基于人工神经网络的系统建模及MATLAB实现

为了提高科研项目评估的客观性和公正性,选用BP网络为模型,利用逆向建模技术和MATLAB实现了"科研项目选题决策综合模糊评估系统"。测试数据表明该系统能较准确地对科研项目作出评估得分。     

基于因子分析的陕西省城市投资环境综合评价

选取自然资源环境、经济环境、基础设施环境、社会服务环境、人口劳动力环境和社会文化环境6个子系统的18个指标构建了城市投资环境指标体系,以陕西省下属的10个地级市为研究对象,采用因子分析的方法,对陕西省城市投资环境进行了实证分析。     

为自治而斗争:解读中世纪大学的命运

自治斗争从中世纪大学诞生开始就不可避免地贯穿在它整个发展过程中。可以说中世纪的历史就是教会与国家的冲突史,大学为获得自身独立发展的空间周旋于教会与国家相互间权力争夺的漩涡中。大学在这一过程中通过各种方式在不同时期取得过自治斗争的胜利,但最终也没能逃脱被强大政权干预的宿命。大学的活力源于自治斗争,中世纪大学自治斗争的过程能够给中国现代大学提供相关经验。     

复方蒙药广枣-肉豆蔻片的制备与质量控制

研究了广枣-肉豆蔻片的制备过程并对其质量进行控制。基于《中国药典》(2020年版)片剂项要求,考察片剂的外观性状、硬度、崩解时限、重量差异及脆碎度;采用高效液相色谱法测定广枣-肉豆蔻片中4种抗氧化成分的含量。结果表明,片剂外表光滑,色泽均匀,硬度值处于30～40 N,崩解时限控制在10 min内,脆碎度小于1%;槲皮素、原儿茶酸、甲基丁香酚、肉豆蔻醚分别在0.16～0.8μg/mL(r=0.999)、4～20μg/mL(r=0.999)、8～40μg/mL(r=0.999)、100～500μg/mL(r=0.999)内呈良好的线性关系,平均回收率分别为99.3%、101.6%、100.3%、99.3%。且方法学验证项下精密度、稳定性和重复性试验的相对标准偏差(relative standard deviation, RSD)数值均未超过2%。该含量测定方法操作简便、专属性强、结果准确可靠,可为复方蒙药广枣-肉豆蔻片的质量标准提供参考。     

无迹卡尔曼滤波估计空间目标特征信息

为了加强对空间目标,尤其是非合作目标的探测监视,空间目标的各种特性正受到越来越多的关注。本文通过无迹卡尔曼滤波UKF对空间目标的位置、速度、姿态、角速度和材料复折射率这5种状态参数进行了反演估计。利用观测角度、光度和偏振度数据作为观测值估计目标的状态,基于位置与速度运动学模型和姿态与角速度动态模型,完成5种状态的时间演化,实现了对5种状态参数的联合估计。仿真结果表明,设置合理的状态初始值、状态方程和测量方程噪声,5种状态参数误差均能合理收敛,UKF能够较好地预测空间目标的5种特征参数,同时也验证了观测角度、光度和偏振度数据可以用于反演空间运动目标的这5种非直接观测特征信息。     

基于孤岛划分约束的有源配电网故障恢复策略

为提高供电恢复效果,更好地应对当前有源配电网信息-物理耦合程度不断加深的形势,提出了一种考虑信息流、能量流、业务流多流融合以及智能软开关(soft open point,SOP)作用的孤岛划分算法,基于该算法实现供电恢复策略。首先,为保证负荷的可靠恢复,该策略深入研究信息-物理耦合并建模,对节点信息重要度排序,讨论其对负荷恢复的影响;其次,构建了SOP的稳态模型,分析了SOP的工作原理及控制模式;接着,为了更大程度、更加灵活地恢复负荷,考虑SOP的作用,建立考虑光伏时变性及负荷运行特性的有源配电网孤岛划分模型;最后,算例仿真验证所提策略的有效性。     

基于时延嵌入式隐马尔科夫模型的癫痫脑电分类算法

癫痫脑电的分类识别能够为癫痫的预警和病程的发展监测提供强有力的技术支持。传统的癫痫脑电分类识别方法需要从较长的时间序列中提取特征,难以刻画大脑的瞬态变化,检测低效且耗时,降低了癫痫预警的有效性。针对上述问题,提出一种基于隐马尔科夫模型的癫痫脑电分类算法。该方法通过时延嵌入式隐马尔科夫模型(time-delay embedded hidden Markov model,TDE-HMM)对脑电进行状态估计,并提取状态序列中的状态切换特征,通过多层感知机(multiple layer perceptron,MLP)实现对不同癫痫发作阶段脑电的有效辨识。实验结果表明,相较于小波变换、微分熵等传统特征,所提方法准确率高,能够有效刻画癫痫不同阶段的大脑状态变化,为癫痫脑电的分类识别和状态分析提供了新的备选方案。     

Operational Patterns of Industrial Symbiosis Network in Industrial Cluster District Based on Circular Economy Theory

Industrial symbiosis network （ISN） is an efficient organizational form for improving resource recycling and efficiency in industrial cluster district. Because of the variety of industrial cluster district formation model, the industrial symbiosis network is different with each other. Based on the circular economy theory, combing with international tendency of cluster district, the paper puts forward the relying-on-oriented industrial symbiosis network. Meanwhile, it also analyzes its organizational mechanism, operating pattern and environmental performance. Through the above efforts, we hope it could be helpful for industry cluster district sustainable development in China.     

Missile robust gain scheduling autopilot design using full block multipliers

Reduction of conservatism is one of the key and difficult problems in missile robust gain scheduling autopilot design based on multipliers. This article presents a scheme of adopting linear parameter-varying (LPV) control approach with full block multipliers to design a missile robust gain scheduling autopilot in order to eliminate conservatism. A model matching design structure with a high demand on matching precision is constructed based on the missile linear fractional transformation (LFT) model. By applying full block S-procedure and elimination lemma, a convex feasibility problem with an infinite number of constraints is formulated to satisfy robust quadratic performance specifications. Then a grid method is adopted to transform the infinite-dimensional convex feasibility problem into a solvable finite-dimensional convex feasibility problem, based on which a gain scheduling controller with linear fractional dependence on the flight Mach number and altitude is derived. Static and dynamic simulation results show the effectiveness and feasibility of the proposed scheme.     

Convergence rates of Markov chain approximation methods for controlled diffusions with stopping

<正> This work is concerned with rates of convergence of numerical methods using Markov chainapproximation for controlled diffusions with stopping (the first exit time from a bounded region).In lieuof considering the associated finite difference schemes for Hamilton-Jacobi-Bellman (HJB) equations,a purely probabilistic approach is used.There is an added difficulty due to the boundary condition,which requires the continuity of the first exit time with respect to the discrete parameter.To prove theconvergence of the algorithm by Markov chain approximation method,a tangency problem might arise.A common approach uses certain conditions to avoid the tangency problem.Here,by modifying thevalue function,it is demonstrated that the tangency problem will not arise in the sense of convergencein probability and in L~1.In addition,controlled diffusions with a discount factor is also treated.