测量数据的信息熵与测量误差熵研究

以Shannon信息论为基础,详细分析了测量过程的物理机制和被测量与测量结果的映射关系,建立被测量、测量误差和测量结果的信息论数学模型。研究了用信息集合和信息熵模型表征测量数据不确定度、被测量值和测量结果的方法,以及被测量信息熵、测量误差熵和测量结果信息熵的内涵、相互关系和求解方法。并推导了典型分布下传统的不确定度理论中的不确定度、置信系数与测量信息论中信息熵的数学关系,为从传统不确定度理论到测量信息论的数据处理方法过渡做了一些前期预研。

Short-term prediction of photovoltaic power generation based on LMD-EE-ESN with error correction

Considering the instability of the output power of photovoltaic(PV)generation system,to improve the power regulation ability of PV power during grid-connected operation,based on the quantitative analysis of meteorological conditions,a short-term prediction method of PV power based on LMD-EE-ESN with iterative error correction was proposed.Firstly,through the fuzzy clustering processing of meteorological conditions,taking the power curves of PV power generation in sunny,rainy or snowy,cloudy,and changeable weather as the reference,the local mean decomposition(LMD)was carried out respectively,and their energy entropy(EE)was taken as the meteorological characteristics.Then,the historical generation power series was decomposed by LMD algorithm,and the hierarchical prediction of the power curve was realized by echo state network(ESN)prediction algorithm combined with meteorological characteristics.Finally,the iterative error theory was applied to the correction of power prediction results.The analysis of the historical data in the PV power generation system shows that this method avoids the influence of meteorological conditions in the short-term prediction of PV output power,and improves the accuracy of power prediction on the condition of hierarchical prediction and iterative error correction.

一种混沌扩频码序列设计的准则

本文根据符号动力学,利用混沌系统构造了一族相互独立的Bernoulli序列作为扩频序列,给出了获得q元Bernoulli序列的一种设计准则——测度熵等于logq。

国外航空母舰主尺度与航速关系的回归分析

采用回归方法研究国外航空母舰航速和主尺度的关系。根据傅汝德数、排水量和动力的分类,分别给出国外各种类型航空母舰的航速预报经验公式,并进行方差和测量熵的分析,提出在各种情况下最佳使用公式的建议。

基于类熵距离测量的热点话题识别方法研究

网络社区热点话题识别是监测与引导网络舆情的关键问题,本文针对该问题,通过分析热点话题的属性特征和应用离差最大化、类熵距离法,计算出各属性的权重和话题的正熵、负熵及优劣度,并据此对话题进行排序,找出热点话题。最后经实证验证该方法是合理有效的,所得结果可作为政府监控网络舆情的依据。

Distributed Sampling Measurement Model in a Large-Scale High-Speed IP Networks

The distributed passive measurement is an important technology for networkbehavior research. To achieve a consistent measurement, the same packets should be sampled atdistributed measurement points. And in order to estimate the character of traffic statistics, thetraffic sample should be random in statistics. A distributed samplingmask measurement model isintroduced to tackle the difficulty of measuring the full trace of high-speed networks. The keypoint of the model is to choose some bits that are suitable to be sampling mask. In the paper, thebit entropy and bit flow entropy of IP packet headers in CERNET backbone are analyzed, and we findthat the 16 bits of identification field in IP packet header are fit to the matching field ofsampling mask. Measurement traffic also can be used to analyze the statistical character ofmeasurement sample and the randomicity of the model. At the same time the experiment resultsindicate that the model has a good sampling performance.

MEASURING STRUCTURE COMPLEXITY OF UML CLASS DIAGRAMS

To provide system designer a valid measure to evaluate the structure complexityof class diagrams objectively, this letter first proposes a method to transform a class diagramsinto a weighted class dependence graph, then presents a structure complexity measure for classdiagrams based on entropy distance.

Safety assessment of platform loadout procedures based on unascertained measures

Safety assessment of offshore platforms is an urgent task. Such assessments are now focusing on the structure, maintenance, and retirement of a platform. Some methods employed have many shortcomings. For example, they cannot make the reliability adequately explicable. Therefore, a mathematical tool, the unascertained measure, was introduced. First, the basic knowledge of the unascertained sets was introduced briefly. Second, the unascertained measure was defined and credible identification was set up. The method has been introduced into the fields for safety assessment of a jacket loadout procedure. Engineering practices showed that it can complete the safety assessment systematically and scientifically without any assumption. The work should have significance in theory and practice for offshore engineering.

An outlier recognition approach in surveying data based on information entropy

A novel outlier recognition method in surveying data is presented based on Shannon information entropy. The probability distribution of surveying data does not need to be known or hypothesized in this method, and it is not only accurate but also convenient to calculate in this method compared with statistical recognition method.

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

Generalized Maximum Fuzzy Entropy Methods with Applications on Wind Speed Data

This study is connected with new Generalized Maximum Fuzzy Entropy Methods （GMax（F）EntM） in the form of MinMax（F）EntM and MaxMax（F）EntM belonging to us. These methods are based on primary maximizing Max（F）Ent measure for fixed moment vector function in order to obtain the special functional with maximum values of Max（F）Ent measure and secondary optimization of mentioned functional with respect to moment vector functions. Distributions, in other words sets of successive values of estimated membership function closest to （furthest from） the given membership function in the sense of Max（F）Ent measure, obtained by mentioned methods are defined as （MinMax（F）Ent）m which is closest to a given membership function and （MaxMax（F）Ent）m which is furthest from a given membership function. The aim of this study consists of applying MinMax（F）EntM and MaxMax（F）EntM on given wind speed data. Obtained results are realized by using MATLAB programme. The performances of distributions （MinMax（F）En0m and （MaxMax（F）Ent）m generated by using Generalized Maximum Fuzzy Entropy Methods are established by Chi-Square, Root Mean Square Error criterias and Max（F）Ent measure.

Topological r-entropy and measure-theoretic r-entropy of a continuous map

In this paper,we introduce the concept of measure-theoretic r-entropy of a continuous map on a compact metric space,and get the results as follows:1.Measure-theoretic entropy is the limit of measure-theoretic r-entropy and topological entropy is the limit of topological r-entropy(r → 0);2.Topological r-entropy is more than or equal to the supremum of 4r-entropy in the sense of Feldman's definition,where the measure varies among all the ergodic Borel probability measures.

Quantization of black hole entropy from unstable circular null geodesics

The quasinormal mode frequencies can be understood from the massless particles trapped at the unstable circular null geodesics and slowly leaking out to infinity. Based on this viewpoint, in this paper, we semiclassically construct the entropy spectrum of the static and stationary black holes from the null geodesics. The result shows that the spacing of the entropy spectrum only depends on the property of the black hole in the eikonal limit. Moreover, for a black hole far from the extremal case, the spacing is found to be smaller than 2π for any dimension, which is very different from the result of the previous work by using the usual quasinormal mode frequencies.

Appraisal on the Regional Technological Innovation Ability Based on Unascertained Measure Method

In market economics, the regional technological innovation ability has become an important factor in the sustainable development of this region and important position in the region＇s competition. In this paper, the application of unascertained measure method in the ability of the regional technological innovation is studied. The appraisal index system is setup and the unascertained measure model is given . At last, an example is given to verify the theory model.

Uncertainty and Certainty Relations for Successive Projective Measurements of a Qubit in Terms of Tsallis' Entropies

We study uncertainty and certainty relations for two successive measurements of two-dimensional observables. Uncertainties in successive measurement are considered within the following two scenarios. In the first scenario, the second measurement is performed on the quantum state generated affer the first measurement with completely erased information. In the second scenario, the second measurement is performed on the post-first- tioned on the actual measurement outcome. Induced entropies. For two successive projective t state condiquantum uncertainties are characterized by means of the Tsallis t of a qubit, we obtain minimal and maximal values of related entropic measures of induced uncertainties. Some conclusions found in the second scenario are extended to arbitrary finite dimensionality. In particular, a connection with mutual unbiasedness is emphasized.

Empirical Study of Mean-entropy Model with the Transaction Costs in Portfolio Selection

Entropy can be as a measurement of the uncertainty and mean-entropy optimization model can help investors to make decisions in the imperfect securities market. In this paper, the transaction costs will be added to the mean-entropy model, which makes the model more rational and objective. The empirical study is done in twenty stocks of Shanghai Stock Exchange A Share to verify the model＇s feasibility and effectiveness.