Evaluation Model of Bridges Health State Based on DHNN

Min He; Rui Guang Hu; Shi Le; Liang Chen

doi:10.4028/www.scientific.net/AMR.1079-1080.207

Paper Titles

Comparative Study on the Hysteresis Performance of the Metal Rubber Vibration Isolating Bearing with Different Height-Width Ratio Parameter
p.191

CWR Study of the Mechanical Properties of the Finite Element Method-Based Bridge Vertical Plate Non-Ballasted Track
p.195

Development Geo-Seepage Models for Solving Seepage Problems of Large Dam’s Foundations, on an Example of ANSYS Mechanical APDL
p.198

Effect of Low Atmospheric Pressure on Air Content of Fresh Concrete
p.202

Evaluation Model of Bridges Health State Based on DHNN
p.207

Experimental Research on Dynamic Behavior of the Masonry Pagoda Based on Soil-Structure Interaction
p.212

Experimental Study on Seismic Behavior of Recycled Aggregate Concrete Torsion Beams with ABAQUS
p.220

Experimental Research on Improvement of Railway Subgrade Loess Fills Using Lime in Northwest China
p.226

Exploring the Traditional Adobe Dwellings in Hexi Corridor, Gansu Province
p.233

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1079-1080Evaluation Model of Bridges Health State Based on...

Evaluation Model of Bridges Health State Based on DHNN

Abstract:

Inthis paper, according to the more important ten evaluation indicators, the fourgrades ideal evaluation is established corresponding to the level of healthstate of bridges. Combined with associative memory capacity of discreteHopfield neural networks, a new health state evaluation of bridges ispresented. Five bridges is evaluated by the model, the network connectionweights is obtained by iterative learning using the outer product method. Thesimulation results shows that the health evaluation model can evaluate thehealth state of bridges fast, accurately and intuitively.

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Periodical:

Advanced Materials Research (Volumes 1079-1080)

Pages:

207-211

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1079-1080.207

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Online since:

December 2014

Authors:

Min He*, Rui Guang Hu, Shi Le, Liang Chen

Keywords:

Discrete Hopfield Neural Networks, Evaluation Indicators, Health State Evaluation

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* - Corresponding Author

References

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