Combined conflict evidence based on twotuple iowa operators. We use the dempstershafer theory of evidence to combine optimally results obtained by content and link analyses on the web. Download book a mathematical theory of evidence in pdf format. The positive results for the bayesian approximation do not come free. Introduction the ability to group complex data into a finite number of classes is important in data mining, and means that more useful decisions can be made based on the available information. Dempstershafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. Jianwei wang, yong hu, fuyuan xiao, xinyang deng and yong deng, a novel method to use fuzzy soft sets in decision making based on ambiguity measure and dempstershafer theory of evidence. However, the counterintuitive results may be obtained when combining with highly conflicting evidence. The application of the theory hinges on the use of a rule for combining evidence from different sources. This paper reports on a largescale experiment for the evaluation of a formal querybiased combination of evidence mechanism. The analysis carried out for three different representations of statistical evidence has shown that the combination of dependent classifiers using dempsters rule.
Combination of evidence in dempstershafer theory unt. Paradox elimination in dempstershafer combination rule. To deal with such a problem, we put forward a new method based on the distance of evidence and the uncertainty measure. First, mass distributions in dempstershafer theory are obtained from the membership degrees of each pixel covering the three image components r, g and b. Measures of uncertainty in the dempstershafer theory of evidence g. Compared with bayesian theory, the dempstershafer theory of evidence feels closer to our human perception and reasoning processes. Approximations for decision making in the dempstershafer theory. Pellegrini a athe mitre corporation, burlington road, bedford, ma 01730. Gordon and others published the dempstershafer theory of evidence find, read and cite all the research you need on. Classic works of the dempstershafer theory of belief functions.
Dempstershafer evidence theory for image segmentation. Ds is a mathematical theory of evidence based on belief functions and plausible. Dempsters rule is posited as a basis for assessing the joint impact of multiple evidence. The combination rule, like the bayesian and cf combining functions, is independent of the order in. Dst is an evidence theory, it combines all possible outcomes of the problem. An application in medical diagnosis, artificial intelligence in medicine, 69, 1, 2016.
Shafer theory to combine the results obtained from individual sources to find a final unified ranking. Representation, independence, and combination of evidence in the dempstershafer theory l. The goal of the combination of imperfect information is to nd an accurate information, easily interpretable, which can resume the information set to be combined. The dempstershafer theory dst is a mathematical theory of evidence.
Its capability to assign uncertainty or ignorance to propositions is a powerful tool for dealing with. It sho wn that application of the dempstershafer rule com bination in this case leads to ev aluation of masses. A neural network classifier based on dempstershafer theory. In dempstershafer theory a numerical measure of the weight of evidence mass assignment, m is assigned to a set of hypotheses as well as individual hypotheses. On the independence requirement in dempstershafer theory for. Combining classifiers using the dempster shafer theory of evidence naseem, imran on. The limitations of the original ds combination rule and works to eliminate them are discussed in section 4. A botnet is an army of compromised computers controlled by a bot herder and used for illicit financial gain. For example, within the field of medical diagnosis, it is. A mathematical theory of evidence turns 40 glenn shafer. Dempstershafer evidence combining for antihoneypot. Approximation algorithms and decision making in the dempster.
An important aspect of this theory is the combination of evidence obtained from. Pdf can evidence be combined in the dempstershafer theory. Basic probability assignment bpa is estimated in unsupervised way using pixels fuzzy membership degrees derived from image histogram. Honeypots are network surveillance architectures designed to resemble easytocompromise computer systems. Dempstershafer is not a method that considers the evidence hypothesis by hypothesis as bayes theorem does, rather the evidence is considered in light of the hypotheses. Intrusion response with dempster shafer theory of evidence. This evidence is represented by basic belief assignments bba and pooled using the dempsters rule of combination. Handling of dependence in dempstershafer theory su. Dempstershafer evidence theory is a primary methodology for multisource information fusion since it allows to deal with uncertain information. No assumption is made about the images data distribution.
Click download or read online button to get a mathematical theory of evidence book now. K, can run into the danger of ignoring the conflicting questions and quantify it as a null set. Probability theory has a long history of representing uncertainty in a formal axiomatic way. Demonstrate the use of the dempstershafer theory of evidence in a tactical military intelligence decision aid. As a formal system, ds theory is distinguished from other uncertainty management approaches by dempster 1967, shafer 1976.
The dempstershafer theory of evidence accumulation is one of the main tools for combining data obtained from multiple sources. On the independence requirement in dempstershafer theory. An important aspect of this theory is the combination of evidence obtained from multiple sources and the modeling of. They are deployed to trap hackers in order to help security professionals capture, control, and analyze malicious internet attacks and other activities of hackers.
Advances in the dempstershafer theory of evidence book. Dempster in 1967 and his student glenn shafer in 1976. A simple view of the dempstershafer theory of evidence. Dempstershafer theory offers an alternative to traditional probabilistic theory for the. Dempstershafer theory of evidence dst 3, 10 is one of the main points of criticism this. This data fusion method is based on the idea of belief and as such can handle ignorance. You can read online a mathematical theory of evidence here in pdf, epub, mobi or docx formats.
The proposed method is composed essentially of two steps. The application of dempstershafer theory demonstrated with. Introduction in his 1976 book, glenn shafer introduced the theory of evidence, later referred to as the dempstershafer theory dst. Application of the dempstershafer theory of evidence for accident. Data classification using the dempstershafer method. If is the basic probability assignment provided by source, the combination. Dempstershafer theory, which can be regarded as a generalisation of probability theory, is a widely used formalism for reasoning with uncertain information. The dempstershafer ds evidence theory is based on the work of dempster during the 1960s and successfully1,2 extended by shafer3. The dempstershafer theory is a mathematical theory of evidencebased on belief functions and plausible reasoning, which is used to combine separate pieces of information evidence to calculate. An important aspect of this theory is the combination of evidence. In this work we focus on the relationship between the dempstershafer ds and bayesian evidence accumulation.
Bayesian theory is only concerned about single evidences. Introduction dempstershafer theory dst, also known as the theory of evidence or the theory of belief functions, was. This report surveys a number of possible combination rules for dempstershafer structures and provides examples of the implementation of these rules. In this paper, it is proposed to apply the dempstershafer theory dst or the theory of evidence to map vegetation, aquatic and mineral surfaces with a view to detecting potential areas of observation of outcrops of geological formations rocks, breastplates, regolith, etc. Dempstershafers basic probability assignment based on. Combining classifiers using the dempster shafer theory of. A new adaptive pattern classifier based on the dempstershafer theory of evidence is presented. Zadeh compufer science division, universify of california, berkeley, california 94720 the emergence of expert systems as one of the major ar. Conflicting evidence combination based on uncertainty. In this paper, an image segmentation method based on dempstershafer evidence theory is proposed. Dempstershafer evidence theory is widely used in many fields of information fusion.
Evidence combination from an evolutionary game theory. Pdf dempstershafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. A mathematical theory of evidence download ebook pdf. June 7, 2016 abstract the book that launched the dempstershafer theory of belief functions. As a tool to manipulate an uncertain environment, dempstershafer ds evidence theory is an established system for uncertainty management 4,5. On the independence requirement in dempstershafer theory for combining classifiers providing statistical evidence. Hong j 2000 reinvestigating dempsters idea of evidence combination. Shafers book contains a wealth of significant results, and is a must for anyone who wants to do serious research on problems relating to the rules of combination of evidence in expert systems. The dempstershafer ds theory of evidence 1,2,3,4,5,6,7 was introduced by dempster and shafer 8. Dempstershafer evidence theory and study of some key. This method uses reference patterns as items of evidence regarding the class membership of each input pattern under consideration. Combining classifiers using the dempster shafer theory of evidence.
Pdf the dempstershafer theory of evidence researchgate. This theory is being released because of following reason. Application of dempstershafer theory in fault diagnosis. Dempstershafer theory, data classification, dempsters rule of combination. This report surveys a number of possible combination rules for dempstershafer structures and provides examples of the implementation of these rules for discrete and intervalvalued data. The dempstershafer ds theory of evidence suggests a coherent approach to aggregate evidence bearing on groups of mutually exclusive hypotheses. In the 1960s and 1970s a number of new formalisms for handling uncertainty were developed, including certainty factors, the dempstershafer theory of evidence, fuzzy logic, and fuzzy set theory. Dempstershafer evidence combination rule and weighted dempstershafer evidence combination rule are generalized forms of the classic bayesian inference method. Extended dempstershafer theory of evidence the dempstershafer mathematical theory of evidences is both a theory of evidence and a theory of probable reasoning. Pdf combination of evidence in dempstershafer theory. Dempstershafer method, especially the weighted dempstershafer method, is suitable for sensor fusion tasks in contextsensing architectures with highly dynamic sensor configurations. An important aspect of this theory is the combination of evidence obtained from multiple sources and the modeling of conflict between them. Ds evidence theory is an uncertainty reasoning method and it decomposes the entire problem into several subproblems, sub evidences, and then uses the evidence combination rule to get the solution of the. By bridging fuzzy logic and probabilistic reasoning, the theory of belief functions.
Each is represented by a belief function, and two belief functions are merged via a combination rule to yield a new function. Focusing versus updating in belief function theory d. Dempstershafer theory, dst, mathematical theory of evidence, belief functions. Data classification using the dempstershafer method arxiv. Combination of evidence in dempster shafer theory sandia. Furthermore, the combination of two mass functions requires. A case of combination of evidence in the dempstershafer. Download pdf a mathematical theory of evidence free. Dempstershafer theory allows one to specify a degree of ignorance in this situation instead of being forced to supply prior probabilities that add to unity. Combination of evidence in dempstershafer theory core. A simple view of the dempstershafer theory of evidence and its implication for the rule of combination lotfi a.
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