基于新型结构化TCNN的组合Web服务动态选择

Lei Yang, Yu Dai, Bin Zhang, Yanxiang Gao
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引用次数: 2

摘要

为了实现高质量、高性能的服务组合,提出了一种新的QoS驱动的组合Web服务动态选择方法,该方法同时考虑了QoS属性和接口参数匹配度。在进行选择时,我们意识到这个任务或多或少是一个多阶段的决策过程。基于暂态混沌神经网络高并行性能和强大的计算能力,提出了一种新的结构化暂态混沌神经网络算法。为了使该算法更适用于多阶段决策问题,我们提出了一种新的结构化神经网络来表达组合服务,而不是使用传统的神经网络,从而使所涉及的神经元最小化,并具有更高的性能。最后,通过实验可以发现,本文提出的方法比其他方法更加实用和有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic selection of composite Web services based on a new structured TCNN
In order to realize a high quality and good performance service composition, we propose new QoS driven dynamic selection of composite Web services, which takes account of both the QoS properties and interface parameter matching degree. When doing the selection, we are aware that the task is more or less a multistage decision making process. Motivated by transiently chaotic neural network high parallel performance and powerful computation ability, a new structured transiently chaotic neural network algorithm is proposed. In order to make this algorithm more adaptable for the multistage decision making problem, we propose a new structured neural network to express the composed service instead of using traditional neural networks, which minimizes the neurons involved and shows higher performance. Finally, through experimentation one can find that the method proposed in this paper is more practical and effective than others.
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