Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/20870
Title: Development of neural networks in civil engineering applications
Authors: Zhang, Yun
Keywords: DRNTU::Engineering::Civil engineering
Issue Date: 2010
Source: Zhang, Y. (2010). Development of neural networks in civil engineering applications. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: The architecture of neural networks (NNs) has a significant impact on a network’s generalization ability. Ensemble neural networks (ENNs) are commonly used networks in many engineering applications due to their better generalization properties. An ENN usually includes several back-propagation networks in its structure, where the back-propagation network is a single feed-forward network trained with the back-propagation learning rule. In this thesis, the Akaike information criterion (AIC) and the entropy are used as the automating design tools for balancing the generalization against the parameters and finding the best combining weights of the ENNs. Two ENNs, namely, the AIC based ENN and the entropy based ENN are developed first. Since the AIC and entropy have their own merits for solving different problems, a new AIC-entropy based ENN is developed. Two analytical functions – the peak function and Friedman function are used first to assess the accuracy of the proposed ensemble approaches. The verified approaches are then applied to the civil engineering applications.
URI: https://hdl.handle.net/10356/20870
DOI: 10.32657/10356/20870
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:CEE Theses

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