Modeling beach realignment using a neuro-fuzzy network optimized by a novel backtracking search algorithm-Reference-Cited by-同舟云学术

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Modeling beach realignment using a neuro-fuzzy network optimized by a novel backtracking search algorithm

Published:2018-10-13 Issue:6 Volume:31 Page:1747-1763
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Chatzipavlis Antonios,Tsekouras George E.,Trygonis Vasilis,Velegrakis Adonis F.,Tsimikas John,Rigos Anastasios,Hasiotis Thomas,Salmas Constantinos

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s00521-018-3809-2.pdf

Reference59 articles.

1. Allenbach K, Garonna I, Herold C, Monioudi I, Giuliani G, Lehmann AF, Velegrakis AF (2015) Black Sea beach vulnerability to sea level rise. Environ Sci Policy 46:95–109

2. Armstrong JS (1985) Long-range forecasting: from crystal ball to computer, 2nd edn. Wiley, Hoboken

3. Atkinson AL, Power HE, Moura T, Hammond T, Callaghan DP, Baldock TE (2017) Assessment of runup predictions by empirical models on non-truncated beaches on the south-east Australian coast. Coast Eng 119:15–31

4. Briganti R, Bellotti G, Franco L, De Rouck J, Geeraerts J (2005) Field measurements of wave overtopping at the rubble mound breakwater of Rome-Ostia yacht harbour. Coast Eng 52(12):1155–1174

5. Chatterjee S, Nigam S, Roy A (2016) Software fault prediction using neuro-fuzzy network and evolutionary learning approach. Neural Comput Appl. https://doi.org/10.1007/s00521-016-2437-y

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