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A genetic algorithm-artificial neural network method for the prediction of longitudinal dispersion coefficient in rivers
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Yang, Jianhua, Hines, Evor, Guymer, I, Iliescu, Daciana, Leeson, Mark S., King, G. P. and Li, XuQin (2008) A genetic algorithm-artificial neural network method for the prediction of longitudinal dispersion coefficient in rivers. In: Porto Pazos, Ana B. and Sierra, Alejandro Pazos and Buceta, Washington Buño, (eds.) Advancing Artificial Intelligence through Biological Process Applications. London: Medical Information Science Reference, pp. 358-374. ISBN 9781599049960
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Official URL: http://dx.doi.org/10.4018/978-1-59904-996-0.ch019
Abstract
In this chapter a novel method, the Genetic Neural Mathematical Method (GNMM), for the prediction of longitudinal dispersion coefficient is presented. This hybrid method utilizes Genetic Algorithms (GAs) to identify variables that are being input into a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN), which simplifies the neural network structure and makes the training process more efficient. Once input variables are determined, GNMM processes the data using an MLP with the back-propagation algorithm. The MLP is presented with a series of training examples and the internal weights are adjusted in an attempt to model the input/output relationship. GNMM is able to extract regression rules from the trained neural network. The effectiveness of GNMM is demonstrated by means of case study data, which has previously been explored by other authors using various methods. By comparing the results generated by GNMM to those presented in the literature, the effectiveness of this methodology is demonstrated.
Item Type: | Book Item | ||||
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Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
Publisher: | Medical Information Science Reference | ||||
Place of Publication: | London | ||||
ISBN: | 9781599049960 | ||||
Book Title: | Advancing Artificial Intelligence through Biological Process Applications | ||||
Editor: | Porto Pazos, Ana B. and Sierra, Alejandro Pazos and Buceta, Washington Buño | ||||
Official Date: | 2008 | ||||
Dates: |
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Number of Pages: | 17 | ||||
Page Range: | pp. 358-374 | ||||
DOI: | 10.4018/978-1-59904-996-0.ch019 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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