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基于Informer神经网络的锂离子电池容量退化轨迹预测 被引量:3
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作者 唐梓巍 师玉璞 +2 位作者 张雨禅 周奕博 杜慧玲 《储能科学与技术》 CAS CSCD 北大核心 2024年第5期1658-1666,共9页
通过对锂离子电池容量退化轨迹的精确预测可以大幅提升电池材料的研究效率。针对Transformer网络在锂电池容量退化轨迹预测这种长时间序列预测任务中存在的问题,本工作采用滑动窗口策略,构建了一种基于Informer网络的锂离子电池容量退... 通过对锂离子电池容量退化轨迹的精确预测可以大幅提升电池材料的研究效率。针对Transformer网络在锂电池容量退化轨迹预测这种长时间序列预测任务中存在的问题,本工作采用滑动窗口策略,构建了一种基于Informer网络的锂离子电池容量退化轨迹预测方法。首先,利用滑动窗口对数据集进行划分和再拼接,便于神经网络挖掘数据序列内部的相关性;然后,根据Informer网络的周期性时间特征捕捉能力设计适用于锂电池数据的全局时间戳;最后,使用前10%容量数据通过多步滚动预测方法实现模型输出,缓解预测中的误差累积问题,进而得到完整的预测轨迹。通过选取不同的误差评价指标和训练过程中的时间开销,在美国马里兰大学提供的锂电池数据集上验证了所建立模型的准确性和训练效率,并在美国航空航天局提供的电池数据集上验证了模型的泛用性。本工作模型的预测结果与多层感知机神经网络、循环神经网络及Transformer网络模型对比,退化轨迹与真实轨迹最为拟合,且训练时间开销小,预测结果的平均绝对误差和均方根误差控制在2.57%和3.5%,验证了所提预测方法的有效性。 展开更多
关键词 锂离子电池 容量退化轨迹 长时间序列预测 滑动窗口策略 Informer网络
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一种基于多尺度描述的异形粘连纤维分割方法
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作者 和英英 姚砺 万燕 《东华大学学报(自然科学版)》 CAS CSCD 北大核心 2011年第2期193-198,共6页
针对异形纤维的形状特征,在分水岭算法结果的基础上,提出一种结合多尺度描述方法标记异形粘连纤维轮廓特征点对其进行分割的方法,并采用自适应滑动窗口策略在保留正确的分割线的同时消除多余的分割线.试验结果表明,该算法能够准确分割... 针对异形纤维的形状特征,在分水岭算法结果的基础上,提出一种结合多尺度描述方法标记异形粘连纤维轮廓特征点对其进行分割的方法,并采用自适应滑动窗口策略在保留正确的分割线的同时消除多余的分割线.试验结果表明,该算法能够准确分割粘连的异形纤维. 展开更多
关键词 异形粘连纤维 分水岭算法 多尺度描述 特征点 自适应滑动窗口策略
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Fast Multi-Pattern Matching Algorithm on Compressed Network Traffic 被引量:2
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作者 Hao Peng Jianxin Li +1 位作者 Bo Li M.Hassan Arif 《China Communications》 SCIE CSCD 2016年第5期141-150,共10页
Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck ... Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s. 展开更多
关键词 compressed network traffic network security multiple pattern matching skip scanning depth of boundary
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SWFP-Miner: an efficient algorithm for mining weighted frequent pattern over data streams
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作者 Wang Jie Zeng Yu 《High Technology Letters》 EI CAS 2012年第3期289-294,共6页
Previous weighted frequent pattern (WFP) mining algorithms are not suitable for data streams for they need multiple database scans. In this paper, we present an efficient algorithm SWFP-Miner to mine weighted freque... Previous weighted frequent pattern (WFP) mining algorithms are not suitable for data streams for they need multiple database scans. In this paper, we present an efficient algorithm SWFP-Miner to mine weighted frequent pattern over data streams. SWFP-Miner is based on sliding window and can discover important frequent pattern from the recent data. A new refined weight definition is proposed to keep the downward closure property, and two pruning strategies are presented to prune the weighted infrequent pattern. Experimental studies are performed to evaluate the effectiveness and efficiency of SWFP-Miner. 展开更多
关键词 weighted frequent pattern (WFP) mining data streams data mining slidingwindow SWFP-Miner
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