在智能环境中使用ANFIS和FML部署透明服务

G. Acampora, V. Loia, A. Vitiello
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引用次数: 5

摘要

本文介绍了一种基于自适应神经模糊推理系统(ANFIS)和模糊标记语言(FML)的协同方法,能够部署增强服务的智能环境的建议。具体而言,该方法实现了一种长生命周期学习策略,能够生成上下文感知服务并通过抽象技术实现它们,以最大限度地提高用户的舒适度和硬件互操作性水平。正如实验结果所显示的那样,在可用性研究中,所提出的方法能够通过自动生成最合适的可互操作服务集合来预测用户的需求,以提高用户的舒适度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using ANFIS and FML for Deploying Transparent Services in Smart Environments
This paper introduces a proposal for a smart environment capable of deploying enhanced services by using a synergic approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy Markup Language (FML). In detail, this approach realizes a long-life learning strategy able to generate context-aware services and actualize them through abstraction techniques in order to maximize the users' comfort and hardware interoperability level. As will be shown in experimental results, where a usability study has been performed, the proposed approach is capable of anticipating user's requirements by automatically generating the most suitable collection of interoperable services for improving users' comfort.
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