Add to ORKGA new method of correlating the output variable with the input variables of the system has been used in this project to determine the extent of time delays. The proposed method has an intuitive appeal and is easy to apply. Based on the data obtained for an industrial heater, various series-parallel neural networks of different external configurations are constructed and examined for their capabilities as one-step ahead predictors as well as long term predictors.RP 15/9
The suitability of pattern recognition for process monitoring of chemical plants is discussed. Exper...
A neural network approach for on-line parameter estimation in unknown or poorly known processes with...
Stricter environmental regulations and a greater need for waste minimization have increased the impo...
A new method of correlating the output variable with the input variables of the system has been used...
Abstract--The integration of Soft Computing techniques in traditional real-time systems is a promisi...
Purpose - To develop a new predictive control scheme based on neural networks for linear and non-lin...
This paper presents an two weighted neural network approach to determine the delay time for a heatin...
This paper presents an approach for realtime systems, as hybrid testing, active and semiactive contr...
Abstract- In this paper, a neural network based predictive controller is designed to govern the dyna...
A very important problem in designing of controlling systems is to choose the right type of architec...
In order to optimize the quality of transition processes on a heating object of control, it is propo...
Neural Network approaches to time series prediction are briefly discussed, and the need to find the ...
Boiler combustion systems represent highly nonlinear systems with associated lags and delays which ...
It is critical that modern control theory techniques be integrated into assignments which involve th...
In a thermal power plant with once-through boilers, it is important to control the temperature at th...
The suitability of pattern recognition for process monitoring of chemical plants is discussed. Exper...
A neural network approach for on-line parameter estimation in unknown or poorly known processes with...
Stricter environmental regulations and a greater need for waste minimization have increased the impo...
A new method of correlating the output variable with the input variables of the system has been used...
Abstract--The integration of Soft Computing techniques in traditional real-time systems is a promisi...
Purpose - To develop a new predictive control scheme based on neural networks for linear and non-lin...
This paper presents an two weighted neural network approach to determine the delay time for a heatin...
This paper presents an approach for realtime systems, as hybrid testing, active and semiactive contr...
Abstract- In this paper, a neural network based predictive controller is designed to govern the dyna...
A very important problem in designing of controlling systems is to choose the right type of architec...
In order to optimize the quality of transition processes on a heating object of control, it is propo...
Neural Network approaches to time series prediction are briefly discussed, and the need to find the ...
Boiler combustion systems represent highly nonlinear systems with associated lags and delays which ...
It is critical that modern control theory techniques be integrated into assignments which involve th...
In a thermal power plant with once-through boilers, it is important to control the temperature at th...
The suitability of pattern recognition for process monitoring of chemical plants is discussed. Exper...
A neural network approach for on-line parameter estimation in unknown or poorly known processes with...
Stricter environmental regulations and a greater need for waste minimization have increased the impo...