@inproceedings{6500b1bcf5ce42a78d69d61ff86ed2e3,
title = "Identification of a nonlinear multivariable dynamic process using feed-forward networks",
abstract = "The practical aspects of identifying a nonlinear multi-input multi-output dynamic system using feed-forward neural networks (NN) is the subject of this paper. By utilizing the measurements of 25 input and internal variables of the process, the primary process output is estimated with a network that has one hidden layer and partial connectivity. Two different connectivity patterns are compared, and problems encountered during the development are summarized. The accuracy of the estimate is demonstrated by comparing the NN output with the process output in time domain and frequency domain.",
author = "Can Isik and Cakmakci, {Mete A.}",
year = "1993",
language = "English (US)",
isbn = "0780312007",
series = "1993 IEEE International Conference on Neural Networks",
publisher = "IEEE Computer Society",
pages = "564--567",
editor = "Anon",
booktitle = "1993 IEEE International Conference on Neural Networks",
address = "United States",
note = "1993 IEEE International Conference on Neural Networks ; Conference date: 28-03-1993 Through 01-04-1993",
}