Temporalized Dempster-Shafer Belief Structure in Discrimination Analysis
نویسندگان
چکیده
The analysis of Dempster-Shafer temporalized structure is performed for the construction of more precise decisions based on the expert knowledge valuations. The relation of information precision is defined on the bodies of evidence. Negative inaccuracy is defined as the stream of rational expert knowledge in DempsterShafer temporalized structure. The principle of negative inaccuracy is developed, as the maximum principle of non-specificity measure and/or Shapley information entropy of a body of evidence. Corresponding mathematical programming problem is constructed. The possibilities of modeling more precise decisions are illustrated using Discrimination Analysis. Key-Words: More precise decision-making, Dempster-Shafer temporalized belief structure, Aggregation operation, Information precision relation, Shapley entropy, Measures of non-specificity, Discrimination Analysis.
منابع مشابه
Prediction Problem’s Solution for the Finite Possibilistic Model of Expert Knowledge Streams
The solution of the prediction problem is presented for the finite possibilistic modelling [3,4,6,7]. A recurrent variant of finite possibilistic models is considered. In this variant, we define the regularization condition for constructing a quasi-optimal estimator of fuzzy transition operator (FTO). We construct the discrete recurrent extremal fuzzy process with possibilistic uncertainty, the...
متن کاملA Sensor-Based Scheme for Activity Recognition in Smart Homes using Dempster-Shafer Theory of Evidence
This paper proposes a scheme for activity recognition in sensor based smart homes using Dempster-Shafer theory of evidence. In this work, opinion owners and their belief masses are constructed from sensors and employed in a single-layered inference architecture. The belief masses are calculated using beta probability distribution function. The frames of opinion owners are derived automatically ...
متن کاملA Logical Interpretation of Dempster-Shafer Theory, with Application to Visual Recognition
We formulate Dempster Shafer Belief functions in terms of Propositional Logic, using the im plicit notion of provability underlying Demp ster Shafer Theory. The assignment of weights to the propositional literals enables the Belief functions to be explicitly computed using Net work Reliability techniques. Also, the updat ing of Belief functions using Dempster's Rule of Combination correspon...
متن کاملThe Dempster-Shafer Theory Algorithm and its Application to Insect Diseases Detection
This paper presents Dempster-Shafer Theory for insect diseases detection. Sustainable elimination of insect diseases as a public-health problem is feasible and requires continuous efforts and innovative approaches. In this research, we used Dempster-Shafer theory for detecting insect diseases and displaying the result of detection process. Insect diseases which include babesiosis, dengue fever,...
متن کاملPredicting Fault Prone Modules by the Dempster-Shafer Belief Networks
This paper describes a novel methodology for predicting fault prone modules. The methodology is based on Dempster-Shafer (D-S) belief networks. Our approach consists of three steps: First, building the Dempster-Shafer network by the induction algorithm; Second, selecting the predictors (attributes) by the logistic procedure; Third, feeding the predictors describing the modules of the current pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009