K_(1.3)—Free图成为哈米顿的一个邻域并条件

在本文中,我们给出下列定理:设G为阶是n≥3的2—连通,K_(13)—free图且满足NC(G)≥n—δ—2。则G为哈米顿的,这里NC(G)=min{|N(u)N(v)|E}。     

不含4圈的最大简单图边数的下界

证明了具有不小于6个顶点的不包含4圈的简单图的最大可能边数的下界是2n-5。     

关于图的局部调和着色

通过引入图的局部调和着色的概念,给出了任意图的局部调和着色的不可改进的上、下界;同时讨论了图的局部调和着色的一些性质,以及一些特殊图的局部调和着色数.     

用键图模拟方法分析连杆助力器稳定性

用键图模拟车辆上广泛应用的连杆式助力器的工作过程,建立空间状态方程.并对状态变量的稳定性进行分析.找出提高助力器稳定性的措施.     

A partial Granger causality based method for analysis of parameter interactions in bioreactors

In this article, we utilize the concept of partial Granger causality to study the penicillin production process under several operating conditions. We propose a graph-theoretic template (causal network) based method for intelligent process monitoring. We validate our results with the aid of existing knowledge and available literature. The proposed method is quite general and can be extended to analyze several physical, chemical or biological systems.     

A Causal Fusion Inference Method for Industrial Alarm Root Cause Analysis Based on Process Topology and Alarm Event Data

Modern industrial systems are usually in large scale, consisting of massive components and variables that form a complex system topology. Owing to the interconnections among devices, a fault may occur and propagate to exert widespread influences and lead to a variety of alarms. Obtaining the root causes of alarms is beneficial to the decision supports in making corrective alarm responses. Existing data-driven methods for alarm root cause analysis detect causal relations among alarms mainly based on historical alarm event data. To improve the accuracy, this paper proposes a causal fusion inference method for industrial alarm root cause analysis based on process topology and alarm events. A Granger causality inference method considering process topology is exploited to find out the causal relations among alarms. The topological nodes are used as the inputs of the model, and the alarm causal adjacency matrix between alarm variables is obtained by calculating the likelihood of the topological Hawkes process. The root cause is then obtained from the directed acyclic graph (DAG) among alarm variables. The effectiveness of the proposed method is verified by simulations based on both a numerical example and the Tennessee Eastman process (TEP) model.     

A Direct Test for Cointegration Between a Pair of Time Series

In this paper we introduce a new test of the null hypothesis of no cointegration between a pair of time series. For a very simple generating model, our test compares favourably with the Engle–Granger/Dickey–Fuller test and the Johansen trace test. Indeed, shortcomings of the former motivated the development of our test. The applicability of our test is extended to series generated by low-order vector autoregressions. Again, we find evidence that this general version of our test is more powerful than the Johansen test. The paper concludes with an empirical example in which the new test finds strong evidence of cointegration, but the Johansen test does not.     

Temporal aggregation and spurious instantaneous causality in multiple time series models

Large aggregation interval asymptotics are used to investigate the relation between Granger causality in disaggregated vector autoregressions (VARs) and associated contemporaneous correlation among innovations of the aggregated system. One of our main contributions is that we outline various conditions under which the informational content of error covariance matrices yields insight into the causal structure of the VAR. Monte Carlo results suggest that our asymptotic findings are applicable even when the aggregation interval is small, as long as the time series are not characterized by high levels of persistence.     

一类协调图的必要条件

本文研究由ｍ个完全图Ｋｎ恰有一个公共Ｋｒ组成的图Ｂ（ｎ,ｒ,ｍ）的协调性,给出了图Ｂ（ｎ．ｒ,ｍ）是协调图的一个必要条件,并证明了对许多整数ｎ,Ｂ（ｎ,２,２）均不是协调图．