Results 61 to 70 of about 1,878 (184)
Predictive processing's flirt with transcendental idealism
Noûs, Volume 60, Issue 1, Page 87-109, March 2026.Abstract The popular predictive processing (PP) framework posits prediction error minimization (PEM) as the sole mechanism in the brain that can account for all mental phenomena, including consciousness. I first highlight three ambitions associated with major presentations of PP: (1) Completeness (PP aims for a comprehensive account of mental phenomena)
Tobias Schlicht
wiley +1 more source
Indistinguishability relations in Dempster–Shafer theory of evidence
International Journal of Approximate Reasoning, 2004 Each theory or model implicitly defines its inherent notion of equality for the objects in question. In turn, this equality, and its counterpart, the mathematical concept of equivalence, provides the basis on which to establish classification mechanisms for the domain at hand.
Hernandez, E, Recasens Ferrés, Jorge
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Energies, 2020 To effectively predict the rolling bearing fault under different working conditions, a rolling bearing fault prediction method based on quantum particle swarm optimization (QPSO) backpropagation (BP) neural network and Dempster−Shafer evidence ...
Lanjun Wan +3 more
doaj +1 more source
Omni Geometry Representation Learning Versus Large Language Models for Geospatial Entity Resolution
Transactions in GIS, Volume 30, Issue 1, February 2026.ABSTRACT The development, integration, and maintenance of geospatial databases rely heavily on efficient and accurate matching procedures of Geospatial Entity Resolution (ER). While resolution of points‐of‐interest (POIs) has been widely addressed, resolution of entities with diverse geometries has been largely overlooked.
Kalana Wijegunarathna +2 more
wiley +1 more source
An improved CoCoSo framework under hesitancy and inconsistency: application in influencer selection
Journal of Business Economics and ManagementInfluencer marketing has become a core component of digital advertising, yet selecting the most suitable influencer remains a complex multi-criteria problem.
James J. H. Liou, Thanh Tuong Vo
doaj +1 more source
Rare Metals, Volume 45, Issue 1, January 2026.ABSTRACT High‐entropy alloys (HEAs) have emerged as a transformative class of materials distinguished by their complex chemical compositions, unique microstructures, and remarkable mechanical and functional properties. Traditionally, the discovery and optimization of HEAs have relied on conventional methods, including trial‐and‐error experimentation ...
Chrispin Ouko Zamzu +2 more
wiley +1 more source
Assessing the Usefulness of Assurance Cases: Experience With the Large Hadron Collider
Systems Engineering, Volume 29, Issue 1, Page 99-113, January 2026.ABSTRACT Assurance cases (ACs) are structured arguments designed to show that a system is sufficiently reliable to function properly in its operational environment. They are mandated by safety standards and are largely used in industry to support risk management for systems; however, ACs often contain proprietary information and are not publicly ...
Torin Viger +7 more
wiley +1 more source
On (Anti)Conditional Independence in Dempster-Shafer Theory
CoRR, 1998 This paper verifies a result of {Shenoy:94} concerning graphoidal structure of Shenoy's notion of independence for Dempster-Shafer theory of belief functions. Shenoy proved that his notion of independence has graphoidal properties for positive normal valuations.
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Fault detection in an engine by fusing information from multivibration sensors
International Journal of Distributed Sensor Networks, 2017 Fault detection based on the vibration signal of an engine is an effective non-disassembly method for engine diagnosis because a vibration signal includes a lot of information about the condition of the engine.
Ruili Zeng +4 more
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ConvNet and Dempster-Shafer Theory for Object Recognition [PDF]
, 2019 We propose a novel classifier based on convolutional neural network (ConvNet) and Dempster-Shafer theory for object recognition allowing for ambiguous pattern rejection, called the ConvNet-BF classifier. In this classifier, a ConvNet with nonlinear convolutional layers and a global pooling layer extracts high-dimensional features from input data.
Zheng Tong, Philippe Xu, Thierry Denoeux
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