Parameter estimation based on interval-valued belief structures

02/15/2014
by   Xinyang Deng, et al.
0

Parameter estimation based on uncertain data represented as belief structures is one of the latest problems in the Dempster-Shafer theory. In this paper, a novel method is proposed for the parameter estimation in the case where belief structures are uncertain and represented as interval-valued belief structures. Within our proposed method, the maximization of likelihood criterion and minimization of estimated parameter's uncertainty are taken into consideration simultaneously. As an illustration, the proposed method is employed to estimate parameters for deterministic and uncertain belief structures, which demonstrates its effectiveness and versatility.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/27/2020

Combination of interval-valued belief structures based on belief entropy

This paper investigates the issues of combination and normalization of i...
research
09/11/2018

Solving Non-identifiable Latent Feature Models

Latent feature models (LFM)s are widely employed for extracting latent s...
research
12/13/2019

An Interval-Valued Utility Theory for Decision Making with Dempster-Shafer Belief Functions

The main goal of this paper is to describe an axiomatic utility theory f...
research
01/29/2019

On the negation of a Dempster-Shafer belief structure based on maximum uncertainty allocation

Probability theory and Dempster-Shafer theory are two germane theories t...
research
11/21/2022

Real bird dataset with imprecise and uncertain values

The theory of belief functions allows the fusion of imperfect data from ...
research
03/13/2013

Interval Structure: A Framework for Representing Uncertain Information

In this paper, a unified framework for representing uncertain informatio...
research
07/07/2021

Uncertainty in Ranking

Ranks estimated from data are uncertain and this poses a challenge in ma...

Please sign up or login with your details

Forgot password? Click here to reset