A Heterogeneous Information Fusion Method for Maritime Radar and AIS Based on D-S Evidence Theory

Maritime radar and automatic identification systems (AIS), which are essential auxiliary equipment for navigation safety in the shipping industry, have played significant roles in maritime safety supervision. However, in practical applications, the information obtained by a single device is limited, and it is necessary to integrate the information of maritime radar and AIS messages to achieve better recognition effects. In this study, the D-S evidence theory is used to fusion the two kinds of heterogeneous information: maritime radar images and AIS messages. Firstly, the radar image and AIS message are processed to get the targets of interest in the same coordinate system. Then, the coordinate position and heading of targets are chosen as the indicators for judging target similarity. Finally, a piece of D-S evidence theory based on the information fusion method is proposed to match the radar target and the AIS target of the same ship. Particularly, the effectiveness of the proposed method has been validated and evaluated through several experiments, which proves that such a method is practical in maritime safety supervision.

From Black Holes to Information Erasure: Uniting Bekenstein’s Bound and Landauer’s Principle

This research aims to integrate Bekenstein’s bound and Landauer’s principle, providing a unified framework to understand the limits of information and energy in physical systems. By combining these principles, we explore the implications for black hole thermodynamics, astrophysics, astronomy, information theory, and the search for new laws of nature. The result includes an estimation of the number of bits stored in a black hole (less than 1.4 × 1030 bits/m3), enhancing our understanding of information storage in extreme gravitational environments. This integration offers valuable insights into the fundamental nature of information and energy, impacting scientific advancements in multiple disciplines.

Application of evidence theory in information fusion of multiple sources in bayesian analysis

How to obtain proper prior distribution is one of the most critical problems in Bayesian analysis. In many practical cases, the prior information often comes from different sources, and the prior distribution form could be easily known in some certain way while the parameters are hard to determine. In this paper, based on the evidence theory, a new method is presented to fuse the information of multiple sources and determine the parameters of the prior distribution when the form is known. By taking the prior distributions which result from the information of multiple sources and converting them into corresponding mass functions which can be combined by Dempster-Shafer (D-S) method, we get the combined mass function and the representative points of the prior distribution. These points are used to fit with the given distribution form to determine the parameters of the prior distribution. And then the fused prior distribution is obtained and Bayesian analysis can be performed. How to convert the prior distributions into mass functions properly and get the representative points of the fused prior distribution is the central question we address in this paper. The simulation example shows that the proposed method is effective.

A Resolution of the Black Hole Information Paradox via Transfinite Set Theory

A black hole is essentially a relativistic as well as a quantum object. Therefore the information paradox of black holes is a consequence of the clash between these two most fundamental theories of modern physics. It is logical to conclude that a resolution of the problem requires some form of a quantum gravity theory. The present work proposes such a resolution using set theory and pointless spacetime geometry.

On Implicit Information Translation of Shakespeare' s Works from the Perspective of Relevance Theory:In the Case of Zhu' s Translation and Liang' s Translation

The Relevance Theory put forward by Sperber and Wilson not only gives rise to a new research on pragmatics, but also provides a new theoretic foundation for other disciplines. Gutt applies the theory to translation and gives a relevance-theoretic account of translation. The relevance-theoretic communicative model provides rational explanation for existence of the implicit information. The appropri ate treatment of the implicit information is consistent with readers' cognitive environment and expectation. Human communication de pends on not only the text, but also the inferential context. The adequate contextual effect is derived from the correct judgment and infer ence of the implicit information in communication. Therefore, the translator should match the original author' s intention with target text readers' expectation to make sure that they yield adequate contextual effects with appropriate processing efforts. Implicitness is one of the features of Shakespeare' s works. It is more demanding for the translators to catch and transfer to the target readers the implicit information. Zhu Shenghao and Liang Shiqiu, the two famous translators adopt different translation strategies to deal with the implicit information in the works.

基于加权D-S证据理论的旋翼故障诊断

旋翼作为直升机的升力面和操作面,其健康状态对直升机的安全至关重要。旋翼故障诊断技术仍是直升机健康与使用监测系统(Health and usage monitoring system, HUMS)领域的薄弱环节,开发旋翼故障诊断技术具有重要价值。基于信息融合技术,首先分析了旋翼故障的诊断机理,建立了旋翼故障模型,通过流固耦合仿真获取了不同故障下桨叶、轮毂和机身的故障特征信息,生成数据集进行网络训练和验证。然后,利用遗传算法反向传播(Genetic algorithm-backpropagation, GA-BP)优化神经网络诊断3种类型的直升机旋翼故障,即后缘调整片误调、变距拉杆误调和桨叶质量不平衡。3个逐级神经网络分别对旋翼故障类型、故障位置和故障程度进行了诊断识别。最后采用加权的Dempster-Shafer(D-S)证据理论对旋翼故障进行诊断和分析。结果证明基于改进D-S证据理论的旋翼故障诊断方法能够成功应用到旋翼故障诊断中,并具有良好的识别效果。

Information Theory of Cartography:An Information-theoretic Framework for Cartographic Communication

Map is one of the communication means created by human being.Cartographers have been making efforts on the comparison of maps to natural languages so as to establish a"cartographic language"or"map language".One of such efforts is to adopt the Shannon’s Information Theory originated in digital communication into cartography so as to establish an entropy-based cartographic communication theory.However,success has been very limited although research work had started as early as the mid-1960 s.It is then found that the bottleneck problem was the lack of appropriate measures for the spatial(configurational)information of(graphic and image)maps,as the classic Shannon entropy is only capable of characterizing statistical information but fails to capture the configurational information of(graphic and image)maps.Fortunately,after over 40-year development,some bottleneck problems have been solved.More precisely,generalized Shannon entropies for metric and thematic information of(graphic)maps have been developed and the first feasible solution for computing the Boltzmann entropy of image maps has been invented,which is capable of measuring the spatial information of not only numerical images but also categorical maps.With such progress,it is now feasible to build the"Information Theory of Cartography".In this paper,a framework for such a theory is proposed and some key issues are identified.For these issues,some have already been tackled while others still need efforts.As a result,a research agenda is set for future action.After all these issues are tackled,the theory will become matured so as to become a theoretic basis of cartography.It is expected that the Information Theory of Cartography will play an increasingly important role in the discipline of cartography because more and more researchers have advocated that information is more fundamental than matter and energy.

The Counterintuitive Increase of Information Due to Extra Spacetime Dimensions of a Black Hole and Dvoretzky’s Theorem

As per Hawking and Bekenstein’s work on black holes, information resides on the surface and there is a limit on it amounting to a bit for every Planck area. It would seem therefore that extra dimensions would logically lead to a hyper-surface for a black hole and consequently a reduction of the corresponding information density due to the dilution effect of these additional dimensions. The present paper argues that the counterintuitive opposite of the above is what should be expected. This surprising result is a consequence of a well known theorem on measure concentration due to I. Dvoretzky.

基于最大信息系数法和邓熵的D-S证据理论改进

物联网中大量传感器采集的数据存在不确定性,针对D-S证据理论在处理冲突证据时融合决策结果与事实相悖的问题,文章提出一种新的基于改进D-S证据理论的多传感器数据融合算法,首先使用最大信息系数法计算证据间的可信度;然后结合信息熵对证据的不确定度进行分析,以确定新的权重;最后使用Dempster组合规则得到融合结果。算例分析表明,文章所提方法能有效融合冲突证据,较经典算法有较高的基本概率分配。将所提方法用于传感器数据处理,不仅能降低数据中存在的不确定性,还能有效处理D-S理论中的冲突问题,从而得到较为准确的融合结果。

Application of Multi-sensor Information Fusion in the Fault Diagnosis of Hydraulic System

Aiming at the problem of incomplete information and uncertainties in the diagnosis of complex system by using single parameter, a new method of multi-sensor information fusion fault diagnosis based on BP neural network and D-S evidence theory is proposed. In order to simplify the structure of BP neural network, two parallel BP neural networks are used to diagnose the fault data at first; and then, using the evidence theory to fuse the local diagnostic results, the accurate inference of the inaccurate information is realized, and the accurate diagnosis resuh is obtained. The method is applied to the fault diagnosis of the hydraulic driven servo system （HDSS） in a certain type of rocket launcher, which realizes the fault location and diagnosis of the main components of the hydraulic driven servo system, and effectively improves the reliability of the system.

Which Information Theoretic Quantity Should We Choose for Steric Analysis of Water Nanoclusters(H2O)n(n=6,32,64)?

As evidenced from recent literature,interest in employing information theory measures for understanding different properties of atomic and molecular systems is increasing tremendously.Following our earlier efforts in this field,we here evaluate the feasibility of using information theory functionals such as Fisher information,Shannon entropy,Onicescu information energy,and Ghosh-Berkowitz-Parr entropy as measures of steric effects for the steric analysis of water nanoclusters.Taking the structural isomers of water hexamers as working models and using information theoretic quantities,we show that the relative energies of water nanoclusters and the computed steric energies are related.We also show the strong effects of steric repulsion on conformational stabilities.At the same time,we have also assessed the usefulness of simultaneously considering the different information theoretic quantities,and achieved more accurate descriptions of the stability of water nanoclusters.In order to consider the effects of cluster size on the obtained results and the extent of applicability of information theoretic quantities,we have also benchmarked larger water nanoclusters with 32 and 64 units.Scrutinizing the obtained data from information theory functionals,we found that Fisher information shows the best overall performance.Our findings underline that the information theoretic quantities,especially Fisher information,can be used as quantitative measures of relative energies and consequently the order of stability of nanoclusters,which affirmed the utility of information theory for investigating various physical and chemical problems.

Riemann Hypothesis, Catholic Information and Potential of Events with New Techniques for Financial and Other Applications

In this research we are going to define two new concepts: a) “The Potential of Events” (EP) and b) “The Catholic Information” (CI). The term CI derives from the ancient Greek language and declares all the Catholic (general) Logical Propositions () which will true for every element of a set A. We will study the Riemann Hypothesis in two stages: a) By using the EP we will prove that the distribution of events e (even) and o (odd) of Square Free Numbers (SFN) on the axis Ax(N) of naturals is Heads-Tails (H-T) type. b) By using the CI we will explain the way that the distribution of prime numbers can be correlated with the non-trivial zeros of the function ζ(s) of Riemann. The Introduction and the Chapter 2 are necessary for understanding the solution. In the Chapter 3 we will present a simple method of forecasting in many very useful applications (e.g. financial, technological, medical, social, etc) developing a generalization of this new, proven here, theory which we finally apply to the solution of RH. The following Introduction as well the Results with the Discussion at the end shed light about the possibility of the proof of all the above. The article consists of 9 chapters that are numbered by 1, 2, …, 9.

改进D-S算法的多感知机器人泄漏源识别研究

危化品泄漏场域环境复杂多变,泄漏源的识别受风速、光照强度、噪声等多重因素影响,当前多以智能机器人探测,利用嗅觉或视觉进行目标识别,但单类传感器识别结果可靠性差,提出一种改进Dempster-Shafer(D-S)证据理论的识别方法,模拟人类多感官识别机制,综合处理嗅觉、视觉和听觉识别信度;通过引入参考证据获取证据源全局信息,解决了经典D-S算法中存在的证据冲突问题,并在MATLAB中进行了算例验证。结果表明,相比嗅觉、视觉和听觉单类传感器识别信度分别提高了42.5%、51.2%和38.4%;对于冲突数据,克服了经典D-S算法、Yager算法融合失效的缺陷,相比Murphy算法识别信度提高了33%,可实现泄漏源的高信度识别,融合决策可靠性好。

On Clausius, Boltzmann and Shannon Notions of Entropy

Discrete dynamical systems are given by the pair (X,f) where X is a compact metric space and f: X→X is a continuous map. During years, a long list of results have appeared to precise and understand what is the complexity of the systems. Among them, one of the most popular is that of topological entropy. In modern applications, other conditions on X and f have been considered. For example, X can be non-compact or f can be discontinuous (only in a finite number of points and with bounded jumps on the values of f or even non-bounded jumps). Such systems are interesting from theoretical point of view in Topological Dynamics and appear frequently in applied sciences such as Electronics and Control Theory. In this paper, we are reviewing the origins of the notion of entropy and studying some developing of it leading to modern notions of entropies. At the same time, we will incorporate some mathematical foundations of such old and new ideas until the appearance of Shannon entropy. To this end, we start with the introduction for the first time of the notion of entropy in thermodynamics by R. Clausius and its evolution by L. Boltzmann until the appearing in the twenty century of Shannon and Kolmogorov-Sinai entropies and the subsequent topological entropy. In turn, such notions have evolved to other recent situations where it is necessary to give some extended versions of them adapted to new problems. Of special interest is to appreciate the connexions of the notions of entropy from Boltzmann and Shannon. Since this history is long, we will not deal with the Kolmogorov-Sinai entropy or with topological entropy and modern approaches.

Quantum-Classical Algorithm for an Instantaneous Spectral Analysis of Signals:A Complement to Fourier Theory

A quantum time-dependent spectrum analysis, or simply, quantum spectral analysis (QSA) is presented in this work, and it’s based on Schrödinger’s equation. In the classical world, it is named frequency in time (FIT), which is used here as a complement of the traditional frequency-dependent spectral analysis based on Fourier theory. Besides, FIT is a metric which assesses the impact of the flanks of a signal on its frequency spectrum, not taken into account by Fourier theory and lets alone in real time. Even more, and unlike all derived tools from Fourier Theory (i.e., continuous, discrete, fast, short-time, fractional and quantum Fourier Transform, as well as, Gabor) FIT has the following advantages, among others: 1) compact support with excellent energy output treatment, 2) low computational cost, O(N) for signals and O(N2) for images, 3) it does not have phase uncertainties (i.e., indeterminate phase for a magnitude = 0) as in the case of Discrete and Fast Fourier Transform (DFT, FFT, respectively). Finally, we can apply QSA to a quantum signal, that is, to a qubit stream in order to analyze it spectrally.

Fault Isolation of Light Rail Vehicle Suspension System Based on D-S Evidence Theory and Improvement Application Case

This paper presents an innovative approach for the fault isolation of Light Rail Vehicle (LRV) suspension system based on the Dempster-Shafer (D-S) evidence theory and its improvement application case. The considered LRV has three rolling stocks and each one equips three sensors for monitoring the suspension system. A Kalman filter is applied to generate the residuals for fault diagnosis. For the purpose of fault isolation, a fault feature database is built in advance. The Eros and the norm distance between the fault feature of the new occurred fault and the one in the feature database are applied to measure the similarity of the feature which is the basis for the basic belief assignment to the fault, respectively. After the basic belief assignments are obtained, they are fused by using the D-S evidence theory. The fusion of the basic belief assignments increases the isolation accuracy significantly. The efficiency of the proposed method is demonstrated by two case studies.

Study on Power Transformers Fault Diagnosis Based on Wavelet Neural Network and D-S Evidence Theory

>Transformer faults are quite complicated phenomena and can occur due to a variety of reasons.There have been several methods for transformer fault synthetic diagnosis,but each of them has its own limitations in real fault diagnosis applications.In order to overcome those shortcomings in the existing methods,a new transformer fault diagnosis method based on a wavelet neural network optimized by adaptive genetic algorithm(AGA)and an improved D-S evidence theory fusion technique is proposed in this paper.The proposed method combines the oil chromatogram data and the off-line electrical test data of transformers to carry out fault diagnosis.Based on the fusion mechanism of D-S evidence theory,the comprehensive reliability of evidence is constructed by considering the evidence importance,the outputs of the neural network and the expert experience.The new method increases the objectivity of the basic probability assignment(BPA)and reduces the basic probability assigned for uncertain and unimportant information.The case study results of using the proposed method show that it has a good performance of fault diagnosis for transformers.

Shift, the Law of the Invention of Zero

After posing the axiom of linear algebra, the author develops how this allows the calculation of arbitrary base powers, which provides an instantaneous calculation of powers in a particular base such as base ten;first of all by developing the any base calculation of these powers, then by calculating triangles following the example of the “arithmetical” triangle of Pascal and showing how the formula of the binomial of Newton is driving the construction. The author also develops the consequences of the axiom of linear algebra for the decimal writing of numbers and the result that this provides for the calculation of infinite sums of the inverse of integers to successive powers. Then the implications of these new forms of calculation on calculator technologies, with in particular the storage of triangles which calculate powers in any base and the use of a multiplication table in a very large canonical base are discussed.

基于D-S证据理论变压器绕组机械状态评估

提出了一种基于D-S证据理论的变压器绕组机械状态评估方法。以S11-M-500/35型变压器为实际样机,绕制正常及故障绕组,分别获取绕组不同状态下的特征信息,将信息进行量化和隶属度分配,分别组建电气参量子证据和振动参量子证据评估分量,最终通过D-S综合证据理论评估模型得到变压器本体状态评估结果。通过试验得出本方法能够准确评估各相绕组当前机械状态,从而验证了本方法的准确性及可行性。

新的证据冲突衡量标准下的D-S改进算法

针对传统证据冲突衡量标准存在的不足及高冲突下Dempster证据组合规则失效的问题,通过pignistic变换,定义了新的证据冲突衡量标准,基于此,提出了一种新的D-S改进算法.该方法依据少数服从多数的决策思想,引入了描述证据重要度的权重系数,对证据进行预处理,再采用Dempster规则进行组合.通过仿真算例分析,并与其它改进方法进行对比,验证了新算法在处理证据冲突方面的性能显著改进,加快了收敛速度,同时降低了决策风险.