Symbiotic Combination of a Bayesian Network and Fuzzy Logic to Quantify the QoS in a VANET: Application in Logistic 4.0

Khalfaoui, Hafida; Azmani, Abdellah; Farchane, Abderrazak; Safi, Saïd

doi:10.3390/computers12020040

Cited by 5 publications

(4 citation statements)

References 25 publications

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“…When Mamdani relies on the defuzzification process for fuzzy outputs, Sugeno calculates the result values through a weighted average. (Bian & Zhang, 2009;Khalfaoui et al, 2023). In this study, the use of Sugeno method is chosen in order to have less processing time, enabling the generation of conditional probabilities with only the first two steps.…”

Section: Fuzzy Logicmentioning

confidence: 99%

Burnout: A Pervasive Challenge Threatening Workplace Well-Being and Organizational Success

Bouhsaien,

Azmani

2024

J. Professional Business Review

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Objective: This study aims to tackle the increasing prevalence of employee burnout by introducing a novel hybrid methodology employing Bayesian networks and fuzzy logic. This approach seeks to identify and address burnout risks comprehensively. Theoretical Framework: Drawing from burnout theories alongside Bayesian networks and fuzzy logic, this research establishes a robust foundation for understanding burnout complexities and evaluating the efficacy of the proposed hybrid approach. Method: The methodology encompasses a model development phase utilizing OpenMarkov and FisPro to integrate Bayesian networks and fuzzy logic. Data collection involved a multifaceted approach including surveys, expert interviews, and a thorough review of literature focusing on workload, work environment, psychology, and other pertinent factors influencing burnout. Results and Discussion: Findings indicate that burnout tends to manifest at lower levels in scenarios characterized by weak communication, high workload, and low obstacles, while it escalates in situations marked by weak communication, occasional workload spikes, and moderate obstacles, among other contributing factors. These results are analyzed within the context of the theoretical framework, emphasizing their implications for individual well-being and organizational success. Research Implications: This study provides actionable insights for companies, particularly human resources managers, to bolster employee psychological support systems and advance organizational objectives. Proactively addressing burnout risks can enhance both employee well-being and overall organizational performance. Originality/Value: By proposing a hybrid methodology that merges Bayesian networks and fuzzy logic to comprehensively tackle burnout risks, this research contributes to the existing literature. The innovative methodology and practical implications underscore the significance and applicability of this study for organizations striving to mitigate burnout within their workforce.

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Section: Fuzzy Logicmentioning

confidence: 99%

Burnout: A Pervasive Challenge Threatening Workplace Well-Being and Organizational Success

Bouhsaien,

Azmani

2024

J. Professional Business Review

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“…The tree is constructed chronologically by predicting, in the first place, the probability of an initiating event. Then, a sequence of intermediate events occurs to prevent additional risk [64].…”

Section: A Event Tree Analysismentioning

confidence: 99%

Evaluation of the Accidents Risk Caused by Truck Drivers using a Fuzzy Bayesian Approach

Benallou,

Azmani,

Azmani

2023

IJACSA

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Road accidents cause hundreds of fatalities and injuries each year; due to their size and operating features, heavy trucks typically experience more severe accidents. Many factors are likely to cause such accidents; however, statistics mainly blame human error. This paper analyses the risk of accidents for heavy vehicles, focusing on driver-related factors contributing to accidents. A model is developed to anticipate the probability of an accident by using Bayesian networks (BNs) and fuzzy logic. Three axioms were verified to validate the developed model, and a sensitivity analysis is performed to identify the factors that have the most significant influence over truck accidents. Subsequently, the result provided by the model was exploited to examine the effects of in-vehicle road safety systems in preventing road accidents via an event tree analysis. The results underlined a strong link between the occurrence of accidents and parameters related to the driver, such as alcohol and substance consumption, his driving style, and his reactivity. Similarly, unfavourable working conditions significantly impact the occurrence of accidents since it contributes to fatigue, one of the leading causes of road accidents. Also, the event tree analysis results have highlighted the importance of equipping trucks with these mechanisms.

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“…Ad hoc networks lack centralized management, which can lead to issues with congestion and prioritization of messages. This can be especially problematic in vehicular networks, where the large number of vehicles on the road and their constantly changing positions can result in a significant amount of network traffic [156]. However, there are solutions being developed to address these issues, such as using intelligent routing algorithms and prioritizing certain types of messages, such as emergency messages, to ensure timely and reliable delivery.…”

Section: Quality Of Service (Qos)mentioning

confidence: 99%

Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey

et al. 2023

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Digital twins and the Internet of Things (IoT) have gained significant research attention in recent years due to their potential advantages in various domains, and vehicular ad hoc networks (VANETs) are one such application. VANETs can provide a wide range of services for passengers and drivers, including safety, convenience, and information. The dynamic nature of these environments poses several challenges, including intermittent connectivity, quality of service (QoS), and heterogeneous applications. Combining intelligent technologies and software-defined networking (SDN) with VANETs (termed intelligent software-defined vehicular networks (iSDVNs)) meets these challenges. In this context, several types of research have been published, and we summarize their benefits and limitations. We also aim to survey stochastic modeling and performance analysis for iSDVNs and the uses of machine-learning algorithms through digital twin networks (DTNs), which are also part of iSDVNs. We first present a taxonomy of SDVN architectures based on their modes of operation. Next, we survey and classify the state-of-the-art iSDVN routing protocols, stochastic computations, and resource allocations. The evolution of SDN causes its complexity to increase, posing a significant challenge to efficient network management. Digital twins offer a promising solution to address these challenges. This paper explores the relationship between digital twins and SDN and also proposes a novel approach to improve network management in SDN environments by increasing digital twin capabilities. We analyze the pitfalls of these state-of-the-art iSDVN protocols and compare them using tables. Finally, we summarize several challenges faced by current iSDVNs and possible future directions to make iSDVNs autonomous.

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Symbiotic Combination of a Bayesian Network and Fuzzy Logic to Quantify the QoS in a VANET: Application in Logistic 4.0

Cited by 5 publications

References 25 publications

Burnout: A Pervasive Challenge Threatening Workplace Well-Being and Organizational Success

Burnout: A Pervasive Challenge Threatening Workplace Well-Being and Organizational Success

Evaluation of the Accidents Risk Caused by Truck Drivers using a Fuzzy Bayesian Approach

Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey

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