This paper summarizes the fuel type systems currently adopted by the fire danger rating systems or fire behavior prediction systems of some countries, such as Canada, the United States, Australia, Greece, and Switzerl...This paper summarizes the fuel type systems currently adopted by the fire danger rating systems or fire behavior prediction systems of some countries, such as Canada, the United States, Australia, Greece, and Switzerland. As an example, the Canadian Forest Fire Danger Rating System organizes fuel types into five major groups, with a total of 16 discrete fuel types recognized. In the United States National Fire Danger Rating System, fuel models are divided into four vegetation groups and twenty fire behavior fuel models. The Promethus System （Greece） divides fuels into 7 types, and Australia has adopted only three distinct fuel types： open grasslands, dry eucalyptus forests, and heath/shrublands. Four approaches to mapping fuels are acceptable： field reconnaissance, direct mapping methods, indirect mapping methods, and gradient modeling. Satellite remote-sensing techniques provide an alternative source of obtaining fuel data quickly, since they provide comprehensive spatial coverage and enough temporal resolution to update fuel maps in a more efficient and timely manner than traditional aerial photography or fieldwork. Satellite sensors can also provide digital information that can be easily tied into other spatial databases using Geographic Information System （GIS） analysis, which can be used as input in fire behavior and growth models. Various fuel-mapping methods from satellite remote sensing are discussed in the paper. According to the analysis of the fuel mapping techniques worldwide, this paper suggests that China should first create appropriate fuel types for its fire agencies before embarking on developing a national fire danger rating system to improve the current data situation for it＇s fire management programs.展开更多
针对基本灰狼算法存在初始种群不均匀、早熟收敛等问题,基于混沌理论从三个方面对灰狼优化(grey wolf optimization,GWO)算法进行改进,提出了混沌灰狼优化(chaotic grey wolf optimization,CGWO)算法用于确定边坡的最小安全系数.首先,...针对基本灰狼算法存在初始种群不均匀、早熟收敛等问题,基于混沌理论从三个方面对灰狼优化(grey wolf optimization,GWO)算法进行改进,提出了混沌灰狼优化(chaotic grey wolf optimization,CGWO)算法用于确定边坡的最小安全系数.首先,采用改进Tent混沌映射提高初始种群多样性;其次,通过混沌扰动策略避免算法陷入局部最优;最后,引入参数混沌非线性调节机制均衡算法的全局开发和局部勘探算力.13个基准测试函数的仿真结果表明,改进后的算法与基本GWO,WOA,PSO以及SCA相比具有更强的综合寻优性能.选取ACADS边坡考核题进行计算分析,CGWO算法表现出较高的计算精度和收敛速度,能够有效地搜索到复杂分层边坡的最小安全系数.对比有限元强度折减法,该方法具有操作简易、搜索区域易于设置等优点.展开更多
基金This paper was supported by the Beijing Fund of Nature Science (No. 6042025), China NKBRSF Project (No. 2001CB409600) and Laboratory of Forest Protection, State Forestry Administration
文摘This paper summarizes the fuel type systems currently adopted by the fire danger rating systems or fire behavior prediction systems of some countries, such as Canada, the United States, Australia, Greece, and Switzerland. As an example, the Canadian Forest Fire Danger Rating System organizes fuel types into five major groups, with a total of 16 discrete fuel types recognized. In the United States National Fire Danger Rating System, fuel models are divided into four vegetation groups and twenty fire behavior fuel models. The Promethus System （Greece） divides fuels into 7 types, and Australia has adopted only three distinct fuel types： open grasslands, dry eucalyptus forests, and heath/shrublands. Four approaches to mapping fuels are acceptable： field reconnaissance, direct mapping methods, indirect mapping methods, and gradient modeling. Satellite remote-sensing techniques provide an alternative source of obtaining fuel data quickly, since they provide comprehensive spatial coverage and enough temporal resolution to update fuel maps in a more efficient and timely manner than traditional aerial photography or fieldwork. Satellite sensors can also provide digital information that can be easily tied into other spatial databases using Geographic Information System （GIS） analysis, which can be used as input in fire behavior and growth models. Various fuel-mapping methods from satellite remote sensing are discussed in the paper. According to the analysis of the fuel mapping techniques worldwide, this paper suggests that China should first create appropriate fuel types for its fire agencies before embarking on developing a national fire danger rating system to improve the current data situation for it＇s fire management programs.
文摘针对基本灰狼算法存在初始种群不均匀、早熟收敛等问题,基于混沌理论从三个方面对灰狼优化(grey wolf optimization,GWO)算法进行改进,提出了混沌灰狼优化(chaotic grey wolf optimization,CGWO)算法用于确定边坡的最小安全系数.首先,采用改进Tent混沌映射提高初始种群多样性;其次,通过混沌扰动策略避免算法陷入局部最优;最后,引入参数混沌非线性调节机制均衡算法的全局开发和局部勘探算力.13个基准测试函数的仿真结果表明,改进后的算法与基本GWO,WOA,PSO以及SCA相比具有更强的综合寻优性能.选取ACADS边坡考核题进行计算分析,CGWO算法表现出较高的计算精度和收敛速度,能够有效地搜索到复杂分层边坡的最小安全系数.对比有限元强度折减法,该方法具有操作简易、搜索区域易于设置等优点.
