搜索条件

清除筛选
筛选: 创建者 Homchaudhuri, Baisravan 删除限定条件 创建者: Homchaudhuri, Baisravan 部门 Aerospace Engineering and Engineering Mechanics 删除限定条件 部门: Aerospace Engineering and Engineering Mechanics

搜索结果

  • Genetic Algorithm Based Simulation–optimization For Fighting Wildfires

    Article thumbnail: Genetic Algorithm Based Simulation–optimization For Fighting Wildfires
    Type:
    Article
    摘抄:
    Wildfire is one of the most significant disturbances responsible for reshaping the terrain and changing the ecosystem of a particular region. Its detrimental effects on environment as well as human lives and properties, and growing trend in terms of frequency and intensity of wildfires over the last decade have necessitated the development of efficient forest fire management techniques. During the last three decades, Forest Fire Decision Support Systems (FFDSS) have been developed to help in the decision-making processes during forest fires by providing necessary information on fire detection, their status and behavior, and other aspects of forest fires. However, most of these decision support systems lack the capability of developing intelligent fire suppression strategies based upon current status and predicted behavior of forest fire. This paper presents an approach for development of efficient fireline building strategies via intelligent resource allocation. A Genetic Algorithm based approach has been proposed in this paper for resource allocation and optimum fireline building that minimizes the total damage due to wildland fires. The approach is based on a simulation–optimization technique in which the Genetic Algorithm uses advanced forest fire propagation models based upon Huygens principles for evaluation of cost index of its solutions. Both homogeneous and heterogeneous environmental conditions have been considered. Uncertainties in weather conditions as well as imperfect knowledge about exact vegetation and topographical conditions make exact prediction of wildfires very difficult. The paper incorporates Monte-Carlo simulations to develop robust strategies in uncertain conditions. Extensive simulations demonstrate the effectiveness of the proposed approach in efficient resource allocation for fighting complex wildfires in uncertain and dynamic conditions.
    作者:
    Cohen, Kelly; Homchaudhuri, Baisravan, and Kumar, Manish
    提交者:
    Kelly Cohen
    上传日期:
    02/13/2017
    更改日期:
    04/05/2017
    创建:
    2013-04
    证书:
    All rights reserved