{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T15:11:50Z","timestamp":1777129910154,"version":"3.51.4"},"reference-count":40,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T00:00:00Z","timestamp":1676332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>Intelligent transportation systems use new technologies to improve road safety. In them, vehicles have been equipped with wireless communication systems called on-board units (OBUs) to be able to communicate with each other. This type of wireless network refers to vehicular ad hoc networks (VANET). The primary problem in a VANET is the quality of service (QoS) because a small problem in the services can extremely damage both human lives and the economy. From this perspective, this article makes a contribution within the framework of a new conceptual project called the Smart Digital Logistic Services Provider (Smart DLSP). This is intended to give freight vehicles more intelligence in the service of logistics on a global scale. This article proposes a model that combines two approaches\u2014a Bayesian network and fuzzy logic for calculating the QoS in a VANET as a function of multiple criteria\u2014and provides a database that helps determine the originality of the risk of degrading the QoS in the network. The outcome of this approach was employed in an event tree analysis to assess the impact of the system\u2019s security mechanisms.<\/jats:p>","DOI":"10.3390\/computers12020040","type":"journal-article","created":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T03:09:21Z","timestamp":1676430561000},"page":"40","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Symbiotic Combination of a Bayesian Network and Fuzzy Logic to Quantify the QoS in a VANET: Application in Logistic 4.0"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9408-1301","authenticated-orcid":false,"given":"Hafida","family":"Khalfaoui","sequence":"first","affiliation":[{"name":"Department of Mathematics and Informatics, Sultan Moulay Slimane University, P.O. Box 592, Beni Mellal 23000, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4975-3807","authenticated-orcid":false,"given":"Abdellah","family":"Azmani","sequence":"additional","affiliation":[{"name":"Intelligent Automation Laboratory, Abdelmalek Essaadi University, Tetouan 93000, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abderrazak","family":"Farchane","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Informatics, Sultan Moulay Slimane University, P.O. Box 592, Beni Mellal 23000, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3390-9037","authenticated-orcid":false,"given":"Said","family":"Safi","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Informatics, Sultan Moulay Slimane University, P.O. Box 592, Beni Mellal 23000, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,14]]},"reference":[{"key":"ref_1","first-page":"458","article-title":"The impact of COVID-19 on the transportation and logistics industry","volume":"19","author":"Osamede","year":"2021","journal-title":"Probl. Perspect. Manag."},{"key":"ref_2","unstructured":"Organisation for Economic Co-operation and Development (2002). Transport Logistics: Shared Solutions to Common Chalenges, OCDE."},{"key":"ref_3","first-page":"47","article-title":"Role of VANET in Logistics and Transportation","volume":"5","author":"Khaliq","year":"2017","journal-title":"Int. Grad. Sch. Dyn. 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