Multicriteria Fuzzy Analysis for a GIS-Based Management of Earthquake Scenarios

被引:18
作者
D'Urso, Maria Grazia [1 ]
Masi, Daniele [2 ]
Zuccaro, Giulio [3 ]
De Gregorio, Daniela [3 ]
机构
[1] Univ Cassino & Southern Lazio, Dept Civil & Mech Engn, Cassino, Italy
[2] Univ Naples Federico II, Dept Struct Engn & Architecture, Naples, Italy
[3] Univ Naples Federico II, PLINIVS Study Ctr LUPT, Naples, Italy
关键词
REGRESSION-ANALYSIS; DECISION-ANALYSIS; NEURAL-NETWORK; MCS INTENSITY; VULNERABILITY; OPTIMIZATION; PREDICTION; SELECTION; HAZARDS; MODEL;
D O I
10.1111/mice.12335
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Objective of this article is the formulation and the implementation of a decision-making model for the optimal management of emergencies. It is based on the accurate definition of possible scenarios resulting from prediction and prevention strategies and explicitly takes into account the subjectivity of the judgments of preference. To this end, a multicriteria decision model, based on fuzzy logic, has been implemented in a user-friendly geographical information system (GIS) platform so as to allow for the automation of choice processes between several alternatives for the spatial location of the investigated scenarios. In particular, we have analyzed the potentialities of the proposed approach in terms of seismic risk reduction, simplifying the decision process leading to the actions to be taken from directors and managers of coordination services. Due to the large number of variables involved in the decision process, it has been proposed a particularly flexible and streamlined method in which the damage scenarios, based on the vulnerability of the territory, have represented the input data to derive a vector of weights to be assigned to different decision alternatives. As an application of the proposed approach, the seismic damage scenario of a region of 400 km(2), hit by the 2009 earthquake in L'Aquila (Italy), has been analyzed.
引用
收藏
页码:165 / 179
页数:15
相关论文
共 59 条
[1]   Fuzzy-wavelet RBFNN model for freeway incident detection [J].
Adeli, H ;
Karim, A .
JOURNAL OF TRANSPORTATION ENGINEERING, 2000, 126 (06) :464-471
[2]   A probabilistic neural network for earthquake magnitude prediction [J].
Adeli, Hojjat ;
Panakkat, Ashif .
NEURAL NETWORKS, 2009, 22 (07) :1018-1024
[3]   Damage pattern recognition for structural health monitoring using fuzzy similarity prescription [J].
Altunok, Erdogan ;
Taha, Mahmoud M. Reda ;
Epp, David S. ;
Mayes, Randy L. ;
Baca, Thomas J. .
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2006, 21 (08) :549-560
[4]  
[Anonymous], 2013, Multi-Criteria Decision Analysis
[5]  
[Anonymous], 2011, COMPUT AIDED CIV INF, DOI DOI 10.1111/J.1467-8667.2010.00673.X
[6]  
Anoop M. B., 2012, COMPUT-AIDED CIV INF, V27, P275
[7]   Solving Civil Engineering Problems by Means of Fuzzy and Stochastic MCDM Methods: Current State and Future Research [J].
Antucheviciene, Jurgita ;
Kala, Zdenek ;
Marzouk, Mohamed ;
Vaidogas, Egidijus Rytas .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
[8]  
Ayhan M. B., 2013, INT J MANAGING VALUE, V4, P11, DOI [10.5121/ijmvsc.2013.4302, DOI 10.5121/IJMVSC.2013.4302]
[9]   FUZZINESS IN GEOGRAPHICAL INFORMATION-SYSTEMS - CONTRIBUTIONS FROM THE ANALYTIC HIERARCHY PROCESS [J].
BANAI, R .
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SYSTEMS, 1993, 7 (04) :315-329
[10]   Prediction of Pavement Performance through Neuro-Fuzzy Reasoning [J].
Bianchini, Alessandra ;
Bandini, Paola .
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2010, 25 (01) :39-54