BP neural network-based web service selection algorithm in the smart distribution grid

A good web selection algorithm can provide the most suitable service for users. However, known for its slow convergence rate and proneness of oscillation in its learning process, the traditional error back propagation neural network algorithm cannot be applied in the service selection scenarios of a...

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Bibliographic Details
Published inThe 16th Asia-Pacific Network Operations and Management Symposium pp. 1 - 4
Main Authors Lanlan Rui, Yinglin Xiong, Ke Xiao, Xuesong Qiu
Format Conference Proceeding
LanguageEnglish
Published 01.09.2014
Subjects
Algorithm design and analysis
Convergence
error back propagation algorithm
gentle factor
Neural networks
Quality of service
smart distribution grid
Training
Uninterruptible power systems
UPS
Web services
web services selection
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Summary:A good web selection algorithm can provide the most suitable service for users. However, known for its slow convergence rate and proneness of oscillation in its learning process, the traditional error back propagation neural network algorithm cannot be applied in the service selection scenarios of actual smart distribution grid. In order to meet the requirements of telecommunication technology for smart distribution grid and improve the quality of telecommunication service, this paper proposes an improved error back propagation algorithm, in which the learning factor can be self-adjusted with every iteration. The simulation results show an optimization of the training speed and an oscillation reduction in the learning process with the new algorithm, thus obvious optimizing the web services selection in smart distribution grid.
DOI:10.1109/APNOMS.2014.6996111