A modeling method of artificial neural network (ANN) is proposed. Experiment data were evaluated and projected by using data envelopment analysis (DEA), a widely used method to evaluate relative efficiency between decision making units. The data would become more scientific and reasonable, and all of them could be used for modeling of ANN. Example shows that the model of ANN, which gained by training these data, is DEA effective. So it is a new method for optimal data utilizing and modeling. The method is useful to the research, which may only get limited and high cost data after sever times or several years of experiments.EI
Energy is essential parameter for economic – social development and quality of life. Sustainable ene...
The study of efficiency measurement was pioneered by Farnell in 1957. Since then, researchers in thi...
the neural network, fuzzy set theory and evolutionary algorithm in artificial intelligence are all i...
When people make use of the limited, expensive and historical data to build multiple-input and multi...
In this study, we propose a new Artificial Neural Networks (ANN) training approach that closes the g...
Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement of the eff...
Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and pro...
Input and output selection in Data Envelopment Analysis (DEA) has many important. In this research, ...
Nowadays, the one of sections which is studied about is Artificial Neural Network (ANN) Models. ANN ...
Abstract—In this paper, we show how the data envelopment analysis (DEA) model might be useful to scr...
Artificial Neural Networks (ANN) approach is an alternate way to classical methods. As a computation...
Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and pro...
This article studies the creation of efficiency measurement structures of Decision-Making Units (DMU...
Artificial neuron network (ANN) is non linear mapping structures based on the function of human inte...
Neural network is a web of million numbers of inter-connected neurons which executes parallel proces...
Energy is essential parameter for economic – social development and quality of life. Sustainable ene...
The study of efficiency measurement was pioneered by Farnell in 1957. Since then, researchers in thi...
the neural network, fuzzy set theory and evolutionary algorithm in artificial intelligence are all i...
When people make use of the limited, expensive and historical data to build multiple-input and multi...
In this study, we propose a new Artificial Neural Networks (ANN) training approach that closes the g...
Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement of the eff...
Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and pro...
Input and output selection in Data Envelopment Analysis (DEA) has many important. In this research, ...
Nowadays, the one of sections which is studied about is Artificial Neural Network (ANN) Models. ANN ...
Abstract—In this paper, we show how the data envelopment analysis (DEA) model might be useful to scr...
Artificial Neural Networks (ANN) approach is an alternate way to classical methods. As a computation...
Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and pro...
This article studies the creation of efficiency measurement structures of Decision-Making Units (DMU...
Artificial neuron network (ANN) is non linear mapping structures based on the function of human inte...
Neural network is a web of million numbers of inter-connected neurons which executes parallel proces...
Energy is essential parameter for economic – social development and quality of life. Sustainable ene...
The study of efficiency measurement was pioneered by Farnell in 1957. Since then, researchers in thi...
the neural network, fuzzy set theory and evolutionary algorithm in artificial intelligence are all i...