Artificial neural networks in civil engineering: another five years of research in Poland

  • Zenon Waszczyszyn Department of Structural Mechanics, Rzeszów University of Technology

Abstract

This state-of-the-art-paper is a resume of research activity of a non-formal Research Group on Artificial Neural Networks (RGANN) applications in Civil Engineering (CE). RGANN has been working at the Cracow University of Technology, Poland, since 1996 under the supervision of the author of this paper. Ten years 1996-2005 of the research and teaching activity of RGANN was reported in paper [61]. The present paper briefly reports on the activities originated in the ten year period and their continuation after 2005. The main attention is focused on new research carried out in the five year period 2006-2011. The paper discusses some selected problems which are included in fourteen supplementary papers, marked in references of these papers as published in this CAMES Special Issue. The attention is focused on: Hybrid Computational Systems, development of modifications of ANNs and methods of their learning, Bayesian neural networks and Bayesian inference methods, damage identification in CE structures, structure health monitoring, applications of ANNs in mechanics of structures and materials, joining of ANNs with measurements on laboratory models and real structures, development of new non-destructive measurement methods, applications of ANNs in health structure monitoring and repair, applications of ANNs in geotechnics and geodesy. The paper is based on the supplementary papers which were presented at the Special Session on Applications of ANNs at the 57th Polish Civil Engineering Conference in Krynica, 2011, see [74].

Keywords

Civil Engineering Artificial (CE), Neural Network (ANN), Standard NN (SNN), Multi-Layred Perceptron (MLP), Fuzzy Weight NN (FWNN), Kalman Filtering (KF), Bayesian NN (BNN), True-BNN (TBNN), Semi-Bayesian NN (SBNN), Gaussian Process (GP), (MES), Em- pirical Data (EMP), Hybrid Monte Carlo Method (HMCM), Hybrid Updated Algorithm (HUA), Neural Material Model (NMM), Structural Health Monitoring (SHM),

References

Published
Jan 25, 2017
How to Cite
WASZCZYSZYN, Zenon. Artificial neural networks in civil engineering: another five years of research in Poland. Computer Assisted Methods in Engineering and Science, [S.l.], v. 18, n. 3, p. 131–146, jan. 2017. ISSN 2299-3649. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/110>. Date accessed: 26 jan. 2022.
Section
Articles