A Matkan; B Mirbagheri; K Akbari
Volume 9, Issue 3 , February 2018, , Pages 111-126
Abstract
Finding optimal Paths between two points on the Road network is one of the most spatial analysis in GIS. The high diversity of possible Paths between two points and difficult in apply all parameters simultaneously select the optimal Path (length of Path, easily track, traffic, road quality…) make finding ...
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Finding optimal Paths between two points on the Road network is one of the most spatial analysis in GIS. The high diversity of possible Paths between two points and difficult in apply all parameters simultaneously select the optimal Path (length of Path, easily track, traffic, road quality…) make finding optimal Paths problem to a difficult problem. Also, in some cases, two or more incompatible effective parameters such as length of the route and traffic adds to the complexity of the problem. Optimization algorithms, such as multi-objective genetic algorithm NSGA-II, that have ability simultaneous. Apply multiple incompatible parameters, can help GIS to solving these problems. Present a NSGA-II model on GIS based for finding optimal paths between origin and destination in the road network is the main Target of this paper. Also two GA innovative operator developed for enhance the ability of the model to find the optimal paths. Output of the model might be introduced optimal paths that they are shorter, quality of roads, transit of intersections and traffic. A hypothetical road network with the necessary restrictions, designed and utilizes for test the capabilities of the innovative model. Evaluation results show that the model is able to finding optimal Paths with multiple incompatible parameters.
, A.A Matkan; , A. Alimohammadi; , B Mirbagheri; , K Akbari; , M Tanasan
Volume 9, Issue 1 , October 2017, , Pages 17-36
Abstract
Commensurate with the complexity of human behavior, social systems are complicated. Population management in these systems are crucial and need to spend too much cost. Because of the interaction between humans and the environment and then the impact of these interactions on social systems in the process ...
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Commensurate with the complexity of human behavior, social systems are complicated. Population management in these systems are crucial and need to spend too much cost. Because of the interaction between humans and the environment and then the impact of these interactions on social systems in the process of population movements, there is a need to identify and study these interactions, especially in emergency situations.In this study, the results of agent based geosimulation of pedestrian movements and fire simulation at Hafte-Tir subway station were used to investigate the behavior of individuals and the environment during fire. Then, the discomfort indices, including environmental and human-environmental indicators, were calculated to examine the effect of the environment and agents on the movement process. This research has introduced two new discomfort indices i.e. environmental index AM1 and environmental-humanity index AM2 to evaluate the behavior of individuals and the environment during the fire. The innovation of these indices relates to the integration of the results of the agent based simulation and the fire simulation in the environment and after that using of visibility, in addition to the interactions of individuals with each other and their interactions with the physical components of the environment. Calculating results of indices and the results of people movement’s simulation in the station represented an inverse relationship between the level of discomfort and speed of crowd in the station. Also, the discomfort induces in the successful environmental scenario shows a reduction in the discomfort in hot spots rather than current situation scenario. The use of agent based geosimulations and the result of discomfort indices in different periods of crisis, can contribute population management strategies and emergency evacuation.
Ali Akbar Matkan; Babak Mansouri; Babak Mirbagheri; Fariba Karbalaei
Volume 7, Issue 3 , November 2015, , Pages 17-32
Abstract
Earthquake is one of the most destructive natural disasters which frequently occurs with different intensities. Earthquakes cause severe damage to buildings, main roads and most importantly, loss of life. Detection of damaged buildings caused by such an event at the right time is a critical issue for ...
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Earthquake is one of the most destructive natural disasters which frequently occurs with different intensities. Earthquakes cause severe damage to buildings, main roads and most importantly, loss of life. Detection of damaged buildings caused by such an event at the right time is a critical issue for crisis management and disaster relief. The aim of this study is to detect earthquake damaged buildings using very high resolution (VHR) satellite imagery. To achieve this result, the satellite images with very high resolution before and after the earthquake in Port-au-Prince in Haiti as well as the observed destruction map in 2010 were used. In this study, the optimum features extracted from the image were selected using correlation analysis. The buildings destroyed were classified using fuzzy inference system and the values of selected textures. Finally, the damage map obtained from the proposed algorithm was compared to the map of the area. The kappa criterion estimated from the results of the proposed method is 82% while the index- Jaccard parameter is 89.69%.
