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 ...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.展开更多
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 acc...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.展开更多
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 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%.展开更多
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 se...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.展开更多
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 significan...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.展开更多
Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this iss...Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.展开更多
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 pap...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.展开更多
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-S...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.展开更多
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 group...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.展开更多
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 th...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.展开更多
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. The...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.展开更多
Multi-source information can be utilized collaboratively to improve the performance of information retrieval. To make full use of the document and collection information, this paper introduces a new informa- tion retr...Multi-source information can be utilized collaboratively to improve the performance of information retrieval. To make full use of the document and collection information, this paper introduces a new informa- tion retrieval model that relies on the Dempster-Shafer theory of evidence. Each query-document pair is taken as a piece of evidence for the relevance between a document and a query. The evidence is combined using Dempster＇s rule of combination, and the belief committed to the relevance is obtained. Retrieved documents are then ranked according to the belief committed to the relevance. Several basic probability as- signments are also proposed. Extensive experiments over the Text REtrieval Conference （TREC） test col- lection ClueWeb09 show that the proposed model provides performance similar to that of the Vector Space Model （VSM）. Under certain probability assignments, the proposed model outperforms the VSM by 63% in terms of mean average precision,展开更多
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 measu...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.展开更多
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-conflictin...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.展开更多
When evidence comes from multiple events they should be handled independently, and it is unknown to which event a piece of evidence is related. In this paper, the problem of clustering all pieces of evidence is analyz...When evidence comes from multiple events they should be handled independently, and it is unknown to which event a piece of evidence is related. In this paper, the problem of clustering all pieces of evidence is analyzed systematically to separate them into subsets for each event on the basis of considering the describing format of evidence and making full use of the distance of evidence. An approach for evidence clustering using distance of evidence is presented based on the criterion for clustering. In the proposed approach, the method which is used to establish the initialization of clus- tering is discussed in detail, called an improved optimal distance. And the centroid vector of evidence and the clustering process are developed respectively to obtain the performance of this novel approach. Finally, an illustrative example shows that this approach is feasible and effective.展开更多
基金Shanghai Rising-Star Program(Grant No.21QA1403400)Shanghai Sailing Program(Grant No.20YF1414800)Shanghai Key Laboratory of Power Station Automation Technology(Grant No.13DZ2273800).
文摘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.
文摘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.
基金Supported by the National Key R&D Program of China(No.2017YFC1405600)the National Natural Science Foundation of China(Nos.42076197,41576032)the Major Program for the International Cooperation of the Chinese Academy of Sciences(No.133337KYSB20160002)。
文摘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%.
基金supported by the National Natural Science Foundation of China under Grant No.60903166 the National High Technology Research and Development Program of China（863 Program） under Grants No.2012AA012506,No.2012AA012901,No.2012AA012903+9 种基金 Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.20121103120032 the Humanity and Social Science Youth Foundation of Ministry of Education of China under Grant No.13YJCZH065 the Opening Project of Key Lab of Information Network Security of Ministry of Public Security（The Third Research Institute of Ministry of Public Security） under Grant No.C13613 the China Postdoctoral Science Foundation General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China under Grant No.km201410005012 the Research on Education and Teaching of Beijing University of Technology under Grant No.ER2013C24 the Beijing Municipal Natural Science Foundation Sponsored by Hunan Postdoctoral Scientific Program Open Research Fund of Beijing Key Laboratory of Trusted Computing Funds for the Central Universities, Contract No.2012JBM030
文摘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.
基金Supported by the National Natural Science Foundation of China (No. 60874105, 61174022)the Program for New Century Excellent Talents in University (No. NCET-08-0345)the Chongqing Natural Science Foundation (No. CSCT, 2010BA2003)
文摘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.
基金supported by the National Natural Science Foundation of China(61903305,62073267)the Fundamental Research Funds for the Central Universities(HXGJXM202214).
文摘Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.
基金supported by the National Natural Science Foundation of China(61272011)
文摘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.
基金jointly supported by the National Natural Science Foundation of China under Grant 61201198 and 61372089the Beijing Natural Science Foundation under Grant 4132015,4132007and 4132019
文摘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.
文摘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.
基金National Natural Science Foundation of China under Grant No.51708446
文摘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.
基金Supported by the National Natural Science Foundation of China (60772006) the Zhejiang Natural Science Foundation (R106745, Y1080422)
文摘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.
基金Supported by the Self-Directed Program of Tsinghua University (No. 2011Z01033)
文摘Multi-source information can be utilized collaboratively to improve the performance of information retrieval. To make full use of the document and collection information, this paper introduces a new informa- tion retrieval model that relies on the Dempster-Shafer theory of evidence. Each query-document pair is taken as a piece of evidence for the relevance between a document and a query. The evidence is combined using Dempster＇s rule of combination, and the belief committed to the relevance is obtained. Retrieved documents are then ranked according to the belief committed to the relevance. Several basic probability as- signments are also proposed. Extensive experiments over the Text REtrieval Conference （TREC） test col- lection ClueWeb09 show that the proposed model provides performance similar to that of the Vector Space Model （VSM）. Under certain probability assignments, the proposed model outperforms the VSM by 63% in terms of mean average precision,
基金supported by the National High Technology Research and Development Program of China(863 Program)(2013AA013801)the National Natural Science Foundation of China(61174022+4 种基金61573290)the open funding project of State Key Laboratory of Virtual Reality Technology and Systemsthe Beihang University(BUAA-VR-14KF-02)the General Research Program of Natural Science of Sichuan Provincial Department of Education(14ZB0322)the Self-financing Program of State Ethnic Affairs Commission of China(14SCZ014)
文摘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.
文摘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.
基金Supported by the National Natural Science Foundation of China (No.60772006)
文摘When evidence comes from multiple events they should be handled independently, and it is unknown to which event a piece of evidence is related. In this paper, the problem of clustering all pieces of evidence is analyzed systematically to separate them into subsets for each event on the basis of considering the describing format of evidence and making full use of the distance of evidence. An approach for evidence clustering using distance of evidence is presented based on the criterion for clustering. In the proposed approach, the method which is used to establish the initialization of clus- tering is discussed in detail, called an improved optimal distance. And the centroid vector of evidence and the clustering process are developed respectively to obtain the performance of this novel approach. Finally, an illustrative example shows that this approach is feasible and effective.
