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    Disaster relief on destructive transportation networks using a circle-based approach

    , Article Transportation Letters ; Volume 13, Issue 8 , 2021 , Pages 568-590 ; 19427867 (ISSN) Shiripour, S ; Mahdavi Amiri, N ; Sharif University of Technology
    Taylor and Francis Ltd  2021
    Abstract
    We formulate an integrated mathematical model for distribution of the injured on a three-type transportation network with destroyable independent links and with actual travel times considering two different groups of the injured. The aim is to find the temporary locations for aid stations and their capacities, the percentage of the injured with various severities allocated to each station and to different routes and the number of vehicles so that the total relief time is minimized. For this, we present a new approach, called circle-based approach, in which the effects of the disaster are considered as a number of concentric circular regions. The original problem is formulated as an integer... 

    Car type recognition in highways based on wavelet and contourlet feature extraction

    , Article Proceedings of the 2010 International Conference on Signal and Image Processing, ICSIP 2010, 15 December 2010 through 17 December 2010, Chennai ; 2010 , Pages 353-356 ; 9781424485949 (ISBN) Arzani, M. M ; Jamzad, M ; Sharif University of Technology
    2010
    Abstract
    Recently many works focus on the vehicle type recognition because it is important in security and authentication systems. Computational complexity and low recognition rate especially when the system has to recognize among a large number of vehicles, are two major problems in vehicle type recognition. In recent years wavelet and contourlet transform have been applied in the recognition tasks successfully. In this paper we proposed a method for recognizing vehicle type in different lighting conditions. We used wavelet and contourlet as tools for feature extraction. These features are powerful and robust to illumination and scale variation. We reduced the dimension of feature vector by resizing... 

    A hierarchical artificial neural network for transport energy demand forecast: Iran case study

    , Article Neural Network World ; Volume 20, Issue 6 , 2010 , Pages 761-772 ; 12100552 (ISSN) Kazemi, A ; Shakouri, H .G ; Menhaj, M. B ; Mehregan, M. R ; Neshat, N ; Asgharizadeh, E ; Taghizadeh, M. R ; Sharif University of Technology
    Abstract
    This paper presents a neuro-based approach for annual transport energy demand forecasting by several socio-economic indicators. In order to analyze the influence of economic and social indicators on the transport energy demand, gross domestic product (GDP), population and total number of vehicles are selected. This approach is structured as a hierarchical artificial neural networks (ANNs) model based on the supervised multi-layer perceptron (MLP), trained with the back-propagation (BP) algorithm. This hierarchical ANNs model is designed properly. The input variables are transport energy demand in the last year, GDP, population and total number of vehicles. The output variable is the energy... 

    Disaster relief on destructive transportation networks using a circle-based approach

    , Article Transportation Letters ; 2020 Shiripour, S ; Mahdavi Amiri, N ; Sharif University of Technology
    Taylor and Francis Ltd  2020
    Abstract
    We formulate an integrated mathematical model for distribution of the injured on a three-type transportation network with destroyable independent links and with actual travel times considering two different groups of the injured. The aim is to find the temporary locations for aid stations and their capacities, the percentage of the injured with various severities allocated to each station and to different routes and the number of vehicles so that the total relief time is minimized. For this, we present a new approach, called circle-based approach, in which the effects of the disaster are considered as a number of concentric circular regions. The original problem is formulated as an integer...