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21st International Congress for Photogrammetry and Remote Sensing, ISPRS 2008

作者： Teimouri, M. Delavar, M.R. Kolyaie, S. Chavoshi, S.H. Kiavarz Moghaddam, H. GIS Division Dept. of Surveying and Geomatics Eng. College of Eng. University of Tehran Tehran Iran Center of Excellence in Geomatics Eng. and Disaster Management Dept. of Surveying and Geomatics Eng. College of Engineering University of Tehran Tehran Iran GIS Division Dept. of Surveying and Geomatics Eng. College of Eng. University of Tehran Tehran and GIS Expert Tehran GIS Center Iran

Lack of reliable, up to date, available and qualified geospatial data is one of the problems we are faced to have a proper response to natural disasters. On the other hand, complexity of earthquake phenomena from time, position and intensity, makes it a very uncertain phenomenon to assess. Furthermore, there is no comprehensive spatial analysis tool to support decision making under such disasters. Therefore, development of spatial decision support system (SDSS) to support processing and analyzing geo-spatial data for disaster management and damage estimation is of extreme importance. Previous research shows that about 70 % of Iranian urban areas are suspect to earthquake, therefore, Iran is located in an extremely earthquake risk prone areas in the *** paper outlines a methodology to assess damage estimation due to an earthquake using SDSS. The methodology is based on quantifying number of buildings destroyed due to an earthquake using high resolution remotely sensed images and other spatial data to be integrated in a *** inventory of buildings in Bam city before the earthquake happened in Dec. 2003 was prepared. The number of destroyed buildings, due to the earthquake was evaluated. An object-based classification and segmentation methods have been used for damage estimation. Out of 18872 buildings in Bam city, 6473 buildings (34 %) were collapsed due to the earthquake. Preliminary assessments indicate an overall accuracy for the classification to be about 80.5%.The results of this paper can assist decision makers to allocate rescue forces to the damaged areas based on their degree of destruction. © 2008 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Earthquakes

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Support and confidence parameters to induct decision rules to classify Tehran's seismic vulnerability 6

Support and confidence parameters to induct decision rules t...

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6th International Symposium on Geo-Information for disaster management, Gi4DM 2010

作者： Samadi Alinia, H. Delavar, M.R. Yao, Y.Y. Dept. of Surveying and Geomatics Eng. College of Eng. University of Tehran Tehran Iran Center of Excellence in Geomatics Eng. and Disaster Management Dept. of Surveying and Geomatics Eng. College of Eng. University of Tehran Tehran Iran Department of Computer Science University of Regina Canada

Rule induction is an area of machine learning in which formal rules are extracted from a set of observations or decision trees. Inducted rules can be expressed as relationships between concepts in terms of their intensions and extensions, such as sub-concepts and super-concepts, disjoint and overlap concepts, and partial sub-concepts. Existing algorithms for construction of decision trees cannot effectively deal with missing values. To overcome the limitation, this paper presents granule network as an improved decision trees to induct more informative classification rules in which all objects in the universe are classified correctly with minimum uncertainty. To achieve this, some quantitative measures such as coverage and support are used to estimate the quality of the granules and their relations at each step. This paper is concentrated on seismic vulnerability classification using granule tree by applying quantity measures. It is implicated on 177 urban areas of north of Tehran, capital of Iran and the results are used to classify Tehran's seismic vulnerability. The achieved results of the classification are successfully verified the proposed methodology. © 2010 Copernicus GmbH. All rights reserved.

关键词： Decision trees

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A systematic review and bibliometric analysis of the impacts of COVID-19 on economy and mobility from the geospatial data perspective

Results in Engineering

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Results in engineering 2025年 26卷

作者： Yudha, Alfan Kurnia Leelawat, Natt Tang, Jing Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Phayathai Road Bangkok Pathumwan10330 Thailand Center of Excellence in Disaster and Risk Management Information Systems Chulalongkorn University Phayathai Road Pathumwan Bangkok10330 Thailand of System Design and Management Keio University Collaboration Complex 4-1-1 Hiyoshi Kohoku-ku Yokohama223-8526 Japan International School of Engineering Faculty of Engineering Chulalongkorn University Phayathai Road Pathumwan Bangkok10330 Thailand

The COVID-19 pandemic has greatly impacted the global economy, human health, and daily life. The World Health Organization declared it a pandemic on March 11, 2020. By May 2023, it had caused over seven million deaths. Until now, its economic and social effects are still felt. This systematic review and bibliometric analysis focuses on how COVID-19 has affected the economy and mobility using geospatial data. Geospatial data from sensors, social media, mobile apps, cars, and remote sensing give us near-real-time insights into people's behaviors and perceptions during the pandemic. The study examines how COVID-19 spread over time and space to help understand and reduce its impact. Even with challenges in combining different datasets, spatial analysis shows patterns of how humans and the pandemic interact. The finding answers key questions: How did COVID-19 affect economic activities and mobility? What common patterns do geospatial data show during the pandemic? By identifying common geospatial datasets and analyzing research trends, the study provides insights for policymakers and researchers to better prepare for future pandemics. This review helps understand the complex systems of pandemics and their effects on society using geospatial big data. Notably, the findings show that nighttime light intensity and mobile phone mobility data were the most consistently used indicators to monitor pandemic-driven disruptions and recovery, captured shifts in behavior and compliance with public health measures, offering a critical data source for real-time health surveillance, enabling health experts to better understand population responses, and adaptive policy interventions. © 2025

关键词： Economic and social effects

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Analysis of dynamic response of axially loaded pile using nodal exact finite element model 14

Analysis of dynamic response of axially loaded pile using no...

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14th International Conference on Concrete engineering and Technology, CONCET 2018

作者： Buachart, C. Hansapinyo, C. Center of Excellence for Natural Disaster Management Faculty of Engineering Department of Civil Engineering Chiang Mai University Thailand Excellent Center in Infrastructure Technology and Transportation Engineering Department of Civil Engineering Chiang Mai University Thailand

This research work presents the adoption of proposed displacement based finite element model so-called nodal exact finite element to solve dynamic response of axially loaded pile. The pile is assumed to be circular cross section embedded in elastic soil. The shape functions satisfy homogeneous differential equation of uniform elasto-dynamic bar was constructed. The stiffness and mass matrices for axially loaded pile are then formulated using energy principle, incorporate with proposed shape function. The dynamic response parameters, such as dynamic pile-head stiffness and damping of pile's axial vibration were computed from proposed finite element model by iterative procedure. Illustrative examples show fairly accurate results and demonstrate an effectiveness of proposed finite element compared with available analytical solutions from literatures. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Dynamic response

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The impact of the set awards on return on equity of listed companies in the stock exchange of Thailand 11

The impact of the set awards on return on equity of listed c...

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11th International Conference on Information management and engineering, ICIME 2019

作者： Paphawasit, Boontarika Surapee, Promlerk Suwan, Teewara College of Arts Media and Technology Chiang Mai University Thailand Center of Excellence in Natural Disaster Management Faculty of Engineering Chiang Mai University Thailand

ISBN: (纸本)9781450372343

This study aims to investigate the impact of the SET awards on Return on Equity (ROE) of 107 listed companies in the Stock Exchange of Thailand from 2009 to 2017. The study applies quantile regression analysis to estimate the relationship between ROE ratio and five influencing factors, which are the Best Company Performance Award, the Best CEO Award, the Best Investor Relations Award, the Best Corporate Social Responsibility Award, and the Best Innovative Company Award. The findings indicate that the Best Company Performance Award has a positive relationship with the Return on Equity. However, the effect of the Best CEO Award, the Investor Relations Award, the Best Corporate Social Responsibility Award, and the Best Innovative Company on the Return on Equity does not exist. © 2019 Association for Computing Machinery. ACM ISBN 978-1-4503-7234-3/19/09…$15.00

关键词： Regression analysis

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Travel itinerary planning in public transportation network using activity-based modeling

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Journal of Applied Sciences 2009年第14期9卷 2532-2543页

作者： Kolyaie, S. Delavar, M.R. Malek, M.R. GIS Division Department of Surveying and Geomatics Engineering College of Engineering University of Tehran Tehran Iran Center of Excellence in Geomatics Engineering and Disaster Management Department of Surveying and Geomatics Engineering College of Engineering University of Tehran Tehran Iran Department of GIS Faculty of Geodesy and Geomatics Engineering KN Toosi University of Technology Tehran Iran

This study presents a new geospatial information system-based solution that assists people in trip planning to reach multiple destinations considering opening hours of points of interest and duration needed to perform multiple activities using multimodel public transportation media. People encounter with complexities in finding optimum paths in a multimodel public transportation system as they need to consider interactions of different modes of transportations in a more specific and constrained spatio-temporal structure. In this situation people's context in the form of their activities diary becomes an important issue affecting trip planning and selecting mode of transportation. Activities diary constrains the spatio-temporal order of activities and enables us to study the effect of activities in transportation planning. In this study, the impact of activity diaries and spatio-temporal dimensions of activities in trip planning and optimum path findings are discussed. A new algorithm is proposed for planning itinerary considering network, time and duration constraints. The algorithm assumes that the activities are mandatory and the locations and duration of each activity are fixed. The travelers' destinations, time and duration constraints provide the input of the algorithm. Using connectivity rules and policies, Dijkstra algorithm for finding the shortest paths is selected. The results determine the possible order of activities and their start and end time. The possible sequences of activities optimized based on minimizing waiting time during the activities i.e., time that person neither is doing an activity nor is traveling between activity locations and must wait till activity can be undertaken according to the time constraints. Finally, efficiency of the algorithm is determined according to the time complexity as a function of number of activity locations in the worst and normal cases. It has been proved that the time complexity of the algorithm depends on the t

关键词： Geographic information systems

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Residual strength index prediction of circular concrete-filled steel tubular columns through advanced machine learning methods

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Asian Journal of Civil engineering 2024年第1期25卷 747-760页

作者： Narang, Aishwarya Kumar, Ravi Dhiman, Amit Center of Excellence in Disaster Mitigation & Management IIT Roorkee Roorkee 247667 India Mechanical & Industrial Engineering Department IIT Roorkee Roorkee 247667 India Chemical Engineering Department IIT Roorkee Roorkee 247667 India

Concrete-filled steel tube (CFST), which has a long-standing relationship for their exceptional mechanical performance and cost-effectiveness, is frequently utilized as the primary load-bearing element in various constructions. In CFSTs, there are challenging constraints between steel tubular and core concrete, and there is a highly nonlinear relationship between geometric and material parameters and high-temperature behavior. Therefore, a thorough understanding of the fire performance of these columns is required. Fifty-six experimental tests from the literature are collected for circular CFST columns into a database and statistically assessed for their residual strength index (RSI). The database was then divided into a test set and a training set, which were used to train and improve the machine learning models. In this study, models to forecast the RSI of circular CFST columns are developed using four machine learning (ML) techniques with feature ranking analysis, namely: Gaussian progress regression (GPR), ensemble, support vector machines (SVM), and artificial neural network (ANN). Quadratic SVM and bi-layered ANN models outperformed the other ML models with R ² values of 0.93 and 0.98, respectively. The relevant experimental test results corroborated the parametric study's findings that the trained ML models could typically represent the influence of each key input attribute. As a result, ML is an adequate substitute for empirical and theoretical formulations. The use of ML models will reduce the research expense, and practicing engineers will find it especially helpful to evaluate the performance of these columns at higher temperatures. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Artificial neural network CFST Fire performance Gaussian progress regression Residual strength index

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Urban growth modeling using fuzzy logic

Urban growth modeling using fuzzy logic

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American Society for Photogrammetry and Remote Sensing Annual Conference 2012, ASPRS 2012

作者： Foroutan, Ehsan Delavar, Mahmoud Reza GIS Division Dept. of Surveying and Geomatics Eng. College of Eng. University of Tehran North Kargar St 11155-4563 Tehran Iran Center of Excellence in Geomatics Eng. and Disaster Management Dept. of Surveying and Geomatics Eng. College of Eng. University of Tehran North Kargar St 11155-4563 Tehran Iran

ISBN: (纸本)9781622764068

This study presents a GIS-based fuzzy logic approach to model urban growth in Isfahan metropolitan area in the center of Iran. Urban growth models can be used to simulate and predict urbanization process and demonstrate the complex spatial and temporal interaction of the growth variables. Fuzzy logic preserves the continuity of urban dynamics spatially by selecting fuzzy membership functions, fuzzy rules, and the fuzzification-defuzzification process. Vagueness in some descriptive or uncertain knowledge of the process can be better represented with fuzzy logic rules, since it utilizes the descriptive power of fuzzy logic as a powerful intelligence technique to map the effects of various parameters to the urban growth phenomenon and expresses it in sensible terms. Historical land use/cover data of Isfahan metropolitan area were extracted from the 1990 and 2001 Landsat ETM+ images and employed in order to simulate urban growth. In this study the effect of urban growth preferences is determined by the expert and restated in a rule-based form which is applied into the model. A map of urban growth suitability is produced and used to select the best threshold value that coincide the simulated map into the real land use map. Three quantified parameters have been employed to validate the proposed model including: Area under the relative operating characteristic (ROC), overall map accuracy (OMA) and kappa statistic. ROC value of 0.80 indicates that the suitability map is valid. Also the overall map accuracy (OMA) and Kappa Statistic (KS) values are 0.78 and 0.55 respectively, prove the validity of the model.

关键词： Urban growth

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INTEGRATION of GENETIC ALGORITHMS and FUZZY LOGIC for URBAN GROWTH MODELING 22

INTEGRATION of GENETIC ALGORITHMS and FUZZY LOGIC for URBAN ...

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22nd Congress of the International Society for Photogrammetry and Remote Sensing, ISPRS 2012

作者： Foroutan, E. Delavar, M.R. Araabi, B.N. GIS Division Dept. of Surveying and Geomatics Eng. College of Eng. University of Tehran Tehran Iran Center of Excellence in Geomatics Eng. in Disaster Management Dept. of Surveying and Geomatics Eng. College of Eng. University of Tehran Tehran Iran School of Electrical and Computer Eng. College of Eng. University of Tehran Tehran Iran

Urban growth phenomenon as a spatio-temporal continuous process is subject to spatial uncertainty. This inherent uncertainty cannot be fully addressed by the conventional methods based on the Boolean algebra. Fuzzy logic can be employed to overcome this limitation. Fuzzy logic preserves the continuity of dynamic urban growth spatially by choosing fuzzy membership functions, fuzzy rules and the fuzzification-defuzzification process. Fuzzy membership functions and fuzzy rule sets as the heart of fuzzy logic are rather subjective and dependent on the expert. However, due to lack of a definite method for determining the membership function parameters, certain optimization is needed to tune the parameters and improve the performance of the model. This paper integrates genetic algorithms and fuzzy logic as a genetic fuzzy system (GFS) for modeling dynamic urban growth. The proposed approach is applied for modeling urban growth in Tehran Metropolitan Area in Iran. Historical land use/cover data of Tehran Metropolitan Area extracted from the 1988 and 1999 Landsat ETM+ images are employed in order to simulate the urban growth. The extracted land use classes of the year 1988 include urban areas, street, vegetation areas, slope and elevation used as urban growth physical driving forces. Relative Operating Characteristic (ROC) curve as an fitness function has been used to evaluate the performance of the GFS algorithm. The optimum membership function parameter is applied for generating a suitability map for the urban growth. Comparing the suitability map and real land use map of 1999 gives the threshold value for the best suitability map which can simulate the land use map of 1999. The simulation outcomes in terms of kappa of 89.13% and overall map accuracy of 95.58% demonstrated the efficiency and reliability of the proposed model.

关键词： Genetic Fuzzy System Suitability mapping Urban driving forces Urban Growth modeling Validation

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Pedestrian level wind characteristics around tall buildings: Effect of building shape and wind direction 9

Pedestrian level wind characteristics around tall buildings:...

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9th Asia Pacific Conference on Wind engineering, APCWE 2017

作者： Mittal, Hemant Sharma, Ashutosh Gairola, Ajay Center of Excellence in Disaster Mitigation and Management Indian Institute of Technology Roorkee Uttarakhanad247667 India Department of Civil Engineering Indian Institute of Technology Roorkee Uttarakhanad247667 India

Wind flow pattern in urban area strongly affects the comfort level of pedestrians, natural ventilation and pollutant dispersion. Wind flow pattern is influenced by many parameters, such terrain condition of building location, architecture of buildings, wind direction and arrangements of neighbouring buildings. In this study effect of building shape (square, tapered and setback) and wind direction on pedestrian level wind has been investigated. © 9th Asia Pacific Conference on Wind engineering, APCWE 2017. All Rights Reserved.

关键词： Tall buildings

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