To improve the ability and precisions of the fuzzy control,this thesis points out the adjusted fuzzy control method,realizes the precision of the fuzzy quantity, and reduces the number of the fuzzy control rules,so th...To improve the ability and precisions of the fuzzy control,this thesis points out the adjusted fuzzy control method,realizes the precision of the fuzzy quantity, and reduces the number of the fuzzy control rules,so that it can predigest the process of disigns and realize the methods without influencing the idiocratic control,which are on the base of the domain flexing.展开更多
Present study proposes a method for fuzzy time series forecasting based on difference parameters.The developed method has been presented in a form of simple computational algorithm.It utilizes various difference param...Present study proposes a method for fuzzy time series forecasting based on difference parameters.The developed method has been presented in a form of simple computational algorithm.It utilizes various difference parameters being implemented on current state for forecasting the next state values to accommodate the possible vagueness in the data in an efficient way.The developed model has been simulated on the historical student enrollments data of University of Alabama and the obtained forecasted values have been compared with the existing methods to show its superiority.Further,the developed model has also been implemented in forecasting the movement of market prices of share of State Bank of India(SBI)at Bombay Stock Exchange(BSE),India.展开更多
文摘To improve the ability and precisions of the fuzzy control,this thesis points out the adjusted fuzzy control method,realizes the precision of the fuzzy quantity, and reduces the number of the fuzzy control rules,so that it can predigest the process of disigns and realize the methods without influencing the idiocratic control,which are on the base of the domain flexing.
文摘Present study proposes a method for fuzzy time series forecasting based on difference parameters.The developed method has been presented in a form of simple computational algorithm.It utilizes various difference parameters being implemented on current state for forecasting the next state values to accommodate the possible vagueness in the data in an efficient way.The developed model has been simulated on the historical student enrollments data of University of Alabama and the obtained forecasted values have been compared with the existing methods to show its superiority.Further,the developed model has also been implemented in forecasting the movement of market prices of share of State Bank of India(SBI)at Bombay Stock Exchange(BSE),India.
