大面积航班延误的实时航班延误程度评估研究

为对大面积航班的延误程度进行实时评估,根据航班延误的时空分布特点,从延误时间和延误范围两个角度给出评估指标,建立了航班延误程度实时评估指标体系。采用层次分析法得到各个指标的权重,并在此基础上给出了基于模糊综合评价的航班延误程度实时评估模型。实例的计算结果表明建立的评估模型是可行的。     

基于模糊聚类分析的步枪作战效能评估

为了评估步枪的战术效能,科学地构建步枪作战效能评估体系,运用模糊聚类分析方法对步枪作战效能进行评估,最后通过算例验证了所建模型是合理、可行的。     

A nonlinear background removal method for seismo-ionospheric anomaly analysis under a complex solar activity scenario: A case study of the M9.0 Tohoku earthquake

A precise determination of ionospheric total electron content (TEC) anomaly variations that are likely associated with large earthquakes as observed by global positioning system (GPS) requires the elimination of the ionospheric effect from irregular solar electromagnetic radiation. In particular, revealing the seismo-ionospheric anomalies when earthquakes occurred during periods of high solar activity is of utmost importance. To overcome this constraint, a multiresolution time series processing technique based on wavelet transform applicable to global ionosphere map (GIM) TEC data was used to remove the nonlinear effect from solar radiation for the earthquake that struck Tohoku, Japan, on 11 March, 2011. As a result, it was found that the extracted TEC have a good correlation with the measured solar extreme ultraviolet flux in 26–34 nm (EUV_26–34) and the 10.7 cm solar radio flux (F_10.7). After removing the influence of solar radiation origin in GIM TEC, the analysis results show that the TEC around the forthcoming epicenter and its conjugate were significantly enhanced in the afternoon period of 8 March 2011, 3 days before the earthquake. The spatial distributions of the TEC anomalous and extreme enhancements indicate that the earthquake preparation process had brought with a TEC anomaly area of size approximately 1650 and 5700 km in the latitudinal and longitudinal directions, respectively.     

Optimized Fuzzy Clustering Method for Health Monitoring of Shield Tunnels

Since health monitoring of shield tunnels generally employs multiple sensors belonging to different types,a fine analysis on massive monitoring data,as well as further quantitative health grading,is really challenging.An optimized fuzzy clustering analysis method based on the fuzzy equivalence relation is proposed for health monitoring of shield tunnels.Clustering results are auto-generated by using fuzzy similarity-valued map.The results follow the idea of unsupervised classification.Moreover,a convenient new health index HI is proposed for a fast tunnel-health grading.A case study on Nanjing Yangtze River Tunnel is presented to validate this method.Three types of indicators,namely soil pressure,pore water pressure and steel strain,are used to develop the clustering model.The clustering results are verified by analyzing the engineering geological conditions;the validity and the efficacy of the proposed method are also demonstrated.Further,the fuzzy clustering analysis also represents a potential for identifying abnormal monitoring data.This investigation indicates the fuzzy clustering analysis method is capable of characterizing the fuzziness of tunnel health,and beneficial to clarify the tunnel health evaluation uncertainties.     

公共场所火灾公众责任险风险评估及核保模型研究

介绍了目前我国公共场所火灾的现状及火灾公众责任险强制性实施的必要性.通过建立公众场所火灾风险评价指标体系,运用多层次模糊综合评价理论对公众场所火灾危险性进行综合评估.最后依据评估结果对火灾公众责任险费率进行浮动,确定科学合理的费率水平和责任限额.     

多层模糊逻辑控制器的设计

本文提出一种适合于多输入多输出(MIMO)系统的多层模糊逻辑控制器(MLFLC)，该控制器由若干个多输入单输出(MISO)模糊控制器构成，每个MISO模糊控制器由许多单输入单输出(SISO)模糊控制器组成。该控制器采用互补型隶属函数，具有一组零控制面，只要使量化因子满足一定的条件，控制系统就是渐近稳定的。最后将上述控制器用于二节机械手中进行仿真试验，验证了上述算法的可行性和有效性。     

一种基于粗糙K-均值的椭球基函数神经网络

改进了一种椭球基函数神经网络,它与经典椭球单元神经网络的结构不同,而与径向基函数神经网络结构类似,即它有一个隐含层,并且隐层单元采用椭球基函数,区别于RBF网络的高斯函数。本文采用粗糙K-均值方法求取椭球函数的中心,并给出了该方法中确定初始阈值的步骤。这种改进方法不但使对输入空间的划分局部作用,而且划分区域封闭有界。因此,改进的神经网络具有较好的函数逼近能力和模式识别能力。仿真实验验证了该椭球基函数神经网络的正确性和有效性。     

成组技术中计算机辅助零件分类方法的探讨

成组技术是有效实现CAD/CAM的基础之一,是提高多品种、中小批量生产水平的重要手段。本文提出了在成组技术中应用模糊数学理论进行计算机辅助零件分类的新方法,并对回转零件进行了分类试验,取得了满意的结果。采用这种方法,不需要对零件进行编码,可以对零件相似性进行定量分析,使得零件分类更具有柔性,为成组技术中零件分类提供了新的方法。     

低轨卫星缺失时序数据的模式识别方法

在航天应用中，低轨卫星经常会由于原始数据缺失而影响卫星时序数据模式识别结果，降低准确率。针对该问题提出了一种新型MR-GRU模型，可有效处理缺失时序数据，并获得较好的模式识别准确率。区别于传统模型的补全缺失数据的方法，MR-GRU模型直接在缺失时序数据上运用循环神经网络进行训练，对传统门控循环单元结构进行了改进，增加了两个新变量：掩蔽项和衰减项。掩蔽项作用于输入，衰减项作用于输入和隐层单元输出。MR-GRU模型不仅能够保持时序数据固有的时间特性，还能有效提高模式识别精度。在卫星时序数据上的模式识别试验表明，MR-GRU模型准确率优于传统模型。     

商务英语模糊语语境顺应性研究

商务英语是国际商务活动的重要语言载体。模糊语在商务英语中有着不可替代的语用功能。以商务活动中的内部沟通语境和对外沟通语境为视角,对在这两种语境下商务英语模糊语的应用规律进行分析研究,应用顺应性理论对其进行解释,阐明在实际应用中应遵循这些规律,做到＂内外有别＂。对准确使用商务英语,提高商务沟通效率以及促进商务英语的教学等方面都有重要的意义。