An intelligent simulation system for earthquake disaster assessment

Tang, Aiping; Wen, Aihua

doi:10.1016/j.cageo.2008.03.003

Cited by 55 publications

(19 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…China is prone to earthquakes [52] and it has the most severe seismic disasters in the world since it is located between the two large seismic zones, the Circum-Pacific and the HimalayaMediterranean seismic zones [53]. The frequency of occurrence of severe earthquakes is about 1/3 and the loss of lives is about 1/2 of the whole world [53].…”

Section: Historical Earthquake Data For Yunnan Province Chinamentioning

confidence: 99%

See 1 more Smart Citation

Seismic Hazard Analysis Based on Fuzzy-Probabilistic Approach

Andrić¹,

Lü²

2017

Proceedings of the 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

View full text Add to dashboard Cite

show abstract

Section: Historical Earthquake Data For Yunnan Province Chinamentioning

confidence: 99%

“…The frequency of occurrence of severe earthquakes is about 1/3 and the loss of lives is about 1/2 of the whole world [53].…”

Section: Historical Earthquake Data For Yunnan Province Chinamentioning

confidence: 99%

Seismic Hazard Analysis Based on Fuzzy-Probabilistic Approach

Andrić¹,

Lü²

2017

Proceedings of the 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

View full text Add to dashboard Cite

show abstract

“…There are some studies that use existing analytical relations or vulnerability indices in a Spatial Decision Support System (SDSS) framework (e.g., [7][8][9][10][11][12][13][14]). These approaches are applicable solely when there are predefined relations or indices elucidated particularly for the studied area, though there are many highly vulnerable urban areas all around the world that lack the required well developed building inventory and/or damage statistics from the previous earthquakes required for developing such relations/indices.…”

Section: Introductionmentioning

confidence: 99%

A GIS-Based Fuzzy Decision Making Model for Seismic Vulnerability Assessment in Areas with Incomplete Data

Sadrykia

Delavar

Zaré

2017

IJGI

View full text Add to dashboard Cite

Earthquakes are one of the natural disasters that threaten many lives every year. It is important to estimate seismic damages in advance to be able to reduce future losses. However, seismic vulnerability assessment is a complicated problem, especially in areas with incomplete data, due to incorporated uncertainties. Therefore, it is important to use adequate methods that take into account and handle the associated uncertainties. Although different seismic vulnerability assessment methods at the urban scale have been proposed, the purpose of this research is to introduce a new Geospatial Information System GIS-based model using a modified integration of Analytical Hierarchy Process (AHP), fuzzy sets theory, and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) in a vector-based environment. The proposed method emphasizes handling one of the important uncertainties in areas with incomplete data, namely the 'vagueness' of the existing knowledge about influences of the criteria on seismic vulnerability, which is handled using fuzzy sets theory in this research. The applicability of the proposed method is tested in a municipality district of Tabriz, which is in a near vicinity to the fault system. It can be concluded that the proposed method contributes to a pragmatic and efficient assessment of physical seismic vulnerability under uncertainty, which provides useful information for assisting planners in mitigation and preparation stages in less-studied areas.

show abstract

“…But there are few researches on risk analysis and early warning which consider multiple meteorological factors as a whole. GIS is a widely used tool with powerful data storage, management and sharing ability and rich spatial analysis ability, which can effectively integrate multi-source sensor data, provide spatial data support for all kinds of disaster management and decision support analysis and thus significantly improve the work efficiency and management level (Qi and Altinakar, 2011;Tang and Wen, 2009;Zerger and Smith, 2003). However, current GIS applications in power line management mainly satisfy the need for basic functions in the power line industry, such as power line layout, minimum cost path analysis, evaluation of environmental impact factors, power line measurement and calculation, three dimensional display and analysis, thematic map and statistics output (Bagli et al, 2011;Yang et al, 2010).…”

Section: Related Workmentioning

confidence: 99%

A Meteorological Risk Assessment Method for Power Lines Based on Gis and Multi-Sensor Integration

Zhang

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:Power lines, exposed in the natural environment, are vulnerable to various kinds of meteorological factors. Traditional research mainly deals with the influence of a single meteorological condition on the power line, which lacks of comprehensive effects evaluation and analysis of the multiple meteorological factors. In this paper, we use multiple meteorological monitoring data obtained by multi-sensors to implement the meteorological risk assessment and early warning of power lines. Firstly, we generate meteorological raster map from discrete meteorological monitoring data using spatial interpolation. Secondly, the expert scoring based analytic hierarchy process is used to compute the power line risk index of all kinds of meteorological conditions and establish the mathematical model of meteorological risk. By adopting this model in raster calculator of ArcGIS, we will have a raster map showing overall meteorological risks for power line. Finally, by overlaying the power line buffer layer to that raster map, we will get to know the exact risk index around a certain part of power line, which will provide significant guidance for power line risk management. In the experiment, based on five kinds of observation data gathered from meteorological stations in Guizhou Province of China, including wind, lightning, rain, ice, temperature, we carry on the meteorological risk analysis for the real power lines, and experimental results have proved the feasibility and validity of our proposed method.

show abstract

An intelligent simulation system for earthquake disaster assessment

Cited by 55 publications

References 1 publication

Seismic Hazard Analysis Based on Fuzzy-Probabilistic Approach

Seismic Hazard Analysis Based on Fuzzy-Probabilistic Approach

A GIS-Based Fuzzy Decision Making Model for Seismic Vulnerability Assessment in Areas with Incomplete Data

A Meteorological Risk Assessment Method for Power Lines Based on Gis and Multi-Sensor Integration

Contact Info

Product

Resources

About