Time dependence of entropy flux and entropy production for a dynamical system driven by noises with coloured cross-correlation

This paper shows the Fokker-Planck equation of a dynamical system driven by coloured cross-correlated white noises in the absence and presence of a small external force. Based on the Fokker-Planck equation and the definition of Shannon＇s information entropy, the time dependence of entropy flux and entropy production can be calculated. The present results can be used to explain the extremal behaviour of time dependence of entropy flux and entropy production in view of the dissipative parameter γ of the system, coloured cross-correlation time τ and coloured cross-correlation strength λ.

A Diagnosis Method of Vibration Fault of a Steam Turbine Based on Information Entropy and Grey Correlation Analysis

The vibration fault, one of the common faults in the steam turbine generator unit, brings great damage to the production and the running process. It is well known that the information entropy is to describe the degree of indeterminacy of the system, so the information entropy can be used to measure Despite its efficiency, one kind of information entropy is just enabled to identify make up for this limitation, based on nalysis was studied for vibration fault the vibration condition of the unit. certain part of the faults. In order to the faulty signals collected from the rotor test platform, the grey correlation adiagnosis of steam turbine shafting in this paper. The reference faulty matrix and the calculation model of grey correlation degree was established based on three kinds of information entropy. The analysis shows that grey correlation analysis is a useful method for fault diagnosis of shafting and can be used as a quantitative index for fault diagnosis.

An Availability Evaluation Method of Web Services Using Improved Grey Correlation Analysis with Entropy Difference and Weight

Web services is one of the basic network services, whose availability evaluation is of great significance to the promotion of users’ experience. This paper focuses on the problem of availability evaluation of Web services and proposes a method for availability evaluation of Web services using improved grey correlation analysis with entropy difference and weight (EWGCA).This method is based on grey correlation analysis, and use entropy difference to illustrate the changes of availability, set weight to quantize availability requirements of different operations or transactions in services. Through simulation experiment in high load scenarios for Web services, the experiment result shows that our method can realize hierarchical description and overall evaluation for availability of Web services accurately in the case of smaller test sample volumes or uncertain data even in the field of big data.

Pearson correlation and transfer entropy in the Chinese stock market with time delay

Correlations between two time series,including the linear Pearson correlation and the nonlinear transfer entropy,have attracted significant attention.In this work,we studied the correlations between multiple stock data with the introduction of a time delay and a rolling window.In most cases,the Pearson correlation and transfer entropy share the same tendency,where a higher correlation provides more information for predicting future trends from one stock to another,but a lower correlation provides less.Considering the computational complexity of the transfer entropy and the simplicity of the Pearson correlation,using the linear correlation with time delays and a rolling window is a robust and simple method to quantify the mutual information between stocks.Predictions made by the long short-term memory method with mutual information outperform those made only with selfinformation when there are high correlations between two stocks.

Preliminary research on the relationship between long-range correlations and predictability

By establishing the Markov model for a long-range correlated time series （LRCS） and analysing its evolutionary characteristics, this paper defines a physical effective correlation length （ECL） T, which reflects the predictability of the LRCS. It also finds that the ECL has a better power law relation with the long-range correlated exponent γ of the LRCS： T = Kexp（-γ/0.3） ＋ Y, （0 〈 γ〈 1） the predictability of the LRCS decays exponentially with the increase of γ It is then applied to a daily maximum temperature series （DMTS） recorded at 740 stations in China between the years 1960-2005 and calculates the ECL of the DMTS. The results show the remarkable regional distributive feature that the ECL is about 10-14 days in west, northwest and northern China, and about 5-10 days in east, southeast and southern China. Namely, the predictability of the DMTS is higher in central-west China than in east and southeast China. In addition, the ECL is reduced by 1-8 days in most areas of China after subtracting the seasonal oscillation signal of the DMTS from its original DMTS; however, it is only slightly altered when the decadal linear trend is removed from the original DMTS. Therefore, it is shown that seasonal oscillation is a significant component of daily maximum temperature evolution and may provide a basis for predicting daily maximum temperatures. Seasonal oscillation is also significant for guiding general weather predictions, as well as seasonal weather predictions.

Upper bound for the time derivative of entropy for a dynamical system driven by coloured cross-correlated white noises

It is shown how the cross-correlation time and strength of coloured cross-correlated white noises can set an upper bound for the time derivative of entropy in a nonequilibrium system. The value of upper bound can be calculated directly based on the Schwartz inequality principle and the Fokker-Planck equation of the dynamical system driven by coloured cross-correlated white noises. The present calculations can be used to interpret the interplay of the dissipative constant and cross-correlation time and strength of coloured cross-correlated white noises on the upper bound.

Multi-dimensional and Multi-threshold Airframe Damage Region Division Method Based on Correlation Optimization

In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance,a multi-dimensional and multi-threshold airframe damage region division method based on correlation optimization is proposed.On the basis of airframe damage feature analysis,the multi-dimensional feature entropy is defined to realize the full fusion of multiple feature information of the image,and the division method is extended to multi-threshold to refine the damage division and reduce the impact of the damage adjacent region’s morphological changes on the division.Through the correlation parameter optimization algorithm,the problem of low efficiency of multi-dimensional multi-threshold division method is solved.Finally,the proposed method is compared and verified by instances of airframe damage image.The results show that compared with the traditional threshold division method,the damage region divided by the proposed method is complete and accurate,and the boundary is clear and coherent,which can effectively reduce the interference of many factors such as uneven luminance,chromaticity deviation,dirt attachment,image compression,and so on.The correlation optimization algorithm has high efficiency and stable convergence,and can meet the requirements of aircraft intelligent maintenance.

Correlation Analysis between TCM Syndromes and Physicochemical Parameters

Traditionally, differentiation of syndromes of Traditional Chinese Medicine (TCM) mainly depends on the information obtained from four diagnosis methods. Now many physicochemical parameters are available in clinic. There exists great correlation between TCM syndromes and physicochemical parameters. The objective of the paper is to analyze the correlation between TCM syndromes and physicochemical parameters quantitatively. Correlation analysis has been widely studied and many analysis methods have been developed. Mutual information based on entropy can measure arbitrary dependence between variables. It has been applied to many kinds of fields, especially to pattern recognition. But most works are restricted to discrete variables and little work has been done to study the relation between discrete and continuous variables. A novel algorithm is proposed to calculate the mutual information between discrete and continuous variables. It is used to analyze the correlation between TCM syndromes and physicochemical parameters.

基于PCA-Entropy TOPSIS 的甘薯品种块根质构品质评价

【目的】质构品质是甘薯块根品质评价的重要指标,直接影响其鲜食和产后加工。质构品质评价是甘薯综合利用过程和品质育种的重要环节。完善甘薯块根质构品质评价体系,为其利用和育种提供参考。【方法】应用物性分析仪质地多面分析法对45个甘薯品种块根的硬度、黏附性、内聚性、弹性、胶黏性和咀嚼性进行测定,分析各质构参数间的相关性,采用主成分分析确定各个参数权重,并结合TOPSIS法对45个甘薯品种块根的质构品质进行综合评价。【结果】45个甘薯品种的质构参数均有一定差异,咀嚼性和黏附性变异系数较大,分别为35.23%和49.15%。咀嚼性变化范围为60.30—284.66 N,平均为149.29 N,浙薯13的咀嚼性最大,为284.66 N,166-7和龙薯14的咀嚼性较小,分别为60.30和77.28 N;黏附性变化范围为-10.4—-0.80 J,平均为-4.71 J,龙薯31的黏附性最大,为-1.34 J,冀紫薯2号和普薯32的黏附性较小,分别为-9.34和-10.40 J。内聚性和弹性的变异系数较小,分别为14.27%和15.75%。内聚性变化范围为0.15—0.28,平均为0.21,商薯19的内聚性最大,为0.28,红皮白心的内聚性最小,为0.15;弹性变化范围为5.01—8.93 mm,平均为6.59 mm,西农431的弹性最大,为8.93 mm,166-7的弹性最小,为5.01 mm。胶黏性变异系数为23.84%,变化范围为11.97—32.78 N,平均为22.20 N,普薯32的胶黏性最大,为32.78 N,166-7的胶黏性最小,为11.97 N;硬度变异系数为19.47%,变化范围为59.79—143.41 N,平均为105 N,绵粉1号、商徐紫1号和苏薯29的块根硬度大于140.00 N,166-7的块根硬度最小,为59.79 N。相关性分析表明,块根硬度与胶黏性、咀嚼性均呈极显著正相关,胶黏性与咀嚼性呈极显著正相关,内聚性与弹性、胶黏性、咀嚼性均呈极显著正相关,弹性与胶黏性、咀嚼性均呈极显著正相关。6个质构参数经主成分分析,被提取的3个主成分累计方差贡献率达94.674%,硬度、黏附性、内聚性、弹性、胶黏性和咀嚼性的权重分别为0.121、0.161、0.102、0.232、0.162和0.223。【结论】明确了淀粉型甘薯质构品质优良的品种为龙薯31、商薯19和冀薯982;鲜食型甘薯质构品质优良的品种为苏薯16、紫罗兰和徐薯32。

基于Entropy-Topsis模型的光伏建筑项目投资风险测评

采用Entropy-Topsis模型,从政策、经济、技术和自然环境等维度,对我国8个典型光伏建筑项目(BIPV)的投资风险水平进行评价与分析。一方面,采用Entropy法确定测评指标的客观权重;另一方面,运用Topsis方法对BIPV项目应承担风险的大小进行量化、排序,并运用灰色关联分析法诊断关键影响因素,以期为我国BIPV项目投资风险管理提供一定的参考依据。

Host markers and correlated mutations in the overlapping genes of influenza viruses: M1, M2;NS1, NS2;and PB1, PB1-F2

The influenza A viruses have three gene segments, M, NS, and PB1, which code for more than one protein. The overlapping genes from the same segment entail their interdependence, which could be reflected in the evolutionary constraints, host distinction, and co-mutations of influenza. Most previous studies of overlapping genes focused on their unique evolutionary constraints, and very little was achieved to assess the potential impact of the overlap on other biological aspects of influenza. In this study, our aim was to explore the mutual dependence in host differentiation and co-mutations in M, NS, and PB1 of avian, human, 2009 H1N1, and swine viruses, with Random Forests, information entropy, and mutual information. The host markers and highly co-mutated individual sites and site pairs (P values < 0.035) in the three gene segments were identified with their relative significance between the overlapping genes calculated. Further, Random Forests predicted that among the three stop codons in the current PB1-F2 gene of 2009 H1N1, the significance of a mutation at these sites for host differentiation was, in order from most to least, that at 12, 58, and 88, i.e., the closer to the start of the gene the more important the mutation was. Finally, our sequence analysis surprisingly revealed that the full-length PB1-F2, if the three stop codons were all mutated, would function more as a swine protein than a human protein, although the PB1 of 2009 H1N1 was derived from human H3N2.

ENTROPY IMMUNITY OF FEEDFORWARD NETWORKS

Siegenthaler’s“Correlation Immunity”concept has been improved in this paper.From practical points of view,the new concept is more powerful than the original one in avoid-ing the trade-off between“the order of correlation immunity”and“the linear complexity”of keystreams in cipher system.Bent functions are also introduced into the studies of linear approxima-tion and entropy immunity for feedforward networks.New results and new methods are presentedalso.

Upper Estimates on the Higher-dimensional Multifractal Spectrum of Local Entropy

We discuss the problem of higher-dimensional multifractal spectrum of local entropy for arbitrary invariant measures. By utilizing characteristics of a dynamical system, namely, higher-dimensional entropy capacities and higher-dimensional correlation entropies, we obtain three upper estimates on the hlgher-dimensional multifractal spectrum of local entropies. We also study the domain of higher-dimensional multifractai spetrum of entropies.

Practical Method of Estimating Standard Entropies of Cations in Solid Compounds

The standard entropy Sm of the cation in solid compound is represented by using the greatest principal quantum number (n) and electron number (m) of the highest energy level group in ground state atom. There is a high correlativity between Sm and n, m, with the coefficient of multiple correlation being 0. 993. The binary linear regres siou equation Sm = 8. 58+ 8. 03n+ 0. 33m is built up by the least square method, and proved highly effective by the F test under the significance level a= 0. 01. The correlativity between Sm and m increases with the increase of n.

Novel Fault Detection Optimization Algorithm for Single Event Effect system Based on Multi-information Entropy Fusion

Fault detection caused by single event effect( SEE) in system was studied,and an improved fault detection algorithm by fusing multi-information entropy for detecting soft error was proposed based on multi-objective detection approach and classification management method. In the improved fault detection algorithm, the analysis model of posteriori information with corresponding multi-fault alternative detection points was formulated through correlation information matrix, and the maximum incremental information entropy was chosen as the classification principle for the optimal detection points. A system design example was given to prove the rationality and feasibility of this algorithm.This fault detection algorithm can achieve the purpose of fault detection and resource configuration with high efficiency.

Dense Fractal Networks, Trends, Noises and Switches in Homeostasis Regulation of Shannon Entropy for Chromosomes’ Activity in Living Cells for Medical Diagnostics

We analyze correlations and patterns of oxidative activity of 3D DNA at DNA fluorescence in complete sets of chromosomes in neutrophils of peripheral blood. Fluorescence of DNA is registered by method of flow cytometry with nanometer spatial resolution. Experimental data present fluorescence of many ten thousands of cells, from different parts of body in each population, in various blood samples. Data is presented in histograms as frequency distributions of flashes in the dependence on their intensity. Normalized frequency distribution of information in these histograms is used as probabilistic measure for definition of Shannon entropy. Data analysis shows that for this measure of Shannon entropy common sum of entropy, i.e. total entropy E, for any histogram is invariant and has identical trends of changes all values of E (r) = lnr at reduction of rank r of histogram. This invariance reflects informational homeostasis of chromosomes activity inside cells in multi-scale networks of entropy, for varied ranks r. Shannon entropy in multi-scale DNA networks has much more dense packing of correlations than in “small world” networks. As the rule, networks of entropy differ by the mix of normal D 2 and abnormal D > 2 fractal dimensions for varied ranks r, the new types of fractal patterns and hinges for various topology (fractal dimension) at different states of health. We show that all distributions of information entropy are divided on three classes, which associated in diagnostics with a good health or dominants of autoimmune or inflammatory diseases. This classification based on switching of stability at transcritical bifurcation in homeostasis regulation. We defined many ways for homeostasis regulation, coincidences and switching patterns in branching sequences, the averages of H&ouml;lder for deviations of entropy from homeostasis at different states of health, with various saturation levels the noises of entropy at activity of all chromosomes in support regulation of homeostasis.

Traffic An o ma ly De te ctio n in Backbone Networks Using C la s s ifica tio n o f M u Itid ime n s io n a I Time Series of Entropy

Detecting traffic anomalies is essential for diagnosing attacks. HighSp eed Backbone Net works （HSBN） require Traffic Anomaly Detection Systems （TADS） which are accurate （high detec tion and low false positive rates） and efficient. The proposed approach utilizes entropy as traffic distributions metric over some traffic dimensions. An efficient algorithm, having low computational and space complexity, is used to estimate entro py. Entropy values over all dimensions are

基于Entropy-Kmeans++的尾矿库安全风险分级预警模型

针对尾矿库安全监管难度大、安全防范意识不足的问题,提出了一种基于Entropy-Kmeans++的尾矿库安全风险分级预警模型。首先,以某尾矿库为例,根据尾矿库现状确定威胁尾矿库安全的主要因素,建立适用于该尾矿库的评价指标体系;其次,运用熵权法(Entropymethod)获取各指标对应的权重信息,得到各个数据点的风险综合评分;接着,采用Kmeans++算法对风险评价结果进行聚类,得到风险评价结果的划分等级。最后运用该模型确定每个数据点对应的风险等级。结果表明:尾矿库安全风险分为低风险、较低风险、中风险、较高风险、高风险5类,该模型的评价结果与该尾矿库的实际安全情况一致,能够有效对该尾矿库的安全风险进行预警。

多向加权Tsallis熵最大化导向的自动阈值分割方法

受噪声或随机细节、目标和背景的大小比例、成像时的点扩散等不同因素的影响,许多图像的灰度直方图呈现为无模态、单模态、双模态或者多模态样式.为了在统一框架内处理这4种不同模态情形下的自动阈值选择问题,本文提出了一种多向加权Tsallis熵最大化导向的自动阈值分割方法(Multi-directional Weighted Tsallis Entropy,MWTE).基于新设计的反正切方向性卷积核的多尺度乘积效应,该方法将不同模态的灰度直方图转化为统一的单模态右偏灰度直方图.在4个不同方向上提取出这种特殊的单模态右偏灰度直方图后,通过多向加权策略构建出与原始图像灰度值紧密相关的加权Tsallis熵目标函数,并以该目标函数取最大值时对应的灰度值作为最终分割阈值.本文将提出的方法和3个阈值分割方法、1个软分割方法、1个活动轮廓分割方法以及1个自动聚类分割方法进行了比较.在4种不同模态情形下的4幅合成图像和50幅真实世界图像上的实验结果表明,本文提出的方法虽然在计算效率方面不占有优势,但它对不同模态的测试图像具有更稳健的分割适应性,且在量化分割精度所用的马修斯相关系数方面优于其他6个分割方法.

基于相关系数-熵-二维云模型的装配式建筑施工风险测度

装配式建筑施工过程要在多维空间中进行,叠加风险高,事故发生率高于传统现浇建筑施工,因此科学、准确地测度装配式建筑施工风险具有重要的现实意义。根据装配式建筑施工的特点,从人员、机械、环境、技术、管理5个维度建立了装配式建筑施工风险测度指标体系,并构建了相关系数-熵-二维云风险测度模型。实例应用结果表明:该测度模型较全面、客观、准确地反映了装配式建筑施工风险要素,能够有效实现装配式建筑施工过程风险的定量化测度,可为装配式建筑施工安全管理提供有力参考和依据。