基于GIS单线图的配网停电单模拟操作应用研究

配电网停电会造成电力系统供配电可靠性以及服务质量下降,研究基于地理信息系统(GIS)单线图的配网停电单模拟操作应用。利用网格长度作为基本单位建立坐标系,以选取起始点与终止点为基础,通过四参数法将GIS坐标映射至图纸网格内,实现配网内设备初步布局,将杆塔、站房和整体均匀分布作为优化目标,设置多目标优化目标函数实现GIS单线图最终优化。选取某电力公司配网作为单模拟操作应用对象,模拟结果表明,单模拟操作配网停电后,该配网各负荷点年故障率、次平均停电时间以及年停电时间均有所减少,可有效提升配网的供配电可靠性。     

马尔可夫跳变线性系统最优控制的研究现状与进展

马尔可夫跳变线性系统（MJLS）是一种具有多个模态的随机系统，系统在各个模态之间的跳变转移由一组马尔可夫链来决定。MJLS模型因其在表示过程中可以产生突变而更能精确的描述实际工程应用中的系统。近年来，MJLS的最优控制问题成为了研究的热点，动态规划、极大值原理以及线性矩阵不等式等成为了解决此类问题的主流方法。本文对MJLS最优控制领域的研究现状进行了综述。分别对一般情况下、带有噪声的情况下、带有时滞的情况下以及某些特定情况下的MLJS最优控制问题的国内外研究现状进行论述。最后进行了总结并提出MJLS最优控制领域未来值得关注的研究方向。     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Enhanced photoreactivity of MOFs by intercalating interlayer bands via simultaneous ?NCO and ?SCu modification

Herein, we propose a novel method to enhance the photoreactivity of an MOF catalyst by grafting isocyanate bonds ( NCO) and sulfhydryl-complexed copper ( SCu) onto ZIF-8 (NIF-SCu). The grafting process intercalated interlayer bands between the conduction and valence bands of ZIF-8, thereby providing a “ladder” for facile electron transition. The extreme improvement in the photoreactivity of NIF-SCu could be attributed to the enhancement in light responses in the range of 350–450 nm by  NCO groups and the widening of the visible light range of the MOF by  SCu groups. The formation of staggered energy levels in NIF-SCu could also narrow the band gap, lower the resistance, and facilitate the transfer of photogenerated carriers, thereby generating electrons with strong reduction potential in the  SCu conduction band. This study provides a new strategy for improving or even endowing the photoactivity of environmental functional materials with wide bandgaps.     

DNAN及TNT基熔铸炸药综合性能比较

为了对比载体炸药2,4,6-三硝基甲苯(TNT)和2,4-二硝基苯甲醚(DNAN)、以及以它们为基的熔铸炸药的综合性能,系统研究了DNAN和TNT、以及DNAN/HMX(20/80)和TNT/HMX(25/75)熔铸炸药的流变、能量、安全、以及力学等性能。结果表明:载体炸药DNAN(6.87 m Pa·s)的粘度低于TNT(9.05 mPa·s),DNAN/HMX熔铸体系的极限固含量(约80%)高于TNT/HMX熔铸体系(约75%);DNAN/HMX(20/80)和TNT/HMX(25/75)熔铸炸药的爆速分别为8336 m·s~(-1)和8452 m·s~(-1),爆压分别为31.03 GPa和31.44 GPa;在1 K·min~(-1)的慢速烤燃条件下,DNAN/HMX(20/80)和TNT/HMX(25/75)熔铸炸药的响应等级分别为燃烧反应和爆炸反应;在4.51GPa的冲击波入射压力条件下,TNT/HMX(25/75)在8～12 mm内达到完全爆轰,而DNAN/HMX(20/80)在12 mm内未能达到完全爆轰;DNAN/HMX(20/80)的抗拉和抗压强度均大于TNT/HMX(25/75)。因此可以得出结论,在能量性能基本持平的情况下,DNAN/HMX(20/80)熔铸炸药的安全及力学性能优于TNT/HMX(25/75)熔铸炸药。     

采用信息增益率的混合入侵检测模型设计

针对现有混合入侵检测模型仅定性选取特征而导致检测精度较低的问题，同时为了充分结合误用检测模型和异常检测模型的优势，提出一种采用信息增益率的混合入侵检测模型.首先，利用信息增益率定量地选择特征子集，最大程度地保留样本信息；其次，采用余弦时变粒子群算法确定支持向量机参数构建误用检测模型，使其更好地平衡粒子在全局和局部的搜索能力，然后，选取灰狼算法确定单类支持向量机参数构建异常检测模型，以此来提高对最优参数的搜索效率和精细程度，综合提高混合入侵检测模型对攻击的检测效果；最后，通过两种数据集进行仿真实验，验证了所提混合入侵检测模型具有较好的检测性能.     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.