@inproceedings{7a6451299fd34923921478df4f399e43,
title = "Decision Analysis Applied to Natural Hazards",
abstract = "Formal methods to handle decision-making under uncertainty that have been created for business management lend themselves to applications in many other areas, in which uncertainties play a major role. Hence, the authors and their co-workers have applied decision analysis to landslides since the 1980′s but many other approaches to landslide assessment and management have in principle done so. The keynote lecture itself will illustrate the application of decision analysis with many examples. For this reason, we concentrate in this paper on the principles of decision-making under uncertainty and the concept of using these principles in hazard and risk analysis of natural threats. We also like to note that what we present here is a summary of our past work. The paper starts with an introduction to the decision-making process and its application to natural threats. Risk management of natural threats is then demonstrated in detail with decision trees and Bayesian networks. This leads to sensitivity analyses to determine which risk management action is most effective.",
keywords = "Bayesian networks, Decision making, Landslides, Natural threats",
author = "Einstein, {Herbert H.} and Sousa, {Rita L.}",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 18th International Probabilistic Workshop, IPW 2020 ; Conference date: 12-05-2021 Through 14-05-2021",
year = "2021",
doi = "10.1007/978-3-030-73616-3_1",
language = "English",
isbn = "9783030736156",
series = "Lecture Notes in Civil Engineering",
pages = "3--13",
editor = "Matos, {Jos{\'e} C.} and Louren{\c c}o, {Paulo B.} and Oliveira, {Daniel V.} and Jorge Branco and Dirk Proske and Silva, {Rui A.} and Sousa, {H{\'e}lder S.}",
booktitle = "18th International Probabilistic Workshop, IPW 2020",
}