二元语义判断矩阵的性质及其在航线优选中的应用

研究二元语义语言判断矩阵的性质及相关问题。利用二元语义的定义,讨论二元语义判断矩阵的定义与性质,探讨这些性质之间的内在联系,并给出基于二元语义判断矩阵的排序算法;通过对二元语义评价值与模糊数以及语言评价值的转化关系的研究,论证转化后的二元语义判断矩阵仍然具有一致性等性质,从而保证评价信息的完整性与真实性。最后给出一个航线优选的算例。     

航空公司航线网络设计的一种三阶段方法

采用三阶段方法来构建航空公司的航线网络,首先利用推广的F loyd算法得到候选航线,然后基于多属性决策方法从候选航线集中选出有效航线构成航线网络,最后结合民航实际建立了航班频率非线性整数规划模型,并采用ILOG软件求解所建模型,从而得到合理的航空公司航线网络设计方案。文中算例证明了本文航线网络设计方法的可行性和有效性。     

Glacier mapping based on rough set theory in the Manas River watershed

Precise glacier information is important for assessing climate change in remote mountain areas. To obtain more accurate glacier mapping, rough set theory, which can deal with vague and uncertainty information, was introduced to obtain optimal knowledge rules for glacier mapping. Optical images, thermal infrared band data, texture information and morphometric parameters were combined to build a decision table used in our proposed rough set theory method. After discretizing the real value attributes, decision rules were calculated through the decision rule generation algorithm for glacier mapping. A decision classifier based on the generated rules classified the multispectral image into glacier and non-glacier areas. The result of maximum likelihood classification (MLC) was used to compare with the result of the classification based on the rough set theory. Confusion matrix and visual interpretation were used to evaluate the overall accuracy of the results of the two methods. The accuracies of the rough set method and maximum likelihood classification were compared, yielding overall accuracies of 94.15% and 93.88%, respectively. It showed the area difference based on rough set was smaller by comparing the glacier areas of the rough set method and MLC with visual interpreter, respectively. The high accuracy for glacier mapping and the small area difference for glacier based on rough set theory demonstrated that this method was effective and promising for glacier mapping.     

A comparative study of decision tree,random forest,and convolutional neural network for spread-F identification

Ionospheric spread-F (SF) is a commonly observed phenomenon of electron density perturbation in the F-layer. The ionospheric irregularities structure has an adverse effect on the propagation of electromagnetic waves in the ionosphere. The automatic identification of ionospheric spread-F and statistical study of the formation of spread-F are of great significance to the study of the physical mechanism of ionospheric inhomogeneity and for prediction of ionospheric irregularities. In this paper, we describe and implement three automatic identification methods of spread-F based on machine learning: decision tree, random forest, and convolutional neural network (CNN). The performance of these automatic identification methods was verified using a large set of test data. Results show that the accuracy of all three methods on identifying ionograms with spread-F exceeded 90%. After comparing the results of the three methods, we found that the decision tree method was the simplest and with the structure easiest to be understood, and it required the shortest interpretation time. In terms of the identification results, the random forest method provided better results than the decision tree method, and the CNN method was the best at accurately identifying ionograms with spread-F.     

运载火箭推力故障下基于智能决策的在线轨迹重规划方法

为了提高运载火箭上升段飞行中推力故障下轨迹重规划的计算效率,提出了一种基于智能决策的在线轨迹重规划方法,将原问题转化为最优救援轨道的在线智能决策和成熟的燃料最优轨迹规划问题进行求解。通过离线求解不同故障状态对应的轨迹重规划问题,建立"故障状态-救援轨道"样本集,基于径向基神经网络建立最优救援轨道的决策模型,并将决策模型装订箭上。在实际飞行中以当前故障状态作为输入,利用决策模型可在线快速决策出最优救援轨道根数,进而求解以救援轨道为目标轨道的燃料最优轨迹规划问题,从而完成推力故障下的在线轨迹重规划。数值仿真表明,与直接求解轨迹重规划问题相比,该方法的计算效率提高了两个数量级以上,同时给出一致的最优救援轨迹。     

基于空中交通密度的进场航班动态协同排序方法

为适应协同决策（CDM）需要，考虑空管、航空公司和机场的诉求，对进场航班动态协同排序问题进行了系统的研究。设计了一种进场航班动态排序方法，提出了一种时隙交换方法，建立了基于空中交通密度的进场航班协同排序模型，设计了精英保留的遗传算法和带精英策略的快速非支配排序遗传算法以求解所建模型，寻求进场航班动态协同排序的最优解。仿真结果表明，较基于滚动时域控制（RHC）方法，动态协同方法所得结果与排序开始时间无关，所需排序次数平均减少26.4%，且排序效率更高。较先到先服务（FCFS）方法，动态协同方法在高密度条件下各排序阶段最后一个进场航班的落地时间平均提前199.8 s；中密度条件下各排序阶段航班延误总时间平均减少29.9%，航班延误均衡性平均提高34.4%；低密度条件在航班正常率及航班延误公平性得到保证的前提下，满足时隙交换规则的排序阶段均增加了1种进场航班排序模式。所提方法可对进场航班进行优化排序，显著提高跑道容量，有效提升航班延误均衡性和航班延误公平性，契合协同决策理念，可实现三方协同排序。     

应用UBET优化开式模锻中连皮厚度参数

连皮厚度是开式模锻工艺参数中的一个重要参量，它对模锻变形力和材料的消耗有很大的影响。本文应用上限单元法（ＵＢＥＴ）对连皮厚度进行了优化设计。基于连皮厚度和飞边高度间的相对大小关系，建立了三种不同的变形流动模式和动可容速度场，根据上限原理和黄金分割法，利用ＴｕｒｂｏＣ语言编程求解，获得了最大锻造力的最佳上限解，并和实验相比较，两者吻合得较好，表明建立的动可容速度场是合理可行的。以最大锻造力和连皮体积的乘积作为优化准则，更好地得到了最佳连皮厚度值。     

武器装备采办模糊多属性群体决策方法

针对武器装备采办的模糊多属性群体决策问题,文章假设定性属性指标都是梯形模糊数状态,运用模糊数学理论和广义海明权距离,提出了一种定性判断和定量分析相结合的武器装备采办模糊多属性群体决策方法,并给出了一个方法应用及求解计算的实际例子,算例结果证明了方法有效。     

论飞机设计发图

设计发图是飞机设计研制过程中非常重要的一个阶段 ,是涉及飞机几乎所有专业和大批专业设计人员的复杂工程。必须精心计划和组织管理 ,并科学合理地解决与设计发图直接有关的技术问题。     

基于信息公理的车间布局问题评价方法

车间布局评价问题属于典型多属性决策问题.为了使信息公理更适合于解决多属性决策问题,通过增加满意度项改进了原有的信息量计算方法.属性值被划分为精确型、不确定型和模糊型,同时针对效益性、成本性、定值性和区间性属性给出了这三种数值类型的信息量的计算办法.改进后的信息量同时反映系统的成功概率以及决策者满意程度,并能够对包含多种数值类型的多属性决策问题进行评价.最后,作为实例,对焊接装配车间的布局方案进行了评价,结果验证了所改进的信息公理对于解决多属性决策问题的可行性和有效性.