Solving the irregular strip packing problem via guided local search for overlap minimization

The irregular strip-packing problem (ISP) requires a given set of non-convex polygons to be placed without overlap within a rectangular container having a fixed width and a variable length, which is to be minimized. As a core sub-problem to solve ISP, we consider an overlap minimization problem (OMP) whose objective is to place all polygons into a container with given width and length so that the total amount of overlap between polygons is made as small as possible. We propose to use directional penetration depths to measure the amount of overlap between a pair of polygons, and present an efficient algorithm to find a position with the minimum overlap for each polygon when it is translated in a specified direction. Based on this, we develop a local search algorithm for OMP that translates a polygon in horizontal and vertical directions alternately. Then we incorporate it in our algorithm for OMP, which is a variant of the guided local search algorithm. Computational results show that our algorithm improves the best-known values of some well-known benchmark instances.     

分辨矩阵法耗时推算

针对粗集理论的分辨矩阵方法求解知识约简过程中时空性能上存在的问题,提出分辨矩阵法耗时推算的原理和算法,包括2个耗时段的推算及推算结果的可靠性验证。推算可预知分辨矩阵法处理数据所消耗的时间,对数据挖掘实验的可行性进行预测。     

基于传感器数据的配电网设备能效评估

在深入分析配电网设备上加装的各类传感器装置中数据获取情况的基础之上,综合考虑设备的能效影响因素,构建了基于传感器数据的配电网设备能效评估指标体系。根据每个指标在节能潜力、成本和难度方面对配电网设备能效的影响程度不同,构建了递阶层次结构模型,并采用层次分析法（ AHP）进行指标权值计算。根据定量指标易于量化的特征,构建了对标函数,完成了定量指标能效指数的计算。从而实现对配电网设备的能效评估。并以某实际的配电变压器算例验证了所提方法的实用性和有效性。     

基于B-ISVM算法的物联网云存储数据伪装不良信息检测

针对物联网云存储数据伪装不良信息隐蔽性造成的信息量预处理困难、深层次语义理解不准确和样本不均衡等问题,提出了一种基于B-ISVM(Boundary-Incremental SVM)算法的物联网云存储数据不良信息检测算法。在该算法中,首先采取基于均值和标准差的K均值初始聚类分析对云存储数据信息量进行样本空间训练分类;然后将所有样本类进行欧氏距离遍历计算,得到类间子聚类中心距离矩阵和各聚类中心的邻界子聚类区;再通过信息量伪装与筛选原理进行云存储信息真伪筛选,以不良信息在伪信息中发生的概率为指数、以数据安全度阂值和不良伪装信息模板向量集的相似度阂值为指标,对云存储信息量进行识别;最后进行增量模式学习,得到各分类样本最终的最优分类超平面,并将各类检测出的不良伪装信息进行输出。系统测试证明,该算法能快速有效地对物联网云存储数据中的伪装信息进行检测。     

基于贝叶斯网络的航材可修件周转比例计算

将贝叶斯网络运用于航：材可修件周转比例的计算。在贝叶斯网络学习阶段,采用BDe评分函数和贪婪算法搜索网络结构,运用贝叶斯算法进行参数学习,从而建立了可修件消耗定额预测模型,并对预测结果进行分析比较。最后利用贝叶斯网络预测结果进行周转比例的计算工作。结果表明,把贝叶斯网络应用于航材周转比例的计算是可行的。     

软距离计算的地震聚类方法*

传统的基于真实距离的聚类分析方法不利于地震不同断层破裂传播和愈合速度的精确计算。为提高地震预测精度,提出并建立了基于软距离计算的聚类方法。给出了基于软距离聚类过程、软距离计算方法以及具体的基于软距离计算的聚类算法。以现实的强震样本点作为聚类数据源,采用该聚类方法以及其它传统聚类方法对该样本数据进行聚类分析。分析结果表明,采用该聚类方法获得的聚类中心点更接近地壳应力场演变的客观真实性,该聚类分析方法为地震的断层带下次发生强震的精确计算提供了很好的计算依据。     

The use of genetic algorithms for assessment of high voltage fields

There are several numerical methods for calculation of electric fields but they need some sort of experience and trial and error to get the correct solution. A genetic algorithm (GA) based approach is used to eliminate the need for the experience and to save time and effort spent in the trial and error. Two enhancement techniques, namely, Refreshment Method and No-Twins Method, are used with the GA operators to improve the performance of the GA in assessment of high voltage fields. The performance of these two enhancement techniques has been studied for computing the electrostatic field in high voltage applications.     

开卷机剩余长度计算与自动减速原理

在唐钢彩涂入口段,为了保证生产的连续性,当开卷机带钢即将没有的时候,需要自动减速停车,使带尾停在合适的位置,以方便接下来的操作。为达到自动减速,必须准确计算出开卷机的剩余长度,从而准确地确定自动减速时机。因此,介绍了开卷机剩余长度计算与自动减速原理。开卷机的剩余长度计算方法的应用很广,此计算方法也可应用与出口卷曲机的长度计算和其他相关的生产线中的长度计算,对保证生产的连续及操作的简化都起着重要的作用。