针对标准PSO中单一社会学习模式造成的算法容易陷入局部最优和后期收敛速度慢等问题,提出了一种基于多种群的自适应迁移PSO算法(Multi-population based self-adaptive migration PSO,MSMPSO).通过融合两种常用的邻居拓扑结构,赋予个体...针对标准PSO中单一社会学习模式造成的算法容易陷入局部最优和后期收敛速度慢等问题,提出了一种基于多种群的自适应迁移PSO算法(Multi-population based self-adaptive migration PSO,MSMPSO).通过融合两种常用的邻居拓扑结构,赋予个体更多的信息来源;在多个子种群并行进化的基础上,利用不同加速因子的组合赋予各子种群不同的搜索特性,进而通过周期性对子种群的历史性能进行评估,以此为基础指导个体的迁移操作,实现子种群间的协作与计算资源的合理分配,并最终提升算法的综合性能.对CEC2013测试函数的优化结果表明,MSMPSO在求解精度、收敛速度等方面均表现出较好的性能.展开更多
评估地球系统模式对气候和植被的模拟能力是利用地球系统模式研究植被对气候变化响应的基础。基于观测和遥感数据,本文评估了第六次国际耦合模式比较计划(CMIP6)中18个全球耦合模式对中国生长季温度、降水和叶面积指数(Leaf Area Index,...评估地球系统模式对气候和植被的模拟能力是利用地球系统模式研究植被对气候变化响应的基础。基于观测和遥感数据,本文评估了第六次国际耦合模式比较计划(CMIP6)中18个全球耦合模式对中国生长季温度、降水和叶面积指数(Leaf Area Index,LAI)的模拟性能。我们基于多元线性回归模型定量了植被对温度、降水的敏感性,对CMIP6模式关于植被敏感性的模拟能力进行定量评估。研究结果表明:(1)大部分模式可较好地模拟生长季温度、降水和LAI的气候态空间分布特征,但普遍高估全国平均LAI,且各模式对气候和植被变化趋势的模拟结果存在较大偏差;(2)与观测数据相比,模式关于LAI对温度和降水的敏感性符号模拟能力均表现出对正值区的模拟优于对负值区的模拟,并且典型脆弱区植被敏感性大于中国区域植被敏感性,模式对植被敏感性幅度及其与气候场对应关系的模拟方面存在较大偏差;(3)基于模式在生长季的温度、降水、LAI及其敏感性方面的综合排名,四个模拟性能最佳的模式分别为CanESM5–CanOE、INM–CM5–0、IPSL–CM6–LR和MPI–ESM1–2–LR。展开更多
In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design （RBD） methodology, advo...In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design （RBD） methodology, advocating systematic integration of risk assessment within the conventional design process has started to takeoff. Despite this wide recognition and increasing popularity, important factors that could potentially undermine the quality of the results come from both quantitative and qualitative aspects during the risk assessment process. This paper details a promising solution by developing a formalized methodology for risk assessment through effective storing and processing of historical data combined with data generated through first-principle approaches. This method should help to generate appropriate risk models in the selected platform （Bayesian networks） which can be employed for decision making at design stare.展开更多
文摘针对标准PSO中单一社会学习模式造成的算法容易陷入局部最优和后期收敛速度慢等问题,提出了一种基于多种群的自适应迁移PSO算法(Multi-population based self-adaptive migration PSO,MSMPSO).通过融合两种常用的邻居拓扑结构,赋予个体更多的信息来源;在多个子种群并行进化的基础上,利用不同加速因子的组合赋予各子种群不同的搜索特性,进而通过周期性对子种群的历史性能进行评估,以此为基础指导个体的迁移操作,实现子种群间的协作与计算资源的合理分配,并最终提升算法的综合性能.对CEC2013测试函数的优化结果表明,MSMPSO在求解精度、收敛速度等方面均表现出较好的性能.
文摘评估地球系统模式对气候和植被的模拟能力是利用地球系统模式研究植被对气候变化响应的基础。基于观测和遥感数据,本文评估了第六次国际耦合模式比较计划(CMIP6)中18个全球耦合模式对中国生长季温度、降水和叶面积指数(Leaf Area Index,LAI)的模拟性能。我们基于多元线性回归模型定量了植被对温度、降水的敏感性,对CMIP6模式关于植被敏感性的模拟能力进行定量评估。研究结果表明:(1)大部分模式可较好地模拟生长季温度、降水和LAI的气候态空间分布特征,但普遍高估全国平均LAI,且各模式对气候和植被变化趋势的模拟结果存在较大偏差;(2)与观测数据相比,模式关于LAI对温度和降水的敏感性符号模拟能力均表现出对正值区的模拟优于对负值区的模拟,并且典型脆弱区植被敏感性大于中国区域植被敏感性,模式对植被敏感性幅度及其与气候场对应关系的模拟方面存在较大偏差;(3)基于模式在生长季的温度、降水、LAI及其敏感性方面的综合排名,四个模拟性能最佳的模式分别为CanESM5–CanOE、INM–CM5–0、IPSL–CM6–LR和MPI–ESM1–2–LR。
基金the financial support received by the University of Strathclyde in the form of a postgraduate research scholarship for the duration of the second author’s P hD studies
文摘In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design （RBD） methodology, advocating systematic integration of risk assessment within the conventional design process has started to takeoff. Despite this wide recognition and increasing popularity, important factors that could potentially undermine the quality of the results come from both quantitative and qualitative aspects during the risk assessment process. This paper details a promising solution by developing a formalized methodology for risk assessment through effective storing and processing of historical data combined with data generated through first-principle approaches. This method should help to generate appropriate risk models in the selected platform （Bayesian networks） which can be employed for decision making at design stare.
