy cognitive map(FCM),which is an explainable and powerful intelligent model.Also,a hybrid learning algorithm of particle swarm optimization(PSO)and gradient descent is proposed for the FCM training.The final results show that the learned FCM can assess the status of situation awareness accurately in real-time,and the proposed hybrid learning algorithm has better efficiency and accuracy.
文摘The fuzzy numerical value analysis method is adopted for the first time, which solves the problem of nanometer electro-thermal in filming process, The key technique is embodied by controlling the time distribution, temperature and press in the filming process. The concrete technique of filming is showed by establishing the fuzzy mumbership function of above three indexes, which improves the precision of the materials of nanometer electro-thermal in hot-working. At the same time, the principles of the fuzzy relationship mapping inversion （FRMI） is put forward, Therefore, the standardization and continuity can be met.
基金Funded by Chongqing Natural Science Foundation (No. CSTC2005BB2189) and Chongqing High Tech Projects Foundation (No. 8277)
文摘Fuzzy cognitive maps （FCM） is a well-established artificial intelligence technique, which can be effectively applied in the domains of performance measurement, decision making and other management science. FCM can be a useful tool in a group decision-making environment by using scientifically integrated expert knowledge. The theories of FCM and balance scorecard （BSC） both emphasize cause-and-effect relationships among indicators in a complex system, but few reports have been published addressing the combined application of these two techniques. In this paper we propose a FCM simulation model for the sample performance measurement system of Intemet-based supply chain, which is constructed by BSC theory. We gave examples to explain how FCM can be adapted to execute the causal mechanism of BSC, and also how FCM can support group decision-making and forecasting in performance measurement.
基金Supported by the National Natural Science Foundation of China(61304254)
文摘Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required infor- mation. Information intelligent push technology could replace the traditional method to speed up the information retrieval process. The fuzzy cognitive map has strong knowledge representation ability and reasoning capability. Information intelligent push with the basis on fuzzy cognitive map could ab- stract the computer user＇ s operations to a fuzzy cognitive map, and infer the user＇ s operating inten- tions. The reasoning results will be translated into operational events, and drive the computer system to push appropriate information to the user.
文摘As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world.Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it.Among the diabetics,it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2.To avoid this situation,we propose a new fuzzy logic based neural classifier for early detection of diabetes.A set of new neuro-fuzzy rules is introduced with time constraints that are applied for thefirst level classification.These levels are further refined by using the Fuzzy Cognitive Maps(FCM)with time intervals for making thefinal decision over the classification process.The main objective of this proposed model is to detect the diabetes level based on the time.Also,the set of neuro-fuzzy rules are used for selecting the most contributing values over the decision-making process in diabetes prediction.The proposed model proved its efficiency in performance after experiments conducted not only from the repository but also by using the standard diabetic detection models that are available in the market.
