基于LP与小波包的复杂机电系统监测序列混沌降噪方法

针对流程工业生产系统监测数据存在强噪声和混沌性的特点,提出了一种局部投影方法(Local Projection Method)与小波包方法相结合的信号降噪方法。该方法先利用局部投影方法从动力学系统嵌入流形的角度进行多次迭代降噪,并根据关联维数来判定迭代终止;再利用小波包方法从频率的角度进行降噪,抑制高频噪声的干扰,取得了较好的降噪效果。用Lorenz时间序列进行仿真验证,对仿真时间序列加入不同程度的噪声,对比分析小波包、局部投影与该方法降噪后的相空间、SNR值和最大Lyapunov指数,证明了该方法对于中高强度噪声具有更好的降噪效果。并将该方法用于某压缩机组的实际监测数据降噪,评估三种方法的降噪效果,进一步验证了该方法的优越性。     

基于边缘和局部熵融合的视觉安全性评估方法

针对基于局部熵进行加密图像视觉安全性评估存在块效应的局限性，引入图像的边缘特征，通过共有边缘来衡量加密图像与原始图像的边缘相似度，消除了块效应。由于局部熵对加密等级低的图像不敏感，边缘相似度对加密等级高的图像不敏感，将两个评估方法进行自适应融合，提出[SLEES]（Local Entropy and Edge Similarity，[SLEES]）指标。通过改变图像像素位置和图像像素值的加密方式处理图像和视频帧进行测试，实验结果表明，[SLEES]指标相比传统评估指标有更好的鲁棒性，评估范围更广。     

Reduced basis method for managed pressure drilling based on a model with local nonlinearities

To circumvent restrictions of conventional drilling methods, such as slow control actions and inability to drill depleted reservoirs, a drilling method called managed pressure drilling (MPD) has been developed. In MPD, single-phase flow processes can be modeled as a feedback interconnection of a high-order linear system and a low-order nonlinear system. These nonlinearities appear locally both inside and at the boundaries of the computational domain. To obtain a fast simulation platform for real-time purposes (eg, online model-based controller implementation), model order reduction is required for MPD. However, the local nonlinearities render applying model order reduction techniques challenging. In this study, a new approach is proposed to deal with such nonlinearities within the reduced basis (RB) context and it is successfully tested on a model for MPD. Contrary to the classical RB technique, the proposed approach not only does not generate nonphysical spikes at the locations of these local nonlinearities but also yields high speedup factors. The obtained reduced-order model can be used for efficient online simulation and controller design for drilling systems with MPD.     

Structural optimization with an automatic mode identification method for tracking the local vibration mode

Traditional optimization methods, which take a specific order of modal frequency as the design constraint, could fail to obtain the desired solution because of modal substitution. An improved optimization model with continuous sizing variables is established to solve this problem, in which the minimum weight and a given local modal frequency are considered as the objective and the constraint. To capture accurately the expected mode of vibration, a local mode identification technique is proposed based on the strain energy ratio between the local area and the whole structure. With that scheme, an optimization system is developed, in which the local mode can be effectively identified and the constraint can be updated with it in the iteration process. Two numerical examples, of a reinforced plate and a satellite structure, are applied to illustrate the effectiveness and efficacy of the proposed method.     

Hybrid self-inertia weight adaptive particle swarm optimisation with local search using C4.5 decision tree classifier for feature selection problems

ABSTRACT

Feature selection is an important task to improve the classifier’s accuracy and to decrease the problem size. A number of methodologies have been presented for feature selection problems using metaheuristic algorithms. In this paper, an improved self-adaptive inertia weight particle swarm optimisation with local search and combined with C4.5 classifiers for feature selection algorithm is proposed. In this proposed algorithm, the gradient base local search with its capacity of helping to explore the feature space and an improved self-adaptive inertia weight particle swarm optimisation with its ability to converge a best global solution in the search space. Experimental results have verified that the SIW-APSO-LS performed well compared with other state of art feature selection techniques on a suit of 16 standard data sets.     

煤矿局部通风机风筒保护装置设计应用

为了提高掘进巷道通风稳定性,降低局部通风机风筒损坏率及漏风系数,提高风筒使用寿命,潞安集团司马煤业公司通风队通过技术分析设计了一套风筒保护装置,该装置提高了风筒使用寿命,降低了风筒漏风量,避免了掘进巷道风量不足现象,取得了显著应用成效。     

The structural variability of quarters and residential areas in the historical texture of the city of Yazd based on Islamic rules and jurisprudence: a case study of Golchinan quarter

According to many researchers and scholars, religious beliefs can be considered as the most influential factor in forming Muslim urban spaces and their architectural elements. In fact, historical cities reflect the culture and beliefs of their residences. Among all historical places in Iranian cities, the historical texture of the city of Yazd, especially the quarters since the age of Qajar dynasty, are well preserved. The present study aims at identifying the Islamic principles and values influencing the formation of architectural spaces and the extent of their applications in one of the historical quarters known as Golchinan. The results of the conformation of the theoretical findings with the data acquired from field studies revealed that almost 90% of the urban and architectural spaces (e.g. residential areas, mosques, bazaars, and pathways) in Yazd are directly influenced by Islamic principles. In other words, there is a strong conformity between the accepted Islamic values of the society and what actually was applied to urban constructions during Qajar dynasty.     

Title加TextRank抽取关键句的情感分类研究

考虑到不同句子对判断文档情感倾向的重要程度不同，因而区分文档的关键句和细节句将有助于提高情感分类的性能。同时，考虑到Title和上下文信息，提出了一种基于Title和加权TextRank抽取关键句的情感分析方法SKTT，实现了高效的情感分析。根据文档Title的情感权重计算Title贡献度，考虑到标点和语义规则对情感倾向的影响；根据加权TextRank算法思想，在文档正文中构建了一个情感句有向图来提取关键句；计算所有关键句的情感倾向进行情感分类。在4个领域上进行实验，实验结果表明，该SKTT方法性能明显优于Baseline，具有高效性。     

基于改进蚁群算法的三维路径规划

针对移动机器人在海水环境中的三维路径规划问题容易陷入局部最优和收敛慢等瑕疵，根据三维环境全局信息来改进蚁群算法以提高实时性和收敛速度。改进蚁群算法的启发函数，采用局部信息和全局信息结合动态地改进信息素更新方式，以及根据三维空间中路径的平坦程度和光滑度二阶微分分别增加了一阶微分和二阶微分来再次修改信息素更新规则。仿真对比实验结果显示改进后的蚁群算法克服了收敛速度慢、容易陷入局部最优的缺点。