Research on Intelligent Optimization of Fiber Bragg Grating Filter and Raman Fiber Amplifier in DWDM System [PDF]
, 2016 随着网络化大数据时代的到来，互联网应用和数据通讯业务的日益剧增，对通信网络的传输容量、速率和带宽提出了更高的需求。为了适应光纤通信系统对高速、大容量、超长距离的传输要求，密集波分复用（DWDM）技术成为一种能够有效挖掘和扩充光纤网络带宽资源并被广泛应用的技术方案。DWDM系统中新型器件的研究和开发进一步推动了光纤传输系统性能的提升。多信道光滤波技术和全波长光放大技术是DWDM突破网络容量瓶颈的两项最核心的技术支撑。其中，多信道光纤布拉格光栅（FBG ...
陈静
core
Location Detection of False Data Injection Attacks in Power Grid Based on Improved Deep Extreme Learning Machine [PDF]
ObjectivesPower systems are facing threats of false data injection attacks. Existing detection methods for false data injection attacks have the problems of insufficient feature learning ability and slow detection speed, making it difficult to locate ...
DONG Lu +3 more
core +1 more source
Gaoya dianqi, 2020 目前变压器绕组应变监测主要分为离线检测和在线检测,由于受现场复杂电磁环境的干扰,在线检测并未得到广泛应用,离线检测虽技术较为成熟,但无法准确判断绕组应变形式。基于以上问题,文中提出了基于分布式光纤传感的变压器绕组应变检测方法,并提出了基于S变换和极限学习机（ELM）的绕组应变识别方法。首先模拟变压器运行过程中绕组可能出现的变形形式,采集相应的布里渊频移;然后通过S变换对应变信号进行时频分析,提取变换后的时频特征量作为神经网络的输入样本,采用极限学习机（ELM）进行训练识别。实验分析表明 ...
刘云鹏, 步雅楠, 贺鹏, 田源
doaj
Research on Compensation Technology of Pressure Sensor Based on Machine Learning and Intelligent Optimization Algorithm [PDF]
, 2017 微机电系统（MicroElectroMechanicalSystem，MEMS）拥有功耗低、灵敏度高、体积小、制造标准化程度高以及性价比高等突出优势，基于MEMS制造工艺的压阻式压力传感器被广泛应用于汽车、航空、石油石化及消费电子的压力测量环节。伴随社会工业化水平的不断发展，对相应工业过程的压力测量性能也日趋严格。环境温度和静压压力作为全面影响高精度MEMS压力传感器整体测量特性的两个关键因素，已然成为压阻式压力传感器在高精度测量领域更进一步的瓶颈。 针对上述问题 ...
李冀
core
Study on wine quality evaluation based on extreme learning machine improved by whale optimization algorithm [PDF]
[Objective] In order to solve the issue of excessive redundant information in near-infrared spectroscopy, enhance the accuracy of wine quality evaluation models, a rapid and non-destructive method was established for wine quality evaluation.
DOU Li, LI Baiqiu, LI Fei, ZHENG Wei
core +1 more source
Fault Diagnosis Method of Wind Turbines Based on Wide Deep Convolutional Neural Network With Resampling and Principal Component Analysis [PDF]
, 2023 Fault diagnosis of wind turbines suffers from less training data and noises. A method based on wide deep convolutional neural network with resampling and principal component analysis was presented for the diagnosis of mechanical faults (that is the main ...
BAO Yanyang, LI Dazi, LIU Zhan
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He jishu随着高能核物理研究进入多维度、高复杂度数据分析阶段，深度学习技术正逐步成为理解极端条件下核物质行为的关键工具，并推动研究范式从经验驱动向数据驱动的根本转变。本文简要梳理了机器学习在该领域的演进，并着重介绍了深度学习方法在其中的前沿进展：早期（20世纪末至21世纪10年代）研究主要采用人工神经网络和支持向量机等传统算法，通过核质量预测、相变识别等任务验证了机器学习处理核物理问题的可行性，但受限于人工特征提取和计算能力的制约，尚未触及物理特征的自主挖掘；深度学习时代（21世纪10年代至今 ...
张 靖宗 +4 more
doaj +1 more source
Reconstruction of Temperature Distribution in Acoustic Tomography Based on Robust Regularized Extreme Learning Machine [PDF]
ObjectivesAcoustic tomography, as a non-invasive temperature detection technology, holds significant value in industrial process monitoring. However, it is constrained by insufficient spatial resolution caused by ill-posed inversion and sensitivity to ...
DONG Xianghu, ZHANG Lifeng
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Survey of research on application of heuristic algorithm in machine learning [PDF]
, 2019 Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling ...
Chunhua WU +3 more
core +1 more source
Online blind equalization algorithm with echo state network based on prediction principle [PDF]
, 2020 In view of the nonlinear channel,the online blind equalization algorithm with echo state network was proposed based on prediction principle.In the proposed algorithm,the traditional linear prediction error filter was replaced by the ESN with good ...
Aonan ZHAO +4 more
core +1 more source