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- W2072201361 abstract "The application of artificial neural network to compressor performance map prediction is investigated. Different types of artificial neural network such as multilayer perceptron network, radial basis function network, general regression neural network, and a rotated general regression neural network proposed by the authors are considered. Two different models are utilized in simulating the performance map. The results indicate that while the rotated general regression neural network has the least mean error and best agreement to the experimental data, it is however limited to curve fitting application. On the other hand, if one considers a tool for curve fitting as well as for interpolation and extrapolation applications, multilayer perceptron network technique is the most powerful candidate. Further, the compressor efficiency based on the multilayer perceptron network technique is determined. Excellent agreement between the predictions and the experimental data is obtained." @default.
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- W2072201361 date "2007-01-01" @default.
- W2072201361 modified "2023-10-17" @default.
- W2072201361 title "Axial Compressor Performance Map Prediction Using Artificial Neural Network" @default.
- W2072201361 doi "https://doi.org/10.1115/gt2007-27165" @default.
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