Results 61 to 70 of about 5,406,970 (171)

Sistem Pakar Inklusif: Diagnosis Kesulitan Belajar Siswa dengan Teori Dempster-Shafer

Edumatic
Learning difficulties are complex issues in education that require early diagnosis to support effective and inclusive learning. This study aims to develop a web-based expert system using the Dempster–Shafer theory to diagnose students’ learning ...
Sri Rahayu Ningsih, Rohminatin Rohminatin, Rizaldi Rizaldi   +2 more
doaj   +1 more source

A new model for threat assessment in data fusion based on fuzzy evidence theory

IJAIN (International Journal of Advances in Intelligent Informatics), 2016
In this paper a new method for threat assessment is proposed based on Fuzzy Evidence Theory. The most widely classical and intelligent methods used for threat assessment systems will be Evidence or Dempster Shafer and Fuzzy Sets Theories.
Ehsan Azimirad, Javad Haddadnia
doaj   +1 more source

Supervised Swin Transformer‐Based Predictive Lithological Mapping and Uncertainty Quantification Using Aeromagnetic and Gravity Data

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Lithological mapping is essential for the exploration of critical minerals supporting energy transition and national defense. Although recent advancements have incorporated multi‐source data sets and leveraged machine learning and deep learning (DL) methods, lithological mapping continues to face significant challenges, such as data imbalance,
Liang Ding, Gilles Bellefleur, Olivier Boulanger, Phuong Vo   +3 more
wiley   +1 more source

Using Dempster-Shafer Theory in Data Mining

, 2005
The origins of Dempster-Shafer theory (DST) go back to the work by Dempster (1967) who developed a system of upper and lower probabilities. Following this, his student Shafer (1976), in his book “A Mathematical Theory of Evidence” added to Dempster’s ...
Malcolm J. Beynon
core   +1 more source

Ellipsoid‐Based Interval‐Type Uncertainty Model Updating Based on Riemannian Manifold and Gaussian Process Model

International Journal of Mechanical System Dynamics, Volume 6, Issue 1, Page 140-152, March 2026.
ABSTRACT Modern engineering systems require advanced uncertainty‐aware model updating methods that address parameter correlations beyond conventional interval analysis. This paper proposes a novel framework integrating Riemannian manifold theory with Gaussian Process Regression (GPR) for systems governed by Symmetric Positive‐Definite (SPD) matrix ...
Yanhe Tao, Qintao Guo, Jin Zhou, Cheng Yi   +3 more
wiley   +1 more source

Particle filtering in the Dempster–Shafer theory [PDF]

, 2011
This paper derives a particle filter algorithm within the Dempster–Shafer framework. Particle filtering is a well-established Bayesian Monte Carlo technique for estimating the current state of a hidden Markov process using a fixed number of samples. When
Reineking, Thomas, Thomas Reineking
core   +1 more source

Interval-Valued Uncertainty Based on Entropy and Dempster–Shafer Theory

Journal of Statistical Theory and Applications (JSTA), 2018
This paper presents a new structure as a simple method at two uncertainties (i.e., aleatory and epistemic) that result from variabilities inherent in nature and a lack of knowledge.
F. Khalaj, E. Pasha, R. Tavakkoli-Moghaddam, M. Khalaj   +3 more
doaj   +1 more source

Blockchain and Digital Technologies in the Telecommunications Industry

Thunderbird International Business Review, Volume 68, Issue 2, Page 139-163, March/April 2026.
ABSTRACT This article examines how fourth industrial revolution (4IR) technologies, specifically blockchain and digital twin technologies, can be utilized to address the energy supply challenge and enhance the management of distributed telecom infrastructure assets in a research context.
Charles Okeyia, Nuno Marques de Almeida, Joe Amad‐Echendu, Simplice A. Asongu   +3 more
wiley   +1 more source

Software quality and reliability prediction using Dempster -Shafer theory [PDF]

, 2004
As software systems are increasingly deployed in mission critical applications, accurate quality and reliability predictions are becoming a necessity. Most accurate prediction models require extensive testing effort, implying increased cost and slowing ...
Guo, Lan
core   +1 more source

Instruction‐Tuned Large Language Models for Review Helpfulness Prediction: An Efficient Fine‐Tuning Framework for E‐Commerce Review Understanding

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT With the exponential growth of online reviews on e‐commerce platforms, efficiently identifying helpful reviews has become increasingly critical for supporting consumer decision‐making and mitigating information overload. The task of Review Helpfulness Prediction (RHP) aims to address this challenge by automatically filtering high‐quality and ...
Xinzhe Li, Qinglong Li, Jaekyeong Kim
wiley   +1 more source