为了实现复杂战场环境下空中目标敌我属性的综合识别,在利用证据权重衡量信息可信度的基础上,提出了一种基于DS证据理论和直觉模糊集相结合(Dempster-Shafer evidence theory-intuitionistic fuzzy sets,DST-IFS)的综合敌我识别方法。首...为了实现复杂战场环境下空中目标敌我属性的综合识别,在利用证据权重衡量信息可信度的基础上,提出了一种基于DS证据理论和直觉模糊集相结合(Dempster-Shafer evidence theory-intuitionistic fuzzy sets,DST-IFS)的综合敌我识别方法。首先,分析了空中目标综合敌我识别问题,给出了具体的识别流程;然后,针对DS(DempsterShafer)函数向直觉模糊集转化过程中存在增大信息不确定性的问题,提出了一种信度分配方法用于直觉模糊隶属度和非隶属度赋值,并利用算例验证了信度分配方法的适应性和有效性;接着,给出了基于理想点法(technique for order preference by similarity to ideal solution,TOPSIS)的DST-IFS决策方法步骤;在此基础上,提出了一种基于DST-IFS的空中目标综合敌我识别的方法;最后进行了实例分析,验证了该综合敌我识别方法的有效性。展开更多
By considering distance error and direction error, Tropical Cyclone(TC) track forecasts with abnormal forecast error(AFE) at lead time of 48 h by ECMWF-IFS are selected out from 2010 to 2013. Factors closely related t...By considering distance error and direction error, Tropical Cyclone(TC) track forecasts with abnormal forecast error(AFE) at lead time of 48 h by ECMWF-IFS are selected out from 2010 to 2013. Factors closely related to AFE cases are investigated. There are 7 factors which are closely related to AFE cases. The most common one is Landfall or Passing through big island(LP) which appears 21 times among all 55 AFE cases. But LP often coexists with other factors to cause AFE cases. The second in the list is Coexistence with other TC or cloud cluster(CO) which affects more than one third of all AFE cases. Besides those 7 factors, fault of TCtracker also results in some AFE cases. There are no simple indicators for forecasters to anticipate a possible AFE case in advance. It seems that forecasters still have to anticipate AFE cases by their experiences and with synthetic analysis on all available data. Some possible ways to improve AFE cases are discussed and proposed to forecasters. That includes relying on products from ensemble prediction system or guidance from other models, simple translation process and manual analysis of TC track by forecasters under some circumstances.展开更多
目的:调查海南省3个主要荔枝品种的农药残留现状,评估其农药残留相关的食品安全风险,为荔枝质量安全监管提供数据支撑。方法:采集海南省妃子笑、紫娘喜、白糖罂3个品种共77份荔枝样品,采用气相色谱-串联质谱(Gas Chromatography-Tandem ...目的:调查海南省3个主要荔枝品种的农药残留现状,评估其农药残留相关的食品安全风险,为荔枝质量安全监管提供数据支撑。方法:采集海南省妃子笑、紫娘喜、白糖罂3个品种共77份荔枝样品,采用气相色谱-串联质谱(Gas Chromatography-Tandem Mass Spectrometry,GC-MS/MS)法对190种农药进行残留筛查,并采用食品安全指数(Index of Food Safety,IFS)法对检出的农药残留开展风险评估。结果:在筛查的77份荔枝样品中,共检出16种农药残留,其中3种拟除虫菊酯类农药存在超标,分别为氯氟氰菊酯和高效氯氟氰菊酯、氯氰菊酯和高效氯氰菊酯及溴氰菊酯。风险评估显示,16种农药的平均IFS值均小于0.03,且3种超标农药的IFS值与最大IFS值均远小于1,整体风险处于可控范围。结论:海南省3个主要荔枝品种的质量安全情况总体良好,但仍存在部分农药超标情况,需要相关部门进一步加强关注与管控,保障荔枝消费安全。展开更多
文摘为了实现复杂战场环境下空中目标敌我属性的综合识别,在利用证据权重衡量信息可信度的基础上,提出了一种基于DS证据理论和直觉模糊集相结合(Dempster-Shafer evidence theory-intuitionistic fuzzy sets,DST-IFS)的综合敌我识别方法。首先,分析了空中目标综合敌我识别问题,给出了具体的识别流程;然后,针对DS(DempsterShafer)函数向直觉模糊集转化过程中存在增大信息不确定性的问题,提出了一种信度分配方法用于直觉模糊隶属度和非隶属度赋值,并利用算例验证了信度分配方法的适应性和有效性;接着,给出了基于理想点法(technique for order preference by similarity to ideal solution,TOPSIS)的DST-IFS决策方法步骤;在此基础上,提出了一种基于DST-IFS的空中目标综合敌我识别的方法;最后进行了实例分析,验证了该综合敌我识别方法的有效性。
文摘By considering distance error and direction error, Tropical Cyclone(TC) track forecasts with abnormal forecast error(AFE) at lead time of 48 h by ECMWF-IFS are selected out from 2010 to 2013. Factors closely related to AFE cases are investigated. There are 7 factors which are closely related to AFE cases. The most common one is Landfall or Passing through big island(LP) which appears 21 times among all 55 AFE cases. But LP often coexists with other factors to cause AFE cases. The second in the list is Coexistence with other TC or cloud cluster(CO) which affects more than one third of all AFE cases. Besides those 7 factors, fault of TCtracker also results in some AFE cases. There are no simple indicators for forecasters to anticipate a possible AFE case in advance. It seems that forecasters still have to anticipate AFE cases by their experiences and with synthetic analysis on all available data. Some possible ways to improve AFE cases are discussed and proposed to forecasters. That includes relying on products from ensemble prediction system or guidance from other models, simple translation process and manual analysis of TC track by forecasters under some circumstances.
文摘目的:调查海南省3个主要荔枝品种的农药残留现状,评估其农药残留相关的食品安全风险,为荔枝质量安全监管提供数据支撑。方法:采集海南省妃子笑、紫娘喜、白糖罂3个品种共77份荔枝样品,采用气相色谱-串联质谱(Gas Chromatography-Tandem Mass Spectrometry,GC-MS/MS)法对190种农药进行残留筛查,并采用食品安全指数(Index of Food Safety,IFS)法对检出的农药残留开展风险评估。结果:在筛查的77份荔枝样品中,共检出16种农药残留,其中3种拟除虫菊酯类农药存在超标,分别为氯氟氰菊酯和高效氯氟氰菊酯、氯氰菊酯和高效氯氰菊酯及溴氰菊酯。风险评估显示,16种农药的平均IFS值均小于0.03,且3种超标农药的IFS值与最大IFS值均远小于1,整体风险处于可控范围。结论:海南省3个主要荔枝品种的质量安全情况总体良好,但仍存在部分农药超标情况,需要相关部门进一步加强关注与管控,保障荔枝消费安全。
