关于Vandermonde行列式的推广

本文定义了一类推广的Ｖａｎｄｅｒｍｏｎｄｅ行列式并给出了它的计算公式。Ｖａｎｄｅｒｍｏｎｄｅ行列式及其它已知的若干著名行列式是它的特例。     

基于粗糙集和元胞自动机的配电网空间负荷预测

该文提出一种新颖的配电网空间负荷预测方法,采用元胞自动机(cellular automata,CA)模拟城市土地利用动态发展过程,预测规划区域各小区土地的未来使用类型。根据城市发展的实际情况,确定CA的迭代时间和转换规则调整时间,并采用粗糙集(rough sets,RS)理论逐步对每个调整时间段中可能影响小区土地使用决策的因素进行属性约简,获取动态的元胞自动机转换规则,消除冗余属性,克服了传统方法在获取小区土地使用决策受主观因素影响较大以及在规划年内一直采用静态的土地使用决策规则的缺陷。最后通过1个实例验证了该方法的有效性。     

采用CWP-EM和IPSO-WNN的配电网单相接地故障定位

随着用户对供电质量要求的不断提高,在线解决配电网单相接地故障定位问题成为供电部分的迫切需要。为此提出了一种中性点不接地或经消弧线圈接地的配电网单相接地故障定位的新方法,采用基于卷积型小波包能量矩(CWP-EM)的特征提取方法,对暂态电流信号进行特征向量的提取。相比传统的小波包能量特征提取方法,此方法能更有效地提取信号在各频带上的能量分布特征,并构造特征向量以作为基于免疫粒子群优化算法(IPSO)的3层小波神经网络(WNN)的训练样本集。最后,利用训练好的小波神经网络实现单相接地故障的定位。MATLAB仿真计算结果表明,提出的方法能够充分利用配电网单相接地故障信息,实现更快、更精确的单相接地故障的定位。     

基于粗糙集理论的配电网故障诊断规则提取方法(英文)

As the first step of service restoration of distribution system,rapid fault diagnosis is a significant task for reducing power outage time,decreasing outage loss,and subsequently improving service reliability and safety.This paper analyzes a fault diagnosis approach by using rough set theory in which how to reduce decision table of data set is a main calculation intensive task.Aiming at this reduction problem,a heuristic reduction algorithm based on attribution length and frequency is proposed.At the same time,the corresponding value reduction method is proposed in order to fulfill the reduction and diagnosis rules extraction.Meanwhile,a Euclid matching method is introduced to solve confliction problems among the extracted rules when some information is lacking.Principal of the whole algorithm is clear and diagnostic rules distilled from the reduction are concise.Moreover,it needs less calculation towards specific discernibility matrix,and thus avoids the corresponding NP hard problem.The whole process is realized by MATLAB programming.A simulation example shows that the method has a fast calculation speed,and the extracted rules can reflect the characteristic of fault with a concise form.The rule database,formed by different reduction of decision table,can diagnose single fault and multi-faults efficiently,and give satisfied results even when the existed information is incomplete.The proposed method has good error-tolerate capability and the potential for on-line fault diagnosis.