Fuzzy teaching learning based optimization approach for solving the QoS-aware web service selection problem in uncertain environments

This paper proposes a new fuzzy optimization approach for the quality of service (QoS)-aware web service selection (QWSS) problem under uncertain QoS parameters. To deal with the ambiguity phenomena of some web services’ QoS characteristics like the execution time attribute, which strongly fluctuate...

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Vydané v:	Journal of ambient intelligence and humanized computing Ročník 12; číslo 12; s. 10667 - 10697
Hlavní autori:	Seghir, Fateh, Khababa, Ghizlane
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021 Springer Nature B.V
Predmet:	Algorithms Ambiguity Artificial Intelligence Communications traffic Computational Intelligence Engineering Fuzzy systems Genetic algorithms Heuristic Internet service providers Linear programming Machine learning Methods Numbers Optimization Original Research Parameter uncertainty Probability distribution Quality of service Random variables Robotics and Automation Traffic congestion User Interfaces and Human Computer Interaction Web services QoS uncertainty Generalized trapezoidal fuzzy numbers QoS-aware web service selection Fuzzy multi-objective optimization TLBO algorithm
ISSN:	1868-5137, 1868-5145
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