Application of a Fuzzy Logic Model for Optimal Assessment of the Maintenance Factor Affecting Lighting in Interior Design

Imamguluyev, Rahib; Mikayilova, Rena; Salahli, Vuqar

doi:10.1007/978-981-19-2069-1_32

Cited by 15 publications

(2 citation statements)

References 11 publications

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“…In addition, the task o oading strategy can be dynamically adjusted based on real-time input data and environmental changes. It thus provides more exible and adaptive decision-making [10].…”

Section: Fuzzy Logic Reasoning Related Workmentioning

confidence: 99%

“…• When adjusting the position of defenders, it is done based on speci c conditions to optimize their layout and enhance the defensive capabilities of the swarm. As shown in formula (10), when F i ≠ F g , it typically indicates that the defenders currently situated at the edge of the swarm have perceived potential danger. To mitigate the risk of predation, these defenders will adopt strategies to gradually move closer to the center of the swarm, thereby facilitating better coordination and protection of the entire swarm.…”

Section: (3) Case2mentioning

confidence: 99%

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An Efficient FLI-KDMSSA Framework for Computing Resource Allocation of IoV in Edge Computing

Hsieh,

Xu,

Yao

2024

Preprint

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The combination of Mobile Edge Computing (MEC) and Internet of Vehicles (IoV) can effectively improve the network performance. However, the mobility of vehicles and the diversity of tasks make the allocation of computing resources more complex. When the vehicle is in motion, its position can change at any time. This can result in overload of the edge servers. Meanwhile, vehicle tasks are sensitive to latency. It makes resource allocation within edge servers more difficult. In order to solve the above problems, this article proposes a FLI-KDMSSA framework for rational allocation of computing resources in the Internet of Vehicles. First, Fuzzy Logic Inference (FLI) algorithm is used in this framework to determine the computing nodes of IoV tasks in edge computing scenarios. This algorithm uses task length, edge server virtual machine utilization, and cloud bandwidth as parameters to establish fuzzy rules. Then, with the objective function of minimizing latency and load balancing values, this paper proposes a Discrete Multi-objective Sparrow Search Algorithm based on K-means (KDMSSA) to solve the virtual machine resource allocation scheme. The experiment is simulated on the iFogSim platform. To compare with PSO algorithm, the performance of KDMSSA is improved by 12.7%. To compare with SSA, the performance of KDMSSA is improved by 7.7%.

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Section: Fuzzy Logic Reasoning Related Workmentioning

confidence: 99%

Section: (3) Case2mentioning

confidence: 99%