网络数字媒体重构资源动态分配方法

Hongyan Ren, Yan Yang
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引用次数: 0

摘要

随着新媒体和网络信息技术的不断发展,需要越来越多的网络数字媒体的可重构资源来构建网络空间的可重构资源配置模型。基于多源特征融合聚类分析的网络数字媒体可重构资源动态分配方法具有一定的可行性。结合特征提取结果,实现了可重构资源的动态分配。研究网络数字媒体的可重构资源分配方法,对提高网络资源的利用能力具有重要意义。传统方法中,动态网络可重构数字媒体资源分配方法主要有基于特征相关性分析的动态分配方法、PCA主成分分析的动态分配方法和融合k均值聚类的动态分配方法等,利用统计特征提取和自相关检测,实现资源的可重构动态分配。传统的资源分配方法适应度差,特征识别能力弱,需要改变。本文主要描述了网络数字媒体可重构资源的动态配置方法,旨在加强网络数字媒体资源的配置,从而进一步提高可重构资源的动态配置能力,加快网络数字媒体的应用。
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Network digital media refactoring resource dynamic allocation method
With the continuous development of new media and network information technology, more and more reconfigurable resources of network digital media are needed to build a reconfigurable resource allocation model in network space. The dynamic allocation method of network digital media reconfigurable resources based on multi-source feature fusion cluster analysis is feasible to a certain extent. Combined with the result of feature extraction, the dynamic allocation of reconfigurable resources is realized. Research on the reconfigurable resource allocation method of network digital media is of great significance in improving the utilization capacity of network resources. Traditional method, the dynamic network reconfigurable digital media resources allocation methods mainly include dynamic allocation method based on the characteristics of correlation analysis, PCA principal component analysis method of dynamic allocation and dynamic allocation of fusion k-means clustering method and so on, USES the statistical features extraction and autocorrelation detection, realize reconfigurable dynamic allocation of resources, However, the traditional method of resource allocation has poor fitness and weak feature identification ability, so it needs to be changed. This paper mainly describes the dynamic allocation method of reconfigurable resources of network digital media, aiming at strengthening the allocation of network digital media resources, so as to further improve the dynamic allocation ability of reconfigurable resources and speed up the application of network digital media.
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发文量
12
审稿时长
20 weeks
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