Classification and assessment of power system static security using decision tree and random forest classifiers

The power system static security classification and assessment is essential in order to identify the post‐contingency problems and take corrective measures and to protect the system from blackout. In this paper, application of two data mining classifiers have been proposed for the security classification and assessment of a multiclass security problem. To design the security problem, contingency analysis is carried out under N‐1 line outage, and static severity index (SSI) is computed, which is a function of the line overload and the voltage deviation using Newton–Raphson load flow method, considering the variable load and generating conditions. Corresponding to the computed values of SSI, the voltage, phase angle, Mega Volt Ampere line flow and so on, a 1 × 7 pattern vector is generated. The generated pattern vectors are used to design a multiclass security problem. The designed security pattern vectors are given as inputs to the decision tree (DT) and random forest (RF) model in order to classify the security status of the power system. The proposed classifiers are investigated on an IEEE 30‐bus test system. The classification accuracy of the DT and the RF are compared with state‐of‐the‐art classifier models, namely, multilayer perceptron (MLP), radial basis function (RBF), and support vector machine (SVM).The simulation results clearly indicate that the proposed DT and RF classifiers are more efficient, reliable, and out performs MLP, RBF, and SVM classifiers for the assessment of the security status of the power system. Hence, DT and RF classifiers are found to be suitable for online implementation. Copyright © 2015 John Wiley & Sons, Ltd.     

基于多级队列调度模型的研究

首先根据传统的Qo S应用瓶颈引出多级调度的必要性,然后根据DSL论坛定义的层次化Qo S基本模型提出一个五级调度的调度树模型。该模型可灵活配置调度节点和调度单元,从而实现六级队列灵活调度以及五级的流水调度,确保了调度的效率和速度。最后,在以太网接口上应用该多级调度的模型实现多用户多业务的服务质量,为网络流量管理提供了一种合理的机制。     

基于新型故障搜寻策略的检测系统设计

为了达到复杂系统快速故障搜寻的目的,设计了一种基于二元决策图优化的新型故障搜寻策略的检测系统设计。通过对基于二元决策图优化的故障搜寻方法研究和实际的硬件电路设计,最终实现了检测系统的软硬件设计。使用这种方法能够很好的实现故障诊断系统在嵌入式平台的开发,并能够取得较好的诊断效果。     

街道可视因子对夏季午后城市街道峡谷 微气候和热舒适度的影响研究

城市街道作为城市最重要的活动空间,对其进行合 理的规划和改造有利于改善城市热环境。揭示街道可视因子对 街道峡谷微气候和热舒适度的作用机制,可以作为城市规划设 计的理论基础。选取杭州市典型街道峡谷为研究对象,通过 实测和数据分析发现,在夏季午后,不同街道峡谷内微气候和 热舒适度存在明显差异：各街道峡谷之间空气温度、平均辐 射温度和生理等效温度最大值与最小值之差分别达到了2.9、 25.3和15.3℃;N-S朝向的街道热环境优于E-W朝向的街 道,但街道的开敞程度和植物遮阴会抵消街道朝向的影响。研 究也发现,在午后,街道可视因子会对街道峡谷热环境产生不 同程度的影响,天空可视因子越高,街道峡谷空间越开敞,街 道热环境和热舒适度越差;建筑可视因子与城市街道峡谷微气 候和热舒适度相关性不大;而树木可视因子则对街道峡谷热环 境具有重要影响,树木可视因子越高,街道树木的遮阴程度越 高,街道内热环境和热舒适度越佳,这种现象在E-W朝向的 街道峡谷中表现得更为明显。     

基于深度学习的小口径弹药装配设备故障诊断专家系统

针对小口径弹药装配设备故障诊断智能化程度不足、诊断效率低以及误诊率高等问题,开展小口径弹药装配设备故障诊断技术和专家系统研究。为提高复杂装备故障知识推理及判别精度,研究基于知识图谱和故障树的故障类别知识库构建方法,提出基于规则和案例的故障知识推理方法,采用深度学习算法进行故障知识推理和更新,构建故障诊断模型并用于小口径弹药装配设备故障诊断专家系统。结果表明：该系统可实现对小口径弹药装配设备故障的智能预测和分析,符合制造装备智能化发展要求,为制造装备智能化、信息化的研制发展和推广应用提供参考。     

基于ENVI-met模拟的不同用地类型居住小区绿地布局对PM2.5的影响

居住区绿地作为城市绿地的主要组成肌理,对改善空气质量起着重要作用。首次将ENVI-met用于居住小区绿地布局与PM2.5的模拟,选取武汉市典型的一类、二类、三类小区,定量分析不同草地、乔木布局对PM2.5的影响。研究表明,集中型的草地布局、四周型的乔木布局能更有效降低小区PM2.5浓度;分散型的草地布局、集中型的乔木布局最不利于消减PM2.5;四周型的乔木布局对阻滞道路上PM2.5的扩散效果最佳。同种绿地布局形式下,二类小区的平均PM2.5浓度最低,三类小区最高,PM2.5空间分布在3类小区中也具有一定的差异。研究揭示了居住小区绿地布局对PM2.5的影响机制,为小区绿地的规划设计实践提供一定参考。     

基于生成树集结算子的群组AHP判断矩阵集结算法

针对现有群组AHP(Analytic Hierarchy Process)判断矩阵集结算法,偏重于专家权重的选择,而忽略判断矩阵元素之间联系的不足,提出一种基于生成树集结算子的群组AHP判断矩阵集结算法.该算法依据判断矩阵与简单无向图生成树之间的关系,采用生成树集结算子获取完全一致集结矩阵,并利用完全一致集结矩阵和群组关联集结矩阵,综合考虑判断矩阵元素之间的个体一致性和群组关联性,计算获得满足一致性约束和最优相似性的群组集结结果.通过算例分析,说明该算法的可行性与有效性.     

Learning Association Rules and Tracking the Changing Concepts on Webpages: An Effective Pornographic Websites Filtering Approach

We applied the decision tree algorithm to learn association rules between webpage’s category (pornographic or normal) and the critical features. Based on these rules, we proposed an efficient method of filtering pornographic webpages with the following major advantages: 1) a weighted window-based technique was proposed to estimate for the condition of concept drift for the keywords found recently in pornographic webpages; 2) checking only contexts of webpages without scanning pictures; 3) an incremental learning mechanism was designed to incrementally update the pornographic keyword database.     

Modeling of quantitative relationships between physicochemical properties of active pharmaceutical ingredients and tensile strength of tablets using a boosted tree

Objectives: The aim of this study was to explore the potential of boosted tree (BT) to develop a correlation model between active pharmaceutical ingredient (API) characteristics and a tensile strength (TS) of tablets as critical quality attributes.

Methods: First, we evaluated 81 kinds of API characteristics, such as particle size distribution, bulk density, tapped density, Hausner ratio, moisture content, elastic recovery, molecular weight, and partition coefficient. Next, we prepared tablets containing 50% API, 49% microcrystalline cellulose, and 1% magnesium stearate using direct compression at 6, 8, and 10?kN, and measured TS. Then, we applied BT to our dataset to develop a correlation model. Finally, the constructed BT model was validated using k-fold cross-validation.

Results: Results showed that the BT model achieved high-performance statistics, whereas multiple regression analysis resulted in poor estimations. Sensitivity analysis of the BT model revealed that diameter of powder particles at the 10th percentile of the cumulative percentage size distribution was the most crucial factor for TS. In addition, the influences of moisture content, partition coefficients, and modal diameter were appreciably meaningful factors.

Conclusions: This study demonstrates that BT model could provide comprehensive understanding of the latent structure underlying APIs and TS of tablets.     

基于故障树的采煤机液压盘式制动器故障研究

通过逻辑分析构建了采煤机液压盘式制动器故障与基本事件的故障树模型;采用二元决策图分析故障树模型,得到了导致制动器故障发生的最小割集,并通过状态枚举法计算了基本事件的结构重要度。结果表明,所列举的任一基本事件的失效均会导致制动器故障。为采煤机液压盘式制动器的故障诊断提供了理论依据。