Prediction of Displacements in Unstable Areas Using a Neural Model

E. Binaghi, M. Boschetti, P.A. Brivio, I. Gallo, F. Pergalani () and A. Rampini

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2004, vol. 32, issue 1, 135-154

Abstract: In pipeline management the accurate prediction of weak displacements is a crucial factor in drawing up a prevention policy since the accumulation of these displacements over a period of several years can lead to situations of high risk. This work addresses the specific problem related to the prediction of displacements induced by rainfall in unstable areas, of known geology, and crossed by underground pipelines. A neural model has been configured which learns of displacements from instrumented sites (where inclinometric measurements are available) and is able to generalise to other sites not equipped with inclinometers. Copyright Kluwer Academic Publishers 2004

Keywords: unstable areas; lifeline; multilayer perceptron neural network; prediction; multisource data analysis; rainfall (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1023/B:NHAZ.0000026796.59079.1a

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