An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and uncertain.What’smore,the classicCREAMassumes that the CPCs are independent,which is unrealistic.Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation.To address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific scenarios.To address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the CPCs.The detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.

Improvement method for the combining rule of Dempster-Shaferevidence theory based on reliability

An improvement method for the combining rule of Dempster evidence theory is proposed. Different from Dempster theory, the reliability of evidences isn't identical; and varies with the event. By weight evidence according to their reliability, the effect of unreliable evidence is reduced, and then get the fusion result that is closer to the truth. An example to expand the advantage of this method is given. The example proves that this method is helpful to find a correct result.

A new oil spill detection algorithm based on Dempster-Shafer evidence theory

Features of oil spills and look-alikes in polarimetric synthetic aperture radar(SAR)images always play an important role in oil spill detection.Many oil spill detection algorithms have been implemented based on these features.Although environmental factors such as wind speed are important to distinguish oil spills and look-alikes,some oil spill detection algorithms do not consider the environmental factors.To distinguish oil spills and look-alikes more accurately based on environmental factors and image features,a new oil spill detection algorithm based on Dempster-Shafer evidence theory was proposed.The process of oil spill detection taking account of environmental factors was modeled using the subjective Bayesian model.The Faster-region convolutional neural networks(RCNN)model was used for oil spill detection based on the convolution features.The detection results of the two models were fused at decision level using Dempster-Shafer evidence theory.The establishment and test of the proposed algorithm were completed based on our oil spill and look-alike sample database that contains 1798 image samples and environmental information records related to the image samples.The analysis and evaluation of the proposed algorithm shows a good ability to detect oil spills at a higher detection rate,with an identifi cation rate greater than 75%and a false alarm rate lower than 19%from experiments.A total of 12 oil spill SAR images were collected for the validation and evaluation of the proposed algorithm.The evaluation result shows that the proposed algorithm has a good performance on detecting oil spills with an overall detection rate greater than 70%.

A Digital Evidence Fusion Method in Network Forensics Systems with Dempster-Shafer Theory

Network intrusion forensics is an important extension to present security infrastructure,and is becoming the focus of forensics research field.However,comparison with sophisticated multi-stage attacks and volume of sensor data,current practices in network forensic analysis are to manually examine,an error prone,labor-intensive and time consuming process.To solve these problems,in this paper we propose a digital evidence fusion method for network forensics with Dempster-Shafer theory that can detect efficiently computer crime in networked environments,and fuse digital evidence from different sources such as hosts and sub-networks automatically.In the end,we evaluate the method on well-known KDD Cup1999 dataset.The results prove our method is very effective for real-time network forensics,and can provide comprehensible messages for a forensic investigators.

THE COMBINATION PREDICTION OF TRANSMEMBRANE REGIONS BASED ON DEMPSTER-SHAFER THEORY OF EVIDENCE

Transmembrane proteins are some special and important proteins in cells. Because of their importance and specificity, the prediction of the transmembrane regions has very important theoretical and practical significance. At present, the prediction methods are mainly based on the physicochemical property and statistic analysis of amino acids. However, these methods are suitable for some environments but inapplicable for other environments. In this paper, the multi-sources information fusion theory has been introduced to predict the transmembrane regions. The proposed method is test on a data set of transmembrane proteins. The results show that the proposed method has the ability of predicting the transmembrane regions as a good performance and powerful tool.

Temporal evidence combination method for multi-sensor target recognition based on DS theory and IFS

In order to effectively deal with the conflict temporal evidences without affecting the sequential and dynamic characteristics in the multi-sensor target recognition(MSTR) system at the decision making level, this paper proposes a Dempster-Shafer(DS) theory and intuitionistic fuzzy set(IFS) based temporal evidence combination method(DSIFS-TECM). To realize the method,the relationship between DS theory and IFS is firstly analyzed. And then the intuitionistic fuzzy possibility degree of intuitionistic fuzzy value(IFPD-IFV) is defined, and a novel ranking method with isotonicity for IFV is proposed. Finally, a calculation method for relative reliability factor(RRF) is designed based on the proposed ranking method. As a proof of the method, numerical analysis and experimental simulation are performed. The results indicate DSIFS-TECM is capable of dealing with the conflict temporal evidences and sensitive to the changing of time. Furthermore, compared with the existing methods, DSIFS-TECM has stronger ability of anti-interference.

基于改进DS证据理论和贝叶斯网络的海运供应链风险评估

作为一个复杂的网络组织,海运供应链为全球产业链提供运输服务,在全球化大背景下,海运供应链面临众多风险与挑战,影响供应链的安全平稳运行。因此,研究其风险至关重要。针对海运供应链风险评估体系中影响因素的不确定性和专家知识推断中存在的主观性,文章提出了基于改进DS证据理论和贝叶斯网络的海运供应链风险评估模型。结果表明,海运供应链处于较高风险等级状态,其中“信息系统风险”和“外部环境风险”概率较高,需要重点关注。该模型可以从系统的角度评估海运供应链风险,切实增强风险评估工作的科学性、准确性;评估结果可为供应链上的参与者进行风险管理提供有效参考。

基于DS证据理论与综合赋权改进可拓法的黄土区重载铁路高填方路基服役性能评价

为有效评价黄土区重载铁路高填方路基的变形与稳定状态,在重载铁路高填方路基服役性能初选评价指标库基础上,通过基于证据可信度的DS证据理论融合指标的重要度、独立度与区分度3项特征值,构建重载铁路高填方路基服役性能优选指标体系;基于综合赋权改进可拓评价法,建立针对重载铁路高填方路基服役性能的多层次综合评价模型,并利用该模型对大准及巴准铁路两段高填方路基服役性能进行评价。研究结果表明,上述两段高填方路基服役性能等级评价结果依次为差与良,并均通过了有效性检验;本文研究所提方法较云模型更能准确评价高填方路基服役性能,且比《铁路路基大维修规则》更能全面客观地反映高填方路基服役性能所处状态。研究结果可为黄土区重载铁路高填方路基服役性能状态评价提供参考。

Full Diversity Reception Based on Dempster-Shafer Theory for Network Coding with Multiple-Antennas Relay

In this paper,a two-way relay system which achieves bi-directional communication via a multiple-antenna relay in two time slots is studied.In the multiple access(MA) phase,the novel receive schemes based on Dempster-Shafer(D-S) evidence theory are proposed at the relay node.Instead of traditional linear detection,the first proposed MIMO-DS NC scheme adopts D-S evidence theory to detect the signals of each source node before mapping them into network-coded signal.Moreover,different from traditional physical-layer network coding(PNC) based on virtual MIMO model,the further proposed MIMO-DS PNC comes from the vector space perspective and combines PNC mapping with D-S theory to obtain network-coded signal without estimating each source node signal.D-S theory can appropriately characterize uncertainty and make full use of multiple evidence source information by Dempster's combination rule to obtain reliable decisions.In the broadcast(BC) phase,the space-time coding(STC) and antenna selection(AS) schemes are adopted to achieve transmit diversity.Simulation results reveal that the STC and AS schemes both achieve full transmit diversity in the BC phase and the proposed MIMO-DS NC/PNC schemes obtain better end-to-end BER performance and throughputs compared with traditional schemes with a little complexity increasing and no matter which scheme is adopted in the BC phase,MIMO-DS PNC always achieves full end-to-end diversity gain as MIMO-ML NC but with a lower complexity and its throughput approaches the throughput of MIMO-ML NC in high SNR regime.

Multi-VMs Intrusion Detection for Cloud Security Using Dempster-shafer Theory

Cloud computing provides easy and on-demand access to computing resources in a configurable pool.The flexibility of the cloud environment attracts more and more network services to be deployed on the cloud using groups of virtual machines(VMs),instead of being restricted on a single physical server.When more and more network services are deployed on the cloud,the detection of the intrusion likes Distributed Denialof-Service(DDoS)attack becomes much more challenging than that on the traditional servers because even a single network service now is possibly provided by groups of VMs across the cloud system.In this paper,we propose a cloud-based intrusion detection system(IDS)which inspects the features of data flow between neighboring VMs,analyzes the probability of being attacked on each pair of VMs and then regards it as independent evidence using Dempster-Shafer theory,and eventually combines the evidence among all pairs of VMs using the method of evidence fusion.Unlike the traditional IDS that focus on analyzing the entire network service externally,our proposed algorithm makes full use of the internal interactions between VMs,and the experiment proved that it can provide more accurate results than the traditional algorithm.

基于盲源分离与改进BP-DS证据理论的生猪声音多特征融合识别

为了提高多种声音混合环境下生猪惊骇声、咳嗽声与饥饿声的识别正确率,试验采用基于盲源分离与改进BP-DS证据理论的生猪声音多特征融合识别方法对生猪混合声音识别进行研究。首先,对多个拾音器采集到的混合声音进行能量检测,排除安静环境及微弱环境噪声下声音的干扰,然后利用基于快速独立成分分析(fast independent component analysis,FastICA)的盲源分离方法对采集到的混合声音进行分离;其次,提取分离后声音信号的梅尔倒谱系数及其一阶差分、线性预测倒谱系数及其一阶差分、梅尔倒谱系数与线性预测倒谱系数的组合参数,训练3种特征参数对应的BP神经网络模型;最后,分别利用训练好的BP神经网络模型对生猪声音进行识别,通过改进DS证据理论对识别结果进行融合后输出。结果表明:研究提出的盲源分离方法分离出的生猪声音信号与生猪声音源信号的相似系数均在0.99以上,可以有效地分离生猪混合声音信号;经过多特征融合后正常环境下的识别正确率达到94.22%,较单特征的正确率有一定的提高。说明基于盲源分离与改进BP-DS证据理论的生猪声音多特征融合识别方法可以更高效地识别多种声音混合环境下的生猪声音。

基于DS-DBN多测点的工业机器人RV减速器故障诊断分析

为了提高减速器故障识别能力,融合DS证据理论和深度信念网络(DBN)设计了一种基于DS-DBN多测点的故障诊断方法,并开展实验测试验证。研究结果表明:经过30代训练后达到收敛状态,训练四个测点的DS-DBN故障诊断模型分类误差均小于5%,该方法能够快速获得全局最优参数。相比较单点测试,通过DS证据理论完成测点故障诊断融合处理后,可以将故障诊断准确率提升至接近100%的程度。该研究有助于解决工业机器人RV减速器隐藏的问题,延长使用寿命、减少经济成本。

基于Z-number和改进DS证据理论的风险评估方法

针对任务风险难度量、评估信息不确定性强等问题,提出一种Z-number和改进DS证据理论的风险评估方法。利用Z-number方法描述评估指标,得到各风险等级的初始基本概率分配(basic probability assignment,BPA);基于信度熵和皮尔逊相关系数改进DS证据理论克服悖论问题进行信息融合,确定风险的最终等级;接着,基于信息融合结果引入Joussleme距离求解专家可信度。最后,以重装空投任务为例,验证本文所提风险评估方法的合理性,并对比分析不同改进DS证据理论方法得到的结果,验证所提方法的有效性和准确性。

基于DS证据理论的极地邮轮减摇鳍选型评价

极地邮轮工作环境特殊,减摇鳍装置的选型需考虑抗低温、抗恶劣海况等在内的诸多因素,单凭主观判断很难选出最优的减摇鳍装置。为解决该问题,提出基于层次分析法(AHP)-熵权法(EWM)、三角模糊理论以及Dempster-Shafer(DS)证据融合的综合评价方法。首先构建环境适应性、装置性能等4个一级指标以及13个二级指标的选型评价指标模型,采用组合赋权法计算定性、定量指标权重;其次构建识别框架及模糊评语集,并邀请专家组对指标做出模糊评价,利用证据距离对DS证据合成策略做出改进,将修正后证据进行两两合成从而得到各方案二级指标mass函数。最后对选型方案进行综合评价,选出符合实际需求的最优减摇鳍装置。结果表明,该方法能充分考虑决策过程的不确定性,对极地邮轮减摇鳍装置选型起到科学决策的作用。

Structural damage assessment using improved Dempster-Shafer data fusion algorithm

As an efficient tool in handling uncertain issues, Dempster-Shafer evidence theory has been increasingly used in structural health monitoring and damage detection. In applications, however, Dempster-Shafer evidence theory sometimes leads to counter-intuitive results. In this study, a new fusion algorithm of evidence theory is put forward to address various counter-intuitive problems and manage the reliability difference of the evidence. The proposed algorithm comprises the following aspects:(1) Dempster's combination rule is generalized by introducing the concept of evidence ullage. The new rule allows classical Dempster's rule and can resolve counter-intuitive problems cause by evidence conflict and evidence compatibility;(2) a reliability assessing method based on a priori and posterior knowledge is proposed. Compared with conventional reliability assessment, the proposed method can reflect the actual evidence reliabilities and can efficiently reduce decision risk. Numerical examples confirm the validity and utility of the proposed algorithm. In addition, an experimental investigation on a spatial truss structure is carried out to illustrate the identified ability of the proposed approach. The results indicate that the fusion algorithm has no strict request on the accuracy and consistency of evidence sources and can efficiently enhance diagnostic accuracy.

A NEW METHOD FOR CONSTRUCTING FUZZY EVIDENCE BASED ON THE NON-CONSONANT RANDOM SET

Natural-language information is often mathematically expressed by fuzzy sets. With the random set theory as a bridge, this kind of information can be transformed into fuzzy evidence in Dempster-Shafer (DS) theory. Then Dempster's combination rule or other combination rules of evi- dence can be used perfectly for fusing natural-language and other information. However, this traditional transformation involves the use of α -cutsets to construct the focal elements which have to be repre- sented as consonant sets. This construction is very inflexible and unreasonable in some practical ap- plications. In this paper, with the desire to overcome this limitation, a method for constructing more general non-consonant focal elements is proposed based on the random set theory. Some examples are given to show the generality and the efficiency of this new method. Finally, we validate that non-consonant constructions provide less degrees of total uncertainty than that of the consonant case in these examples by using the evaluation criterion of total uncertainty.

基于DS证据理论融合油液振动多参数的故障诊断方法研究

齿轮箱广泛应用于石油化工、船舶、电力与工程机械等领域,其故障监测诊断技术研究一直是热点问题。提出了一种基于DS证据理论融合油液与振动多参数的齿轮箱故障诊断方法,针对传统单一振动信号分析方法对齿轮磨损早期不敏感的问题,采用径向基神经网络建立振动时域特征与油液特征融合的分类模型,基于高维变分自编码器自适应提取振动频域特征并完成故障分类;将由径向基神经网络与高维变分自编码器分别得到的不同证据体通过加权DS证据理论进行融合,获得最终的诊断结果。与不同融合方法进行对比,验证了该方法对齿轮故障诊断的实际效果。

A generalized evidence distance

How to efficiently measure the distance between two basic probability assignments（BPAs） is an open issue. In this paper, a new method to measure the distance between two BPAs is proposed, based on two existing measures of evidence distance. The new proposed method is comprehensive and generalized. Numerical examples are used to illustrate the effectiveness of the proposed method.

A New Fusion Method for Conflicting Evidence

A new conflicting evidence fusion method is proposed for the deficiency of Dempster's rule which can not fuse the conflicting evidence. Evidence is divided into three categories:believable evidence, non-conflicting evidence and conflicting evidence. The influences of these three categories of evidences on fusion results when discounted are analyzed respectively. On these bases, the evidence distance and the conjunctive conflict are utilized in sequence to recognize the believable evidence and non-conflicting evidence. The discounting factors of these two categories of evidences are set to one, which keeps the evidences support the true hypothesis to the greatest degree, and makes the fusion results focus onto the true hypothesis. Examples of some missile fault diagnosis show that the new method can effectively fuse the conflicting evidences, and is suited to fuse the relievable evidences. The new method improves the reliability and rationality of fusion results compared with traditional methods.

基于DS–PCA模型的包装设备滚动轴承故障诊断方法研究

目的针对包装设备长期连续工作的工作特性,对其滚动轴承的常见失效故障进行分析,提出一种基于DS–PCA模型的滚动轴承故障诊断方法,构建滚动轴承DS–PCA故障诊断模型,实现包装设备中滚动轴承的在线故障诊断。方法先运用DS证据理论对采集到的滚动轴承径向振动数据和轴向振动数据进行融合,使得信息具有整体完备性,同时对采集信号进行决策规则下的去噪处理,剔除干扰噪声信息;然后利用主成分分析法(PCA)将融合后的振动信号数据进行Q与T2的统计量计算,并通过对故障轴承振动信号的Q与T2统计量计算,确立故障时的经验阈值;最后,依据实时统计量与经验阈值对比,判断滚动轴承是否发生故障。结果通过对西储大学公开的滚动轴承试验数据分析计算,得到滚动轴承故障诊断准确率达到94%。结论该方法满足包装设备故障诊断的要求,其应用将有利于提升包装企业的生产质量和效率。