基于隐马尔可夫模型的非侵入式负荷监测泛化性能改进

隐马尔可夫模型(HMM)是非侵入式负荷监测常用的算法.由于电压波动与负荷自身电气特性变化等原因,负荷的测量状态如功率可能持续变化,运行过程中出现新的状态转移,但当前基于HMM的非侵入式负荷监测方法并未考虑如何处理该情况,缺乏状态辨识与功率分解的泛化能力.针对这一问题,本文提出并构建二元参数隐马尔科夫模型(BPHMM),结合DBSCAN聚类算法,基于有功功率和稳态电流对负荷状态进行聚类,降低了因电压波动和噪声数据对负荷状态聚类结果造成干扰的可能性;改进维特比算法使其考虑到HMM模型参数更新以实现对负荷状态预测泛化性能的改进;考虑到功率的随机波动性,基于极大似然估计原理构建功率计算优化模型并实现负荷的功率分解.本文采用公共数据集AMPds2对所述方法进行验证,测试算例验证了所述方法的有效性.     

Elliptic Gauss sums and applications to point counting

We define a class of algebras over finite fields, called polynomially cyclic algebras, which extend the class of abelian field extensions. We study the structure of these algebras; furthermore, we define and investigate properties of Lagrange resolvents and Gauss and Jacobi sums.     

A Polynomial Approach to the Constructive Induction of Structural Knowledge

The representation formalism as well as the representation language is of great importance for the success of machine learning. The representation formalism should be expressive, efficient, useful, and applicable. First-order logic needs to be restricted in order to be efficient for inductive and deductive reasoning. In the field of knowledge representation, term subsumption formalisms have been developed which are efficient and expressive. In this article, a learning algorithm, KLUSTER, is described that represents concept definitions in this formalism. KLUSTER enhances the representation language if this is necessary for the discrimination of concepts. Hence, KLUSTER is a constructive induction program. KLUSTER builds the most specific generalization and a most general discrimination in polynomial time. It embeds these concept learning problems into the overall task of learning a hierarchy of concepts.     

广义高阶Euler数的同余

对于任意的正整数a,利用展开式1a(exp(t)+exp(-t))/2+1-()a k=∑∞n=0E(k)n,at nn!定义了一类广义k阶Euler数Ekn,a,并利用对比系数法,幂级数展开等初等方法得到一些相关的递推公式,同余式以及反转公式.     

回转窑主拖动变频调速技术的应用及推广前景

文章介绍了变频调速在回转窑主拖动应用技术的使用过程，同时还介绍了变频器、电机的选型及推广应用前景。     

微分中值定理的推广

微分中值定理是微分学中较著名的定理,很多人对它进行了研究,文章把区间及端点的函数值推广为无限。     

珠江流域概况及水文特性分析

介绍了珠江流域自然地理概况,详细分析了水文气象、降水、蒸发、径流、暴雨洪水、泥沙、成潮和潮汐等方面的水文特性。     

Analysis of multivariate frequency data by graphical models and generalizations of the multidimensional row-column association model.

Models used to analyze cross-classifications of counts from psychological experiments must represent associations between multiple discrete variables and take into account attributes of stimuli, experimental conditions, or characteristics of subjects. The models must also lend themselves to psychological interpretations about underlying structures mediating the relationship between stimuli and responses. To meet these needs, the author extends the graphical latent variable models for nominal and/or ordinal data proposed by C. J. Anderson and J. K. Vermunt (2000) to situations in which dependencies between observed variables are not fully accounted for by the latent variables. The graphical models provide a unified framework for studying multivariate associations that include log-linear models and log-multiplicative association models as special cases. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On the origin and early use of the term vicarious trial and error (VTE).

Several of the generalizations made by Goss and Wischner (see 31: 2422), in their review of the studies concerned with vicarious trial and error, are evaluated. The author confines his statements to the early research on "VTE." (PsycINFO Database Record (c) 2010 APA, all rights reserved)