Results 61 to 70 of about 12,210 (170)
Unsupervised intrusion detection model based on temporal convolutional network [PDF]
Most existing intrusion detection models rely on long short-term memory (LSTM) networks to consider time-dependencies among data. However, LSTM’s sequential data processing significantly increases computational complexity and memory consumption during ...
DING Jiawei, FENG Guanghui, LIAO Jinju
core +1 more source
Functional Ecology, Volume 40, Issue 3, Page 750-763, March 2026.Read the free Plain Language Summary for this article on the Journal blog. Abstract Forests worldwide are increasingly impacted by drought due to climate change, prompting plants to adapt through dehydration tolerance (DT) and avoidance (DA), two distinct physiological strategies.
Xingyun Liang +11 more
wiley +1 more source
基于RIME-VMD-TCN-iTransformer模型的变压器油中溶解气体含量预测
Gaoya dianqi油中溶解气体含量是评估变压器运行状态的关键指标，其发展趋势对于预防变压器故障至关重要。本文采用RIME-VMD-TCN-iTransformer组合模型预测油中溶解气体含量的发展趋势，首先采用变分模态分解算法削弱信号的非平稳特性，并通过霜冰算法进一步提升分解序列的有序性。然后采用TCN-iTransformer模型对各模态分量分别预测，最后将所有模态分量预测结果进行重构得到预测结果。研究结果指出RIME-VMD分解后的各模态分量之间没有频谱混叠现象，其能将突变型时序信号分解成为若干平稳且规律的频率分量 ...
邢超 +7 more
doaj
Marine fire pump motor bearings fault feature enhancement and diagnosis based on adaptive SSA and improved TEO [PDF]
ObjectiveThe working environment of marine fire pump motor bearings is complex with low fault diagnosis accuracy. To address these issues, this study proposes a fault feature enhancement and diagnosis method for marine fire pump motor bearings based on ...
Baozhu JIA, Xuewei SONG, Zhiqiang LIAO
core +1 more source
NEPA “Modernization”: From the Trump Administration to the Biden Administration
Review of Policy Research, Volume 43, Issue 2, March 2026.ABSTRACT Researchers have recently examined changes to American environmental policy under the Trump administration's first term, and to a lesser extent, under the Biden administration. Scholars have largely not considered changes to the National Environmental Policy Act (NEPA), one of the earliest environmental laws in the United States, and a law ...
Michelle L. Edwards
wiley +1 more source
基于多级特征提取和IHHO-KELM的变压器油中溶解气体体积分数预测
Gaoya dianqi油中溶解气体分析是变压器早期故障诊断的主要方法，准确预测未来特征气体体积分数有助于提前获取变压器的运行状态。为此提出了一种基于多级特征提取和IHHO-KELM的变压器油中溶解气体体积分数预测方法。首先，通过自适应白噪声完全集合经验模态分解将气体体积分数序列分解为多个子序列，利用奇异谱分析对子序列做进一步降噪处理，降低其非平稳性；其次，建立核极限学习机预测模型分别对各子序列进行预测，再将各子序列的预测结果叠加得到油中溶解气体体积分数的最终预测结果，并通过改进哈里斯鹰算法优化其超参数；最后，通过算例验证表明，
傅雨晨 +5 more
doaj +2 more sources
基于TVFEMD和多模型融合的变压器油中溶解气体体积分数预测方法
Gaoya dianqi油中溶解气体分析可以反映变压器的运行状态，对其体积分数精准预测可以为变压器早期故障判别和预警提供理论支撑。为此提出了一种基于时变滤波经验模态分解和多模型融合的变压器油中溶解气体体积分数预测方法。首先，通过时变滤波经验模态分解将气体体积分数序列分解为多个子序列，降低其非平稳性；其次，利用多模型融合策略，将4种不同单模型的预测结果进行融合重构，因单模型权重系数对预测结果有显著影响，利用改进黏菌算法对权重系数进行优化，以提高预测精度；最后，通过算例验证表明，相比于传统的预测模型，所提方法具有更高的预测精度 ...
曹正江, 付文龙, 文斌, 花雅文
doaj
A review of deep learning-based few sample fault diagnosis method for rotating machinery [PDF]
ObjectivesDeep learning has shown great potential in the field of rotating machinery fault diagnosis. Its excellent performance heavily relies on sufficient training samples.
Jun WU +4 more
core +1 more source
双馈风电变流器IGBT模块的损耗与结温准确计算模型及规律研究
Gaoya dianqi, 2017 为了解决交变热应力大范围波动会导致IGBT模块稳定性大幅下降,引起双馈风电变流器IGBT模块故障频发的问题,基于解析解理论以及不同损耗分析方法并结合双馈风电变流器实际运行特性,建立了IGBT模块功率损耗以及机侧、网侧结温稳态模型,并且分析了其在不同工况下的变化特性。结果表明,风速对机侧以及网侧变流器IGBT模块的功损耗以及结温变化特性影响较大,最终得到基于开关周期理论所建模型更加适用于分析IGBT模块结温以及损耗的精确模拟。双馈风电用机侧变流器IGBT稳态结温波动幅值随风速的增大而增大。
李治中, 哈立原
doaj
Fault diagnosis of marine electric thruster gearbox based on MPDCNN under strong noisy environments [PDF]
ObjectivesTo address the performance degradation in fault diagnosis of rotating machinery caused by noise interference in practical applications, a novel fault diagnosis approach based on Mel-frequency cepstral coefficients (MFCC) and a parallel dual ...
Qianming SHANG +4 more
core +1 more source