A MASS ASSIGNMENT ALGORITHM FOR DEMPSTER-SHAFER APPROACH

2014-04-25
Turhan, Hasan Ihsan
Demirekler, Mübeccel
Gunay, Melih
In this work, a new methodology is proposed for probability mass assignment to be used in Dempster-Shafer approach. The approach is developed for the cases where the prior and the current information are represented by probability density functions. Masses are assigned by comparing the prior and the current probability density functions which are assumed to be Gaussian. The proposed method is tested by artificial data and compared with the method given in [13] which is most similar to the proposed one in the literature.
22nd IEEE Signal Processing and Communications Applications Conference (SIU)

Suggestions

A Favorable Weight-Based Evolutionary Algorithm for Multiple Criteria Problems
SOYLU, Banu; Köksalan, Mustafa Murat (Institute of Electrical and Electronics Engineers (IEEE), 2010-04-01)
In this paper, we present a favorable weight-based evolutionary algorithm for multiple criteria problems. The algorithm tries to both approximate the Pareto frontier and evenly distribute the solutions over the frontier. These two goals are common for many multiobjective evolutionary algorithms. To achieve these goals in our algorithm, each member selects its own weights for a weighted Tchebycheff distance function to define its fitness score. The fitness scores favor solutions that are closer to the Pareto...
A DRBEM Approach for the STOKES Eigenvalue Problem
Tezer, Münevver; Türk, Önder (2016-07-04)
In this study, we propose a novel approach based on the dual reciprocity boundary element method (DRBEM) to approximate the solutions of various Steklov eigenvalue problems. The method consists in weighting the governing differential equation with the fundamental solutions of the Laplace equation where the definition of interior nodes is not necessary for the solution on the boundary. DRBEM constitutes a promising tool to characterize such problems due to the fact that the boundary conditions on part or all...
An interactive ranking-based multi-criteria choice algorithm with filtering: Applications to university selection
Karakaya, Gülşah (Orta Doğu Teknik Üniversitesi (Ankara, Turkey), 2019-6)
In this study, we develop an interactive algorithm to converge to the most preferred alternative of a decision maker (DM) among a set of discrete alternatives. The algorithm presents a limited number of alternatives to the DM and collects preference ranking of them iteratively. The preferences are modeled by a flexible and realistic preference function. To improve the performance, the alternatives presented are determined by a filtering method. We compare our algorithm with benchmark algorithms on nume...
A matheuristic for binary classification of data sets using hyperboxes
Akbulut, Derya; İyigün, Cem; Özdemirel, Nur Evin (null; 2018-07-08)
In this study, an optimization approach is proposed for the binary classification problem. A Mixed Integer Programming (MIP) model formulation is used to construct hyperboxes as classifiers, minimizing the number of misclassified and unclassified samples as well as overlapping of hyperboxes. The hyperboxes are determined by some lower and upper bounds on the feature values, and overlapping of these hyperboxes is allowed to keep a balance between misclassification and overfitting. A matheuristic, namely Iter...
A LINEAR MATHEMATICAL-MODEL FOR THE SEISMIC INPLANE BEHAVIOR OF BRICK MASONRY WALLS .2. DETERMINATION OF MODEL PARAMETERS THROUGH OPTIMIZATION USING EXPERIMENTAL-DATA
Sucuoğlu, Haluk; McNiven, Hugh (Wiley, 1984-01-01)
The parameters appearing in the mixture and effective modulus models proposed in Part 1 are determined through optimization by matching theoretical and experimental responses. The optimization analysis is performed in frequency space. The response quantities chosen to be matched are the complex frequency response functions (experimental and theoretical) relating the Fourier transforms of top and base accelerations of the wall. Computations in optimization analysis are carried out by introducing an object (e...
Citation Formats
H. I. Turhan, M. Demirekler, and M. Gunay, “A MASS ASSIGNMENT ALGORITHM FOR DEMPSTER-SHAFER APPROACH,” presented at the 22nd IEEE Signal Processing and Communications Applications Conference (SIU), Karadeniz Teknik Univ, Trabzon, TURKEY, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55473.