Hybrid Genetic Algorithm-Based Approach for Estimating Flood Losses on Structures of Buildings

被引:4
|
作者
Hanak, Tomas [1 ]
Tuscher, Martin [1 ]
Pribyl, Oto [1 ]
机构
[1] Brno Univ Technol, Fac Civil Engn, Brno 60200, Czech Republic
关键词
flood; hybrid genetic algorithm; insurance; loss estimation; residential building; structure; DAMAGE ASSESSMENT; PROPERTY; MODEL; RIVER;
D O I
10.3390/su12073047
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Occurrence of extreme natural events raises the need for a quick and accurate estimation of losses on the insured residential property in order to support timely recovery of the area. Although various models are now available to estimate the amount of loss on buildings, there is a lack of models providing a sufficient level of detail and accuracy that can be used for insurance purposes. In this study, a hybrid genetic algorithm-based model for flood loss estimation on the structures of buildings is presented. The proposed model combines the ordinary least squares method, a genetic algorithm, and the bill of costs method, which offers a good balance of maximum simplicity on the one hand and the accuracy of calculation on the other hand. The model considers the geometric characteristics (dimensions and shape) of rooms and is enabled to work with various types of materials and structures, as well as a variable depth of flooding. The results achieved show that in quick loss estimation, the model provides highly accurate results which meet the requirements for its use for the purposes of settlement of real insurance claims by insurance companies. The article outlines the potential automated connection of the model to insurance companies' information system in order to create a simple building information model (BIM) of the insured property (building's structures).
引用
收藏
页数:16
相关论文
共 50 条
  • [41] Genetic algorithm-based clustering approach for k-anonymization
    Lin, Jun-Lin
    Wei, Meng-Cheng
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (06) : 9784 - 9792
  • [42] A Hybrid Genetic Algorithm-Based Random Forest Model for Intrusion Detection Approach in Internet of Medical Things
    Norouzi, Monire
    Gurkas-Aydin, Zeynep
    Turna, Ozgur Can
    Yagci, Mehmet Yavuz
    Aydin, Muhammed Ali
    Souri, Alireza
    APPLIED SCIENCES-BASEL, 2023, 13 (20):
  • [43] A hybrid genetic algorithm-based edge detection method for SAR image
    Wang, M
    Yuan, SY
    2005 IEEE International Radar, Conference Record, 2005, : 503 - 506
  • [44] Algorithm-based approach to headache
    Ravan, Jayaprakash R.
    Pattnaik, Jigyansa I.
    Samantray, Swayanka
    JOURNAL OF FAMILY MEDICINE AND PRIMARY CARE, 2023, 12 (09) : 1775 - 1783
  • [45] A genetic algorithm-based approach for automated refactoring of component-based software
    Kebir, Salim
    Borne, Isabelle
    Meslati, Djamel
    INFORMATION AND SOFTWARE TECHNOLOGY, 2017, 88 : 17 - 36
  • [46] GENETIC ALGORITHM-BASED MULTI-CRITERIA APPROACH TO PRODUCT MODULARIZATION
    Kumar, Binay
    Singh, Ritesh Kumar
    Kumar, Surendra
    INTERNATIONAL JOURNAL OF TECHNOLOGY, 2018, 9 (04) : 775 - 786
  • [47] A Genetic Algorithm-based Beamforming Approach for Delay-constrained Networks
    Guo, Hao
    Makki, Behrooz
    Svensson, Tommy
    2017 15TH INTERNATIONAL SYMPOSIUM ON MODELING AND OPTIMIZATION IN MOBILE, AD HOC, AND WIRELESS NETWORKS (WIOPT), 2017,
  • [48] An Image Processing and Genetic Algorithm-based Approach for the Detection of Melanoma in Patients
    Salem, Christian
    Azar, Danielle
    Tokajian, Sima
    METHODS OF INFORMATION IN MEDICINE, 2018, 57 (1-2) : 74 - 80
  • [49] Genetic algorithm-based approach to cell composition and layout design problems
    Univ of Colorado at Denver, Denver, United States
    Int J Prod Res, 2 (447-482):
  • [50] Genetic algorithm-based parameter selection approach to single image defogging
    Guo, Fan
    Peng, Hui
    Tang, Jin
    INFORMATION PROCESSING LETTERS, 2016, 116 (10) : 595 - 602