NEURAL NETWORK FOR STABILITY ANALYSIS OF RUBBLE-MOUND BREAKWATERS

This paper examines the applicability of a neural network to analyze model test data of the stability of rubble-mound breakwaters. The neural network is an information-processing system, modeled on the structure of the human brain, that is able to deal with information whose interrelation is not clear. Seven parameters concerning the stability of rock slopes are used: the stability number, the damage level, the number of attacking waves, the surf-similarity parameter, the permeability parameter, the dimensionless water depth in front of the structure, and the spectral shape parameter. The damage levels predicted by the neural network, calibrated by using a part of Van der Meer's 1988 experimental data, agree satisfactorily well with the measured damage levels of another part of the data source by Van der Meer 1988 and by Smith et al's 1992 data. The agreement between the predicted stability numbers by the neural network and the measured stability numbers is also good.

• Supplemental Notes:
  • J Waterway, Port, Coastal, and Ocean Engng, v 121 n 6, Nov/Dec 1995, p 294 [6 p, 11 ref, 12 fig]
• Authors:
  • Mase, Hajime
  • SAKAMOTO, M
  • Sakai, T
• Publication Date: 1995

Language

• English

Subject/Index Terms

• TRT Terms: Artificial intelligence; Networks; Rubble mound breakwaters; Stability (Mechanics)
• Subject Areas: Data and Information Technology; Marine Transportation;

Filing Info

• Accession Number: 00718455
• Record Type: Publication
• Source Agency: British Maritime Technology
• Files: TRIS
• Created Date: Mar 27 1996 12:00AM