Helicopter mathematical model mainly depends on design helicopter control system, flight simulator, and real time control simulation system. But it is difficult to establish a helicopter flight dynamics mathematical ...Helicopter mathematical model mainly depends on design helicopter control system, flight simulator, and real time control simulation system. But it is difficult to establish a helicopter flight dynamics mathematical model that has features such as rapidness, reliability and precision, because there is no unique and precise expression to some sophisticated phenomenon of helicopter. In this paper a fuzzy helicopter flight model is constructed based on the flight experimental data. The fuzzy model, which is identified by fuzzy inference, has characteristics of computed rapidness and high precision. In order to guarantee the precision of the identified fuzzy model, a new method is adopted to handle the conflict fuzzy rules. Additionally, using fuzzy clustering technology can effectively reduce the number of rules of fuzzy model, namely, the order of the fuzzy model. The simulation results indicate that the method of this paper is effective and feasible.展开更多
The adaptive neural fuzzy inference system （ANFIS） is used to make a ease study considering features of complex social-technical system with the target of increasing organizational efficiency of public scientific re...The adaptive neural fuzzy inference system （ANFIS） is used to make a ease study considering features of complex social-technical system with the target of increasing organizational efficiency of public scientific research institutions. An integrated ANFIS model is built and the effectiveness of the model is verified by means of investigation data and their processing results. The model merges the learning mechanism of neural network and the language inference ability of fuzzy system, and thereby remedies the defects of neural network and fuzzy logic system. Result of this case study shows that the model is suitable for complicated socio-technical systems and has bright application perspective to solve such problems of prediction, evaluation and policy-making in managerial fields.展开更多
The underwater target recognition is a key technology in acoustic confrontation and underwater defence. In this article, a recognition system based on fuzzy logic inference (FLI) is set up. This system is mainly compo...The underwater target recognition is a key technology in acoustic confrontation and underwater defence. In this article, a recognition system based on fuzzy logic inference (FLI) is set up. This system is mainly composed of three parts: the fuzzy input module, the fuzzy logic inference module with a set of inference rules and the de-fuzzy output module. The inference result shows the recognition system is effective in most conditions.展开更多
The spontaneous combustion is a smoldering process and characterized by a slow burning speed and a long duration. Therefore, it is a hazard to coal mines. Early detection of coal mine spontaneous combustion is quite d...The spontaneous combustion is a smoldering process and characterized by a slow burning speed and a long duration. Therefore, it is a hazard to coal mines. Early detection of coal mine spontaneous combustion is quite difficult because of the complexity of different coal mines. And the traditional threshold discriminance is not suitable for spontaneous combustion detection due to the uncertainty of coalmine combustion. Restrictions of the single detection method will also affect the detection precision in the early time of spontaneous combustion. Although multiple detection methods can be adopted as a complementarity to improve the accuracy of detection, the synthesized method will in- crease the complicacy of criterion, making it difficult to estimate the combustion. To solve this problem, a fuzzy inference system based on CRI （Compositional Rule of Inference） and fuzzy reasoning method FITA （First Infer Then Aggregate） are presented. And the neural network is also developed to realize the fuzzy inference system. Finally, the effectiveness of the inference system is demonstrated bv means of an experiment.展开更多
This paper mainly describes that loose of jig bed affects jig's separation effect, and the corresponding fuzzy rules were built. Using the evaluating index of jig's separation effect--imperfection (I) and tota...This paper mainly describes that loose of jig bed affects jig's separation effect, and the corresponding fuzzy rules were built. Using the evaluating index of jig's separation effect--imperfection (I) and total misplaced material (Cz), it evaluates status of loose of jig bed by fuzzy inference system. Experimental simulation and applications in practice prove the method's feasibility.展开更多
It has been shown in recent economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones. However, the literature on combining forecasts has almost exclusively foc...It has been shown in recent economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones. However, the literature on combining forecasts has almost exclusively focused on linear combining forecasts. In this paper, a new nonlinear combination forecasting method based on fuzzy inference system is present to overcome the difficulties and drawbacks in linear combination modeling of non-stationary time series. Furthermore, the optimization algorithm based on a hierarchical structure of learning automata is used to identify the parameters of the fuzzy system. Experiment results related to numerical examples demonstrate that the new technique has excellent identification performances and forecasting accuracy superior to other existing linear combining forecasts.展开更多
The application of Co（Ⅲ）/Al2O3 catalyst in Fischer-Tropsch synthesis（FTS）was studied in a wide range of synthesis gas conversions and compared with Fuzzy Simulation results.Present study applies fuzzy model to pr...The application of Co（Ⅲ）/Al2O3 catalyst in Fischer-Tropsch synthesis（FTS）was studied in a wide range of synthesis gas conversions and compared with Fuzzy Simulation results.Present study applies fuzzy model to predicting the product composition of CH4,CO2 and CO in Fischer-Tropsch process for natural gas synthesis,in which the input vector was 4-dimension including four variables（operating pressure, operating temperature,time and CO/H2 ratio）of 70 different experiments and the output product is a composition of CO2,CO and CH4. The Mamdani algorithm has been applied to the training of the fuzzy system and the test set was used to evaluate the performance of the system including R2,ARE,AARE and SD.The results demonstrated that the predicted values from the model were in good consistency with the experimental data.The work indicates how fuzzy inference system（FIS）,as a promising predicting technique,would be effectively used in FTS.展开更多
Mechanical reliability prediction (MRP) is an important task of mechanical reliability design. In the initial design stage (IDS), the lack of reliability data and some fuzzy characteristics of MRP make this work hardn...Mechanical reliability prediction (MRP) is an important task of mechanical reliability design. In the initial design stage (IDS), the lack of reliability data and some fuzzy characteristics of MRP make this work hardness. Because fuzzy synthetical assessment (FSA) can well utilize expert′s experience and fuzzy data, it is used to assess the influence factors of reliability. On the basis of the assessed results, the predicted value of reliability is inferred by the fuzzy inference system (FIS). This approach particularly suits to predict the reliability of complex machinery (including other products) in IDS, so that it can remedy some defects of the existing methods. An example is discussed to interpret how to utilize it.展开更多
文摘Helicopter mathematical model mainly depends on design helicopter control system, flight simulator, and real time control simulation system. But it is difficult to establish a helicopter flight dynamics mathematical model that has features such as rapidness, reliability and precision, because there is no unique and precise expression to some sophisticated phenomenon of helicopter. In this paper a fuzzy helicopter flight model is constructed based on the flight experimental data. The fuzzy model, which is identified by fuzzy inference, has characteristics of computed rapidness and high precision. In order to guarantee the precision of the identified fuzzy model, a new method is adopted to handle the conflict fuzzy rules. Additionally, using fuzzy clustering technology can effectively reduce the number of rules of fuzzy model, namely, the order of the fuzzy model. The simulation results indicate that the method of this paper is effective and feasible.
基金Supported by the Soft Science Program of Jiangsu Province(BR2010079)~~
文摘The adaptive neural fuzzy inference system （ANFIS） is used to make a ease study considering features of complex social-technical system with the target of increasing organizational efficiency of public scientific research institutions. An integrated ANFIS model is built and the effectiveness of the model is verified by means of investigation data and their processing results. The model merges the learning mechanism of neural network and the language inference ability of fuzzy system, and thereby remedies the defects of neural network and fuzzy logic system. Result of this case study shows that the model is suitable for complicated socio-technical systems and has bright application perspective to solve such problems of prediction, evaluation and policy-making in managerial fields.
文摘The underwater target recognition is a key technology in acoustic confrontation and underwater defence. In this article, a recognition system based on fuzzy logic inference (FLI) is set up. This system is mainly composed of three parts: the fuzzy input module, the fuzzy logic inference module with a set of inference rules and the de-fuzzy output module. The inference result shows the recognition system is effective in most conditions.
基金Project 20050290010 supported by the Doctoral Foundation of Chinese Education Ministry and 2005AA133070 by National 863 Program for High Technique Research Development
文摘The spontaneous combustion is a smoldering process and characterized by a slow burning speed and a long duration. Therefore, it is a hazard to coal mines. Early detection of coal mine spontaneous combustion is quite difficult because of the complexity of different coal mines. And the traditional threshold discriminance is not suitable for spontaneous combustion detection due to the uncertainty of coalmine combustion. Restrictions of the single detection method will also affect the detection precision in the early time of spontaneous combustion. Although multiple detection methods can be adopted as a complementarity to improve the accuracy of detection, the synthesized method will in- crease the complicacy of criterion, making it difficult to estimate the combustion. To solve this problem, a fuzzy inference system based on CRI （Compositional Rule of Inference） and fuzzy reasoning method FITA （First Infer Then Aggregate） are presented. And the neural network is also developed to realize the fuzzy inference system. Finally, the effectiveness of the inference system is demonstrated bv means of an experiment.
文摘This paper mainly describes that loose of jig bed affects jig's separation effect, and the corresponding fuzzy rules were built. Using the evaluating index of jig's separation effect--imperfection (I) and total misplaced material (Cz), it evaluates status of loose of jig bed by fuzzy inference system. Experimental simulation and applications in practice prove the method's feasibility.
基金Funded by the Excellent Young Teachers of MOE (350) and Chongqing Education Committee Foundation
文摘It has been shown in recent economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones. However, the literature on combining forecasts has almost exclusively focused on linear combining forecasts. In this paper, a new nonlinear combination forecasting method based on fuzzy inference system is present to overcome the difficulties and drawbacks in linear combination modeling of non-stationary time series. Furthermore, the optimization algorithm based on a hierarchical structure of learning automata is used to identify the parameters of the fuzzy system. Experiment results related to numerical examples demonstrate that the new technique has excellent identification performances and forecasting accuracy superior to other existing linear combining forecasts.
文摘The application of Co（Ⅲ）/Al2O3 catalyst in Fischer-Tropsch synthesis（FTS）was studied in a wide range of synthesis gas conversions and compared with Fuzzy Simulation results.Present study applies fuzzy model to predicting the product composition of CH4,CO2 and CO in Fischer-Tropsch process for natural gas synthesis,in which the input vector was 4-dimension including four variables（operating pressure, operating temperature,time and CO/H2 ratio）of 70 different experiments and the output product is a composition of CO2,CO and CH4. The Mamdani algorithm has been applied to the training of the fuzzy system and the test set was used to evaluate the performance of the system including R2,ARE,AARE and SD.The results demonstrated that the predicted values from the model were in good consistency with the experimental data.The work indicates how fuzzy inference system（FIS）,as a promising predicting technique,would be effectively used in FTS.
文摘Mechanical reliability prediction (MRP) is an important task of mechanical reliability design. In the initial design stage (IDS), the lack of reliability data and some fuzzy characteristics of MRP make this work hardness. Because fuzzy synthetical assessment (FSA) can well utilize expert′s experience and fuzzy data, it is used to assess the influence factors of reliability. On the basis of the assessed results, the predicted value of reliability is inferred by the fuzzy inference system (FIS). This approach particularly suits to predict the reliability of complex machinery (including other products) in IDS, so that it can remedy some defects of the existing methods. An example is discussed to interpret how to utilize it.
