Results 41 to 50 of about 13,159 (226)

Place Classification using Dempster-Shafer Theory

open access: yesFoundations of Computing and Decision Sciences, 2017
The paper presents a novel place labeling method. It is assumed that an indoor mobile robot equipped with a camera or RGB-D sensor ambulates an indoor environment. The places visited by the robot are classified based on objects which have been recognized.
Siemiątkowska Barbara   +1 more
doaj   +1 more source

Radar target classification using improved Dempster–Shafer theory

open access: yesThe Journal of Engineering, 2019
This study considers the problem of coarse classification of targets using multifunction radar. Several methods are available for classification such as decision trees, Dempster–Shafer, Bayes, neural networks, etc. A different approach to assign the mass
Parth Mehta   +3 more
doaj   +1 more source

The Evaluation on Development Quality of Open Education Based on Dempster-Shafer With Multigranularity Unbalanced Hesitant Fuzzy Linguistic Information for Chinese Case

open access: yesIEEE Access, 2022
Multi-granularity unbalanced hesitant fuzzy linguistic term set (MGUHFLTS) is an effective expression of linguistic information, which applied in multi-attribute group decision-making (MAGDM), meanwhile Dempster-Shafer evidence theory (DSET) is profound ...
Lili Rong
doaj   +1 more source

The Greatest Mystery of Futures Studies

open access: yesFUTURES &FORESIGHT SCIENCE, Volume 8, Issue 2, August 2026.
ABSTRACT Futures studies has long lived with a puzzle: every domain the field investigates is already studied by some special science. Three familiar replies—that futures studies extracts insights, takes a longer view, or includes lay perspectives—each capture something real but do not, on closer inspection, individuate the field at the level of its ...
Veli Virmajoki
wiley   +1 more source

A vector and geometry interpretation of basic probability assignment in Dempster‐Shafer theory

open access: yesInternational Journal of Intelligent Systems, 2020
Because of the superiority in dealing with uncertainty expression, Dempster‐Shafer theory (D‐S theory) is widely used in decision theory. In D‐S theory, the basic probability assignment (BPA) is the basis and core.
Ziyuan Luo, Yong Deng
semanticscholar   +1 more source

Trapezoidal Intuitionistic Fuzzy Multiattribute Decision Making Method Based on Cumulative Prospect Theory and Dempster-Shafer Theory

open access: yesJournal of Applied Mathematics, 2014
With respect to decision making problems under uncertainty, a trapezoidal intuitionistic fuzzy multiattribute decision making method based on cumulative prospect theory and Dempster-Shafer theory is developed.
Xihua Li, Fuqiang Wang, Xiaohong Chen
doaj   +1 more source

An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

open access: yesEnergies, 2016
The power transformer is one of the most critical and expensive components for the stable operation of the power system. Hence, how to obtain the health condition of transformer is of great importance for power utilities. Multi-attribute decision-making (
Lingjie Sun   +5 more
doaj   +1 more source

Dempster–Shafer theory framed in modal logic

open access: yesInternational Journal of Approximate Reasoning, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Elena Tsiporkova   +2 more
openaire   +2 more sources

Multi‐Model Ensembles in Ecosystem Modeling: Challenges and Best Practices for Decision‐Making

open access: yesGlobal Change Biology, Volume 32, Issue 8, August 2026.
As ecosystem models increasingly inform environmental policy, markets, and climate‐related investments, this article highlights a critical but often overlooked issue: combining multiple models does not automatically make predictions more reliable.
Kaiyu Guan   +21 more
wiley   +1 more source

Combination of Evidence in Dempster-Shafer Theory

open access: yes, 2002
Dempster-Shafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or ...
Kari Sentz, S. Ferson
semanticscholar   +1 more source

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