Multiple mental tasks classification based on nonlinear parameter of mean period using support vector machines

Mental task classification is one of the most important problems in Brain-computer interface.This paper studies the classification of five-class mental tasks.The nonlinear parameter of mean period obtained from frequency domain information was used as features for classification implemented by using the method of SVM(support vector machines).The averaged classification accuracy of 85.6% over 7 subjects was achieved for 2-second EEG segments.And the results for EEG segments of 0.5s and 5.0s compared favorably to those of Garrett's.The results indicate that the parameter of mean period represents mental tasks well for classification.Furthermore,the method of mean period is less computationally demanding,which indicates its potential use for online BCI systems.

Relationship Between Mean Length and MeanPeriod of Wind Waves

The mean wavelength of ocean waves is an important environmental parameter in ocean engineering. Owing to the difficulty in its measurement, it is usually estimated from the mean wave period according to the theoretical relationship between the two wave parameters. However, the relationships that have been proposed are not very satisfactory. In this paper, some suggestions are made for improvement of the data analysis method by which the mean wavelength is estimated from surface elevation records. Laboratory experiments are conducted in a wind-wave flume, and a new relationship between the mean wavelength and mean wave period is obtained by the application of the improved data analysis method. The new relationship deviates from that of Xu et al. （1999） while it is very close to the one proposed by Kinsman （1965）, although the last one is theoretically deficient.

Mean-square Almost Periodic Random Functions

In this paper, we present a basic theory of mean-square almost periodicity, apply the theory in random differential equation, and obtain mean-square almost periodic solution of some types stochastic differential equation.

Research on the spectral analysis and testmethod of period signals in monthly mean sea level

This paper summarizes the general methods,existing problems and their causes of the period analysis for the monthly mean sea level and points out that it is the key to the analysing period signals and forecasting the change trend of the monthly mean sea level that the periods of the signals are selected reasonably. As there are often many period signals in these series, nonlinear effects exist between pairs of period signals. In order to avoid the false periods that may be introduced due to the effects of side lobes and the periods with statistical phase significance coherence that may be introduced due to the effects of nonlinear effects and their restraint to other period signals, the maximum entropy spectral analysis and the corresponding significance period test may be performed repeatedly on the basis of the bispectrum analysis and meanwhile the most significant period component is filtered out by the least square filtering method, i. e., the method of the significance period analysis with mixed spectra modeled by a nonlinear system is adopted and the signal periods approaching the reality are selected one by one. The examples of the bispectrum analysis, the signal period analysis by mixed spectra and the fitting parameters for combined period components with linear trend in the time series of monthly mean sea level are given in this paper.

Period components in the monthly mean sea level variations in the Pacific Ocean

To study the period components in the monthly mean sea level variations in the Pacific Ocean, this paper analyses the monthly mean series of 236 tide gauge stations in the Pacific on the basis of the improved analytical method of the monthly mean sea level period signals. The results show that the oscillation periods of the sea level series are not fixed, but vary with stations. This paper also discusses the existences of the quasi-2 years atmospheric oscillation period, the 3～7 a period related to the El Nino events, sunspots, double sunspots and the 25～30 a overlength oscillation periods. The corresponding amplitudes and initial phase angles as well as the linear trend coefficient are obtained by using significant period components plus the linear trend to fit the monthly mean sea level series. A conspicuous features of the results are found,i. e.,taking 25°～30°S as the axial line in the Pacific, the annual lags gradually increase to the north and the south respectively, depicting a variation trend of partial symmetry. But in China seas, the north and south distributional trend of the annual period lags is almost opposite to those in most parts of the Pacific Ocean. In the low-latitude zone where El Nino events occur or impose more significant effects, the ratio of the sum of amplitudes of various periods within 2～7 a to the annual amplitude is equal to or more than 1. 0, while that of the sum of amplitudes of periods larger than 8 a to the annual amplitude is equal to or more than 0. 5. This suggests that the dominant role of annual amplitude in the monthly mean sea level series of this region has declined and that, correspondingly, there exist significant period components of El Nino events as well as the long-period oscillations of quasi-10 a and over 10 a. In the high-latitude zone, off China, in North America north of 40°N and the coast of Japan, the annual period oscillation occupies a dominant position in the various period components.

基于耿贝尔-线性矩和K-Means算法的短时强降水等级划分研究

短时强降水地域特点突出,致灾性强,是气象防灾减灾的重点和难点.本文基于1951—2021年国家气象观测站逐小时降水资料,采用耿贝尔—线性矩法拟合2215个国家气象观测站的1 h、3 h、6 h短时强降水的重现期分布,统计显示99%以上的国家气象观测站分布函数通过0.05显著性检验;同时,根据我国防洪标准、室外排水设计规范及中央气象台山洪预警等标准,将短时强降水按照重现期2 a、20 a、50 a、100 a划分为一般、较强、强、特强四个等级.然后,采用K-Means算法,应用耿贝尔函数的位置参数和尺度参数、短时降水的百分位值和极值等变量聚类,将我国划分为三个短时强降水区,量化了三个区的短时强降水等级并应用2019—2021年70490个区域自动观测站和国家气象观测站监测统计验证了合理性.研究成果可以满足气象业务应用需求,也为气象监测、预报预警和影响评估提供技术支撑.

Connotations and Internal Cultural Meanings of Chinese Jade in Chu Culture at Pre-Qin Period

The thesis conducts its analysis fromthe perspective of cultural characteristics of Chu state of Pre-Qin period in ancient China.The culture of Chu,usually focusing on ceremony sacrifice and several other activities,presents unique characteristics of the development of Chinese society and culture.Actually,the jade artifact at that time shows cultural features both at artistic and spiritual level and bears prominent cultural connotations like national spirit of solemnness and generosity.Chinese jade of Chu state of Pre-Qin period due to its abundant cultural connotations and meanings,poses to be an essential element of traditional Chinese culture,which shows artistic and national features of traditional jade culture and can directly influence development of modern society and culture.

百年回眸:延安时期中国共产党领导的语文运动

延安时期,中国共产党领导开展了两场影响深远的语文运动。一是新文字运动,一是语言大众化运动,都取得了举世瞩目的成就。延安时期的新文字运动,为更科学合理、更符合中国国情的文字改革做出了宝贵的探索。语言大众化运动以人民大众喜闻乐见的新鲜活泼语言作为民族语言资源来建立起具有中国作风和中国气派的语言风格,最终确立了大众语与现代汉语的话语范式,对整个20世纪的现代汉语走向产生了深远影响。

基于用电数据的潍坊市工业污染源冬奥会管控效果评估

利用潍坊市安装用电监控的工业企业在冬奥会前和会中的生产用电数据及部分企业大气污染物排放在线监测数据,分析企业生产用电量和排放量的变化特征及潜在的相关性,评估管控措施落实状况及减排效果。结果表明:管控期间,潍坊市工业企业用电量相比管控前平均下降57.96%;完全停产类企业用电量下降75%以上,大气污染物(SO_(2)、NO_(x)、烟粉尘)排放量下降100%;限产类企业用电量降幅呈现随管控措施加严而增大的趋势;延迟复产类企业延迟复产率为47.83%~96.00%,用电量下降50.76%。根据管控期间各行业企业的用电量变化状况,判定各企业基本落实了减排要求。可见,企业用电数据在一定情况下,可以替代或辅助工业企业排放数据,反映企业管控措施落实状况及减排效果。

面向扑翼飞行机器人的电子稳像算法设计

在扑翼飞行机器人的飞行过程中,由于其特有的驱动方式,机身存在周期性的俯仰和滚转运动,导致航拍视频出现抖动,影响成像效果的清晰度和稳定性.为了解决这一问题,本文提出了一种基于ORB和滑动均值滤波的电子稳像算法,用于在线消抖处理.首先,针对扑翼飞行机器人航拍图像的抖动周期与机翼扑动周期相一致的特性,设计了一种估计算法来根据图像特征估计机翼扑动周期.这一算法能够更准确地捕捉到抖动的周期性特征,为后续的稳像处理提供了重要参数.其次,提出了一种与扑动周期相关联的运动滤波算法,能够根据不同飞行工况对滤波参数自适应地进行动态调整.本文提出的算法优点在于能够根据扑翼飞行机器人实际飞行情况实时调整参数,从而更好地适应不同的飞行工况,进一步提高了稳像效果.最后,为了验证算法的可行性和稳定性,将视觉成像装置搭载在扑翼飞行机器人上进行了飞行实验.实验结果表明,相较于常用的电子稳像算法,本文所设计的算法在扑翼飞行机器人中表现出更好的稳像效果.最后,总结了本文所提出的算法优点,并对未来研究方向做出了展望.

平均降采样多周期微分均值的旋转部件故障特征增强方法

为解决编码器的瞬时角速度(Instantaneous Angular Speed,IAS)信号中旋转部件故障特征微弱的难题,本文提出一种平均降采样多周期微分均值(Average Down⁃Sampling Multi⁃period Differential Means,ADSMPDM)的故障特征增强方法。基于IAS信号的估计特性,开展了IAS信号的平均降采样研究,验证了平均降采样具有抑制随机噪声的特性;基于平均降采样抑制随机噪声特性、降低计算成本和减小存储空间的优势,结合多周期微分均值的累积特性,提出一种ADSMPDM算法对原始IAS信号中的旋转部件故障分量进行增强处理;通过阶次谱分析揭示故障特征。采用仿真数据和实验数据进行验证分析,并与快速谱峭度、可调整多点优化最小熵反卷积、离散随机分离和谱幅值调制算法进行对比,验证了ADSMPDM算法增强旋转部件故障特征的有效性和优势。

交交变频调速系统中变周期均值采样的研究应用

针对交交变频调速系统中电压、电流纹波含量较大且纹波周期时变,无法直接反馈于调速控制系统的问题,提出一种变周期均值采样算法。首先,该算法以实时交交变频功率器件触发脉冲的间隔时间作为均值周期,对电压、电流实际值进行均值计算。其次,根据电压、电流实时频率及均值周期计算该均值周期所带来的相位滞后角度。最后,按照相位滞后角度进行滞后补偿及插补运算,得到更理想的电压、电流反馈值,用于调速控制系统。相较于一般的均值采样,该算法更适合交交变频纹波周期时变的情况,并能消除采样滞后,提升调速系统控制性能及稳定性。

一类分数阶随机微分方程的均方渐近概周期解

关于分数阶随机微分方程解的性质研究是近几年数学界的热门方向之一。针对Hilbert空间上一类线性分数阶随机微分方程,研究其均方渐近概周期温和解的存在性和唯一性,然后将这类线性分数阶随机微分方程的结论推广到对应的半线性分数阶随机微分方程中,利用Banach不动点定理讨论这类半线性分数阶随机微分方程均方渐近概周期温和解的存在唯一性,再利用Schauder不动点定理讨论这类方程在非Lipschitz条件下均方渐近概周期温和解的存在性。

基于在线特征库的非侵入式负荷特征提取方法

负荷特征是指负荷设备运行过程中具备某种统计规律的特殊标识,而包含负荷特征的数据库则是实现非侵入式负荷监测与分解的基本依据。对于纯阻性负荷设备,研究人员利用其运行状态切换过程中功率产生跃变的特点,可以准确提取相应状态下的负荷特征。然而,对非纯阻性设备,其负荷特征提取存在以下2个问题。问题1)运行状态切换过程中功率变化不显著,无法精准定位状态投切时刻点;问题2)负荷设备存在功率缓变化的运行状态,导致对应状态下的负荷特征不唯一,无法手动提取。为了解决非纯阻性设备负荷特征提取中存在的上述问题,提出一种基于在线特征库的非侵入式负荷特征提取方法,该方法分为2个阶段。第一阶段:基于负荷设备运行过程中的稳态周期电流数组建立在线特征库,通过改进Pearson相似系数构建滑窗函数,得到负荷设备运行时的周期电流数组与在线特征库的相似性,并同步判断在线特征库冗余性,实现负荷设备状态数据分割;第二阶段:计算在线特征库的特征矩阵,对特征矩阵进行K-means聚类分析,融合相似在线特征库,形成负荷设备的状态特征库,从而实现负荷设备特征电流数组的提取。在私人数据集和PLAID数据集上的测试结果证明,所提负荷特征提取方法在不同的用电场景下均有较好的鲁棒性。所提方法可大幅减少负荷特征提取阶段的人工参与,有利于缓解因负荷设备种类过多导致的负荷特征提取烦琐的问题,为后续建立负荷特征数据库提供了便利。

顾及周期性变化的大气加权平均温度模型构建

针对大气加权平均温度(T_(m))是地基全球卫星导航系统(GNSS)水汽反演过程中的一个中间变量,其精度会影响地基GNSS水汽反演精度,同时T_(m)表现出较强的地域性差异的现状,研究建立地区的T_(m)模型:利用兰州市榆中探空站气象数据和欧洲中期天气预报中心第五代大气再分析数据集(ERA5)分别建立单因子、顾及年周期变化、顾及年和半年周期变化的T_(m)模型;并对2种气象数据所建的3类模型进行显著性检验和精度验证。结果表明:模型均能通过显著性水平为0.05的显著性检验,同时顾及周期性变化模型的预测值的均方根误差和平均绝对误差均小于贝维斯(Bevis)模型和单因子模型;利用顾及周期变化的模型预测的T_(m)偏差中大于5 K和大于10 K的值占比明显减小且预测残差的周期趋势明显减弱,具有零均值的正态分布特性,仅表现出误差的随机性。总体而言,ERA5气象数据所建模型预测精度高于探空站气象数据所建模型;用ERA5气象数据建立的顾及周期性变化的T_(m)模型可用于兰州市GNSS大气水汽反演。

基于K-means聚类方法和相似时段的特高压并联电抗器油温预测

为及时评估特高压并联电抗器内部的绝缘状态,提出了一种特高压并联电抗器油温预测方法。首先基于特高压并联电抗器油温曲线的“单峰单谷”变化趋势,利用K-means聚类方法将油温曲线划分为低谷时段和高峰时段2个部分。然后分析了特高压并联电抗器油温的主要影响因素,并根据K-means聚类和时间“近大远小”原则,基于气象、油温和时间3个因素对油温历史样本进行3次分类后,选择得到了相似时段。最后详细给出了基于相似时段的油温预测方法的计算流程。将所提方法应用到江苏地区某特高压并联电抗器油温的预测工作中,结果表明所提方法的平均误差为1.03%,最大误差为4.84%,具有较高预测精度,从而验证了方法的有效性。

THEORETICAL AMPLITUDE AND PERIOD OF PRECURSOR SOLITON GENERATION IN TWO-LAYER FLOW

An fKdV equation of two-layer how and an averaged fKdV equation (AfKdV equation) with respect to phase are derived to determine the theoretical amplitude and period of the precursor solitons in the present paper. In terms of the AfKdV equation derived by the authors, a new theory on the precursor soliton generation based on Lee et al.'s concept is presented. Concepts of asymptotic mean hydraulic fall and level are introduced in our analysis, and the theoretical amplitude and period both depend on the asymptotic mi-an levels and stratified parameters. From the present theoretical results, it is obtained that when the moving velocity of the topography is at the resonant points, there exist two general relations: (1) amplitude relation (A) over circle = 2F, (2) period relation <(tau)over circle> = -8m(1)m(3)(-1)root 6m(4)m(3)(-1)F, in which (A) over circle and <(tau)over circle> are the amplitude and period of the precursor solitons at the resonant points respectively, m(1), m(3) and m(4) are coefficients of the fKdV equation, and F is asymptotic mean half-hydraulic fall at subcritical cutoff points. The theoretical results of this paper are compared with experiments and numerical calculations of two-layer flow over a semicircular topography and all these results are in good agreement. Due to the canonical character of the coefficients of fKdV equations, this theory also holds for any two-dimensional system, which can be reduced to fKdV equations.

数据驱动下的传染病大流行期间大城市交通运行状况研究

新型冠状病毒肺炎是近百年来人类遭遇的影响范围最广的全球性大流行病,探究新冠疫情期间不同城市交通运行状况的演变规律,对当前传染病大流行情境下的交通运行至关重要,并对未来类似情形下的城市交通治理具有借鉴作用。城市交通运行状况可由交通健康指数、拥堵延时指数等数据来表征,因此本文收集疫情放开后十个大城市近一个月的拥堵延时指数、平均车速和交通健康指数等数据,通过相关性分析、线性回归、k-means聚类分析等方法,从多个角度探究城市交通健康指数与拥堵延时指数或平均车速之间的关系,据此采用拥堵延时指数来研究各城市交通运行状况。进而基于拥堵延时指数将研究时段划分为疫情影响期、疫情稳定期、复工复产期、春节影响期这四个阶段。并在早晚高峰、疫情、春节以及跨年夜等多种情境下,从工作日和节假日多方面挖掘各城市在疫情放开影响下交通状况变化的异同点。结果表明,在疫情放开和春节假期等多种复杂因素的影响下,交通健康指数仍能由拥堵延时指数或平均车速线性表征,交通健康指数存在一定程度的冗余,用拥堵延时指数等更易获取的数据就能够描述城市的交通运行状况。此外,疫情消退过程中,工作日早晚高峰出行的不均衡性较小,而节假日早晚高峰出行的不均衡性较大,达到40%。

Application of Linear Mean-Square Estimation in Ocean Engineering

The attempt to obtain long-term observed data around some sea areas we concern is usually very hard or even impossible in practical offshore and ocean engineering situations. In this paper, by means of linear mean-square estimation method, a new way to extend short-term data to long-term ones is developed. The long-term data about concerning sea areas can be constructed via a series of long-term data obtained from neighbor oceanographic stations, through relevance analysis of different data series. It is effective to cover the insufficiency of time series prediction method＇s overdependence upon the length of data series, as well as the limitation of variable numbers adopted in multiple linear regression model. The storm surge data collected from three oceanographic stations located in Shandong Peninsula are taken as examples to analyze the number-selection effect of reference oceanographic stations（adjacent to the concerning sea area） and the correlation coefficients between sea sites which are selected for reference and for engineering projects construction respectively. By comparing the N-year return-period values which are calculated from observed raw data and processed data which are extended from finite data series by means of the linear mean-square estimation method, one can draw a conclusion that this method can give considerably good estimation in practical ocean engineering, in spite of different extreme value distributions about raw and processed data.