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基于深度学习的基层网络数据个性化挖掘算法 被引量:6
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作者 熊蕾 彭吉琼 +1 位作者 李铭 邓伦丹 《计算机仿真》 北大核心 2022年第1期318-321,332,共5页
为提升基层网络数据挖掘精度与效率,有效应用基层网络数据提供帮助,提出基于深度学习的基层网络数据个性化挖掘算法,设计基于模糊神经网络的基层网络数据个性化挖掘算法过程,通过数据准备阶段清洗、选取及转化初始基层网络数据,得到高... 为提升基层网络数据挖掘精度与效率,有效应用基层网络数据提供帮助,提出基于深度学习的基层网络数据个性化挖掘算法,设计基于模糊神经网络的基层网络数据个性化挖掘算法过程,通过数据准备阶段清洗、选取及转化初始基层网络数据,得到高精度完整统一的待挖掘基层网络数据,划分其为训练组与测试组,构建包含输入层、模糊输入层、隐含层、模糊输出层及期望输出层的五层模糊神经网络,运用训练组基层网络数据训练该模糊神经网络,裁剪掉训练后模糊神经网络内的冗余权值规则,提取出最大权值规则,运用该规则对测试组基层网络数据实施挖掘。实验结果表明,上述算法实际应用中收敛速度较高,在训练与测试速度方面具有较大优势,可实现高精确、高查全及高重合度的精准挖掘,为基层网络数据的有效利用奠定基础。 展开更多
关键词 深度学习 模糊神经网络 基层网络数据 挖掘 网络裁剪 规则提取
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Hierarchical Scene Analysis Method for Audio Sensor Networks
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作者 Li Qi Wang Jiteng Zhang Miao 《China Communications》 SCIE CSCD 2012年第5期108-116,共9页
Abstract: A hierarchical method for scene analysis in audio sensor networks is proposed. This meth-od consists of two stages: element detection stage and audio scene analysis stage. In the former stage, the basic au... Abstract: A hierarchical method for scene analysis in audio sensor networks is proposed. This meth-od consists of two stages: element detection stage and audio scene analysis stage. In the former stage, the basic audio elements are modeled by the HMM models and trained by enough samples off-line, and we adaptively add or remove basic ele- ment from the targeted element pool according to the time, place and other environment parameters. In the latter stage, a data fusion algorithm is used to combine the sensory information of the same ar-ea, and then, a role-based method is employed to analyze the audio scene based on the fused data. We conduct some experiments to evaluate the per-formance of the proposed method that about 70% audio scenes can be detected correctly by this method. The experiment evaluations demonstrate that our method can achieve satisfactory results. 展开更多
关键词 audio sensor network audio surveil-lance audio scene analysis
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