Work

Improvements proposed to noisy-OR derivatives for multi-causal analysis: A case study of simultaneous electromagnetic disturbances

Year: 2023

Type: article

Source: International Journal of Approximate Reasoning

DOI: 10.1016/j.ijar.2023.109068

Authors: Lokesh Devaraj, Qazi Mashaal Khan, Alastair R. Ruddle, Alistair P. Duffy, Richard Perdriau, Mohsen Koohestani

Institutions: Horiba (France), De Montfort University, MIRA (United Kingdom), Chalmers University of Technology, Institut d'Électronique et des Technologies du numéRique, École Supérieure d'Électronique de l'Ouest, Université Rennes 1, Université de Rennes

Language: English

Topic: Bayesian Modeling and Causal Inference

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: European Commission, Horizon 2020, H2020 Marie Skłodowska-Curie Actions

Awards: Pan-European Training, research and education network on Electromagnetic Risk management, Pan-European Training, research and education network on Electromagnetic Risk management, G434337789

OpenAlex ID: W4388312259

FWCI: 0.07

Cites: 22

Cited by: 1

Related to: 10