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摘要:
Wireless networks are key enablers of ubiquitous communication. With the evolution of networking technologies and the need for these to inter-operate and dynamically adapt to user requirements, intelligent networks are the need of the hour. Use of machine learning techniques allows these networks to adapt to changing environments and enables them to make decisions while continuing to learn about their environment. In this paper, we survey the various problems of wireless networks that have been solved using machine-learning based prediction techniques and identify additional problems to which prediction can be applied. We also look at the gaps in the research done in this area till date.
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篇名 Application of Machine-Learning Based Prediction Techniques in Wireless Networks
来源期刊 通讯、网络与系统学国际期刊(英文) 学科 医学
关键词 WIRELESS Networks Prediction Machine Learning UBIQUITOUS Communication PERVASIVE COMPUTING
年,卷(期) 2014,(5) 所属期刊栏目
研究方向 页码范围 131-140
页数 10页 分类号 R73
字数 语种
DOI
五维指标
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研究主题发展历程
节点文献
WIRELESS
Networks
Prediction
Machine
Learning
UBIQUITOUS
Communication
PERVASIVE
COMPUTING
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
通讯、网络与系统学国际期刊(英文)
月刊
1913-3715
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
763
总下载数(次)
1
总被引数(次)
0
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