Abstract: Traditional approaches to measure risk to natural hazards considers the use of composite indices. However,
most of the times such indices are built assuming linear interrelations (interdependencies) between the aggregated
components in such a way that the final index value is based only on an accumulative or scalable
structure. In this paper we propose the use of Fuzzy Inference Systems type Mamdami in order to aggregate
physical seismic risk and social vulnerability indicators. The aggregation is made by establishing rules (ifthen
type) over the indicators in order to get an index. Finally a quantitative seismic risk estimation is made
though the convolution of these two main factors by means of fuzzy inferences, in such a way that no linear
assumptions are used along the estimation. We applied the fuzzy model over the city of Bogota Colombia.
We consider that this approach is a useful way to estimate a measure of an intangible reality such as seismic
risk, by assuming the urban settlement’s complexity where the interrelations between the associated risk
components are inherently non-linear. The proposed model possess a practical use over the risk management
field, since the design of the logic rules uses a smooth application of risk management knowledge following
a multidisciplinary approach, thus making the model easily adapted to a particular circumstance or context
regardless the background of the final user.(More)

Traditional approaches to measure risk to natural hazards considers the use of composite indices. However, most of the times such indices are built assuming linear interrelations (interdependencies) between the aggregated components in such a way that the final index value is based only on an accumulative or scalable structure. In this paper we propose the use of Fuzzy Inference Systems type Mamdami in order to aggregate physical seismic risk and social vulnerability indicators. The aggregation is made by establishing rules (ifthen type) over the indicators in order to get an index. Finally a quantitative seismic risk estimation is made though the convolution of these two main factors by means of fuzzy inferences, in such a way that no linear assumptions are used along the estimation. We applied the fuzzy model over the city of Bogota Colombia. We consider that this approach is a useful way to estimate a measure of an intangible reality such as seismic risk, by assuming the urban settlement’s complexity where the interrelations between the associated risk components are inherently non-linear. The proposed model possess a practical use over the risk management field, since the design of the logic rules uses a smooth application of risk management knowledge following a multidisciplinary approach, thus making the model easily adapted to a particular circumstance or context regardless the background of the final user.

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González Cárdenas, J.; Nebot, À.; Mugica, F. and Crowley, H. (2015). Tackling Non-linearity in Seismic Risk Estimation using Fuzzy Methods.In Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCES, (SIMULTECH 2015) ISBN 978-989-758-120-5, ISSN 2184-2841, pages 532-541

@conference{mscces15, author={J. Rubén González Cárdenas. and Àngela Nebot. and Francisco Mugica. and Helen Crowley.}, title={Tackling Non-linearity in Seismic Risk Estimation using Fuzzy Methods}, booktitle={Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCES, (SIMULTECH 2015)}, year={2015}, pages={532-541}, publisher={SciTePress}, organization={INSTICC}, doi={}, isbn={978-989-758-120-5}, }

TY - CONF

JO - Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCES, (SIMULTECH 2015) TI - Tackling Non-linearity in Seismic Risk Estimation using Fuzzy Methods SN - 978-989-758-120-5 AU - González Cárdenas, J. AU - Nebot, À. AU - Mugica, F. AU - Crowley, H. PY - 2015 SP - 532 EP - 541 DO -