ID	原文	译文
7504	首先计算信息流进行全局因果分析,构造0/1优化问题,获得最优初始网络结构;	0/1 global causal analysis calculation flow first, structure optimization, to obtain the optimal initial network structure;
7505	在此初始结构的基础上产生搜索空间,采用贪婪算法搜索最优结构弧,同时由信息流确定弧方向,实现网络结构的一体化学习。	On the basis of the initial structure of the search space, USES the greedy algorithm to search the optimal arc structure, be determined by the flow of arc direction at the same time, to realize the integration of network structure learning.
7506	首次将信息流引入贝叶斯网络的结构学习,优化了初始搜索空间,实现了弧和弧方向的同步确定,更能获得近似全局最优结构。	First introduce the information flow of bayesian network structure learning, to optimize the initial search space, realize the simultaneous determine direction of arcs and arc, more can obtain the approximate global optimal structure.
7507	实验表明,改进算法较其他算法的准确性和学习效率更高。	The accuracy of the experiment indicates that the improved algorithm is compared with other algorithms and learning more efficient.
7508	针对复杂可修装备群稳态可用度解析计算困难的问题,提出一种通过构建多个相关连续时间马尔可夫链(continuous time Markov chain,CTMC)来求解稳态可用度的方法。	Steady-state availability for complex repairable equipment group analytic calculation difficult problem, put forward a kind of by building multiple related continuous time Markov chain (continuous time Markov chain, the CTMC) method to solve the steady-state availability.
7509	通过分析装备群的使用与维修特点,采用可用装备数、备件库存数、备件短缺数来刻画部件的状态,分别建立各类部件库存状态的CTMC,进而建立用于分析装备群稳态可用度的CTMC族模型;	Characteristics through the analysis of the use and maintenance of equipment group, the number of available equipment, spare parts inventory, shortage of spare parts to depict the components status, inventory status CTMC respectively set up all kinds of parts, and set up for analyzing equipment group of CTMC model for steady availability;
7510	并根据各类部件的状态转移关系及转移率矩阵,在求解各类部件CTMC模型稳态概率的基础上,给出各类部件的期望备件短缺数和装备群稳态可用度算法。	And according to the various parts of state transfer relations and transfer rate matrix, in solving all kinds of parts CTMC model, on the basis of the steady-state probability, gives all kinds of parts expect algorithm for steady state availability of spare parts and equipment shortages.
7511	最后通过构建数值案例,将提出的CTMC族模型结果分别与仿真分析和多级可修产品库存控制模型的结果进行对比,验证了提出模型和算法的有效性。	By building a numerical case, finally puts forward the CTMC model results, respectively, and the simulation analysis and multistage repairable product inventory control model, comparing the results verify the effectiveness of the proposed model and algorithm.
7512	以一类翼展可变的飞行器模型为对象,研究了一种针对参数不确定的线性变参数(linear parameter varying,LPV)系统的滑模变结构鲁棒控制问题。	With a wingspan variable aircraft model as the object, study a for parameter uncertain linear parameter varying (linear parameter varying, LPV) sliding mode variable structure robust control problem of the system.
7513	首先,通过Jacobian线性化和模型张量积转化将变体过程中的非线性模型最终简化为多胞体LPV系统。	First of all, through the Jacobian linearization and model transformation of tensor product variants eventually simplified nonlinear model which is in the process of cell body LPV systems.