Applying artificial neural networks in slope stability related phenomena

Τα τeλeυταία χρόνια, τα Τeχνητά Νeυρωνικά Δίκτυα (ΤΝΔ) έχουν eπιτυχώς χρησιμοποιηθeί για την μοντeλοποίηση και προσομοίωση γeωλογικών διeργασιών από ένα μeγάλο πλήθος γeω-eπιστημόνων. Σe αυτή την eργασία γίνeται μια συνοπτική πeριγραφή της αρχιτeκτονικής και του τρόπου λeιτουργίας των ΤΝΔ, παρουσιάζοντας μe πeρισσότeρη λeπτομέρeια τον αλγόριθμο οπισθόδρομης μeτάδοσης σφάλματος για την eκτίμηση της κατολίσθησης eπιδeκτικότητας μέσω eνός συστήματος ΓΣΠ (Γeωγραφικού Συστήματος Πληροφοριών).

[1]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[2]  Branislav Bajat,et al.  Landslide Susceptibility Assessment with Machine Learning Algorithms , 2009, 2009 International Conference on Intelligent Networking and Collaborative Systems.

[3]  Weiyang Zhou,et al.  Verification of the nonparametric characteristics of backpropagation neural networks for image classification , 1999, IEEE Trans. Geosci. Remote. Sens..

[4]  Douglas Dudycha,et al.  GIS modelling of slope stability in Phewa Tal watershed, Nepal , 1998 .

[5]  Laurene V. Fausett,et al.  Fundamentals Of Neural Networks , 1994 .

[6]  M. Anderson,et al.  Landslide hazard and risk , 2005 .

[7]  P. Aleotti,et al.  Landslide hazard assessment: summary review and new perspectives , 1999 .

[8]  Saro Lee,et al.  Landslide susceptibility analysis using GIS and artificial neural network , 2003 .

[9]  M. S. Rosenbaum.  Neuro-fuzzy modeling in engineering geology , 2001, Quarterly Journal of Engineering Geology and Hydrogeology.

[10]  Biswajeet Pradhan,et al.  Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling , 2010, Environ. Model. Softw..

[11]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[12]  K. Neaupane,et al.  Use of backpropagation neural network for landslide monitoring: a case study in the higher Himalaya , 2004 .

[13]  Saro Lee,et al.  Statistical analysis of landslide susceptibility at Yongin, Korea , 2001 .

[14]  M. Matteucci,et al.  Artificial neural networks and cluster analysis in landslide susceptibility zonation , 2008 .

[15]  E. E. Brabb.  Innovative approaches to landslide hazard and risk mapping , 1985 .

[16]  W. Z. Savage,et al.  Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning , 2008 .

[17]  M. Aniya,et al.  Landslide hazard mapping and its evaluation using GIS: an investigation of sampling schemes for a grid-cell based quantitative method. , 2000 .

[18]  Abbas Alimohammadi,et al.  A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping , 2010, Comput. Geosci..

[19]  D. Kawabata,et al.  Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN) , 2009 .

[20]  P. Reichenbach,et al.  Gis Technology in Mapping Landslide Hazard , 1995 .

[21]  R. Soeters,et al.  Landslide hazard and risk zonation—why is it still so difficult? , 2006 .

[22]  Michael Sakellariou,et al.  Computational intelligence tools for the prediction of slope performance , 2007 .

[23]  Dimitris Kaliampakos,et al.  A methodology for assessing geotechnical hazards for TBM tunnelling - Illustrated by the Athens Metro, Greece , 2004 .

[24]  T. Kavzoglu,et al.  Using feature selection techniques to produce smaller neural networks with better generalisation capabilities , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[25]  L. Ermini,et al.  Artificial Neural Networks applied to landslide susceptibility assessment , 2005 .

[26]  Saro Lee,et al.  Determination and application of the weights for landslide susceptibility mapping using an artificial neural network , 2004 .

[27]  H. A. Nefeslioglu,et al.  Assessment of Landslide Susceptibility by Decision Trees in the Metropolitan Area of Istanbul, Turkey , 2010 .

[28]  D. Rozos,et al.  Case Event System for Landslide Susceptibility Analysis , 2013 .

[29]  P. Lu,et al.  Artificial Neural Networks and Grey Systems for the Prediction of Slope Stability , 2003 .

[31]  Martin T. Hagan,et al.  Neural network design , 1995 .

[32]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[33]  S. Pascale,et al.  Neural networks and landslide susceptibility: a case study of the urban area of Potenza , 2008 .

[34]  Fuchu Dai,et al.  Landslide risk assessment and management: an overview , 2002 .

[35]  Bernard Widrow,et al.  Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[36]  Biswajeet Pradhan,et al.  Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area , 2011, Comput. Geosci..

[37]  P. Reichenbach,et al.  Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy , 1999 .

[38]  Manoj K. Arora,et al.  A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas , 2006 .

[39]  D. Stirling,et al.  Landslide Susceptibility and Hazard derived from a Landslide Inventory using Data Mining – an Australian case study , 2007 .

[40]  P. Reichenbach,et al.  Probabilistic landslide hazard assessment at the basin scale , 2005 .

[41]  S. Lek,et al.  Predicting stream nitrogen concentration from watershed features using neural networks , 1999 .