A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

电弧加热高焓风洞Ma=10 AGARD-B标模测力试验

高超声速设备的试验能力对高超声速技术的发展至关重要,目前受制于加热器技术,常规高超声速风洞能够模拟的最高Mach数不超过10。电弧加热器是高焓风洞的重要设备,将电弧加热高焓风洞用于常规气动力试验,为提高试验模拟Mach数开辟了新的方向。介绍了中国航天空气动力技术研究院1.2 m电弧加热高焓风洞进行的AGARD-B标模试验,通过多次标模测力试验结果的标准差,检验了风洞试验数据的重复性和流场稳定性,通过和国内外已有风洞试验数据的对比分析,检验了风洞试验数据的准确性,为后续该电弧加热高焓风洞承接Mach数10的气动力试验提供强有力的技术支撑。

oncausal spatial prediction filtering based on an ARMA model

Conventional f-x prediction filtering methods are based on an autoregressive model. The error section is first computed as a source noise but is removed as additive noise to obtain the signal, which results in an assumption inconsistency before and after filtering. In this paper, an autoregressive, moving-average model is employed to avoid the model inconsistency. Based on the ARMA model, a noncasual prediction filter is computed and a self-deconvolved projection filter is used for estimating additive noise in order to suppress random noise. The 1-D ARMA model is also extended to the 2-D spatial domain, which is the basis for noncasual spatial prediction filtering for random noise attenuation on 3-D seismic data. Synthetic and field data processing indicate this method can suppress random noise more effectively and preserve the signal simultaneously and does much better than other conventional prediction filtering methods.

基于SARIMA-LSTM组合模型的油气集输系统能耗预测

油气集输是油田开发生产过程的重要阶段,准确预测油气集输系统能耗能够为生产调度和能源管控提供支持。为提高油气集输系统能耗预测的准确性,针对其线性和非线性特征,综合考虑数理统计和机器学习预测方法的优缺点,提出一种基于季节性差分自回归积分滑动平均(SARIMA)和长短期记忆(LSTM)神经网络的组合预测模型。根据S油田M环状掺水油气集输系统6年的运行数据,设计组合模型的网络结构,训练组合模型的网络参数。研究结果表明:与传统的SARIMA模型和LSTM神经网络相比,组合模型对三个能耗指标的预测准确性显著提高,可为企业调整生产运行方案和优化能源管控方案提供指导和数据支持。

AUTOREGRESSIVE MODEL AND POWER SPECTRUM CHARATERISTICS OF CURRENT SIGNAL IN HIGH FREQUENCY GROUP PULSE MICRO-ELECTROCHEMICAL MACHINING

The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining （HGPECM） is mainly discussed. The auto-regressive（AR） model of group pulse current flowing across the cathode and the anode are created under different situations with different processing parameters and inter-electrode gap size. The AR model based on the current signals indicates that the order of the AR model is obviously different relating to the different processing conditions and the inter-electrode gap size; Moreover, it is different about the stability of the dynamic system, i.e. the white noise response of the Green＇s function of the dynamic system is diverse. In addition, power spectrum method is used in the analysis of the dynamic time series about the current signals with different inter-electrode gap size, the results show that there exists a strongest power spectrum peak, characteristic power spectrum（CPS）, to the current signals related to the different inter-electrode gap size in the range of 0～5 kHz. Therefore, the CPS of current signals can implement the identification of the inter-electrode gap.

A COMPARISON OF FORECASTING MODELS OF THE VOLATILITY IN SHENZHEN STOCK MARKET

Based on the weekly closing price of Shenzhen Integrated Index, this article studies the volatility of Shenzhen Stock Market using three different models： Logistic, AR（1） and AR（2）. The time-variable parameters of Logistic regression model is estimated by using both the index smoothing method and the time-variable parameter estimation method. And both the AR（1） model and the AR（2） model of zero-mean series of the weekly dosing price and its zero-mean series of volatility rate are established based on the analysis results of zero-mean series of the weekly closing price, Six common statistical methods for error prediction are used to test the predicting results. These methods are： mean error （ME）, mean absolute error （MAE）, root mean squared error （RMSE）, mean absolute percentage error （MAPE）, Akaike＇s information criterion （AIC）, and Bayesian information criterion （BIC）. The investigation shows that AR（1） model exhibits the best predicting result, whereas AR（2） model exhibits predicting results that is intermediate between AR（1） model and the Logistic regression model.

Sleep spindles detection from human sleep EEG signals using autoregressive (AR) model: a surrogate data approach

A new algorithm for the detection of sleep spindles from human sleep EEG with surrogate data approach is presented. Surrogate data ap-proach is the state of the art technique for nonlinear spectral analysis. In this paper, by developing autoregressive (AR) models on short segment of the EEG is described as a superposition of harmonic oscillating with damping and frequency in time. Sleep spindle events are detected, whenever the damping of one or more frequencies falls below a prede-fined threshold. Based on a surrogate data, a method was proposed to test the hypothesis that the original data were generated by a linear Gaussian process. This method was tested on human sleep EEG signal. The algorithm work well for the detection of sleep spindles and in addition the analysis reveals the alpha and beta band activities in EEG. The rigorous statistical framework proves essential in establishing these results.

ARMA Modelling for Whispered Speech

The Autoregressive Moving Average （ARMA） model for whispered speech is proposed. with normal speech, whispered speech has no fundamental frequency because of the glottis being semi-opened and turbulent flow being created, and formant shifting exists in the lower frequency region due to the narrowing of the tract in the false vocal fold regions and weak acoustic coupling with the aubglottal system. Analysis shows that the effect of the subglottal system is to introduce additional pole-zero pairs into the vocal tract transfer function. Theoretically, the method based on an ARMA process is superior to that based on an AR process in the spectral analysis of the whispered speech. Two methods, the least squared modified Yule-Walker likelihood estimate （LSMY） algorithm and the Frequency-Domain Steiglitz-Mcbide （FDSM） algorithm, are applied to the ARMA mfldel for the whispered speech. The performance evaluation shows that the ARMA model is much more appropriate for representing the whispered speech than the AR model, and the FDSM algorithm provides a name acorate estimation of the whispered speech spectral envelope than the LSMY algorithm with higher conputational complexity.

A novel transgenic mouse model of Chinese CharcotMarie-Tooth disease type 2L

We previously found that the K141N mutation in heat shock protein B8 （HSPB8） was responsible for Charcot-Marie-Tooth disease type 2L in a large Chinese family. The objective of the present study was to generate a transgenic mouse model bearing the K141N mutation in the human HSPB8 gene, and to determine whether this K141NHSPB8 transgenic mouse model would manifest the clinical phenotype of Charcot-Marie-Tooth disease type 2L, and consequently be suitable for use in studies of disease pathogenesis. Transgenic mice overexpressing K141N HSPB8 were generated using K141N mutant HSPB8 cDNA cloned into a pCAGGS plasmid driven by a human cytomegalovirus expression system. PCR and western blot analysis confirmed integration of the KI41NHSPB8 gene and widespread expression in tissues of the transgenic mice. The K141N HSPB8 transgenic mice exhibited decreased muscle strength in the hind limbs and impaired motor coordination, but no obvious sensory disturbance at 6 months of age by behavioral assessment. Electrophysiological analysis showed that the compound motor action potential amplitude in the sciatic nerve was significantly decreased, but motor nerve conduction velocity remained normal at 6 months of age. Pathological analysis of the sciatic nerve showed reduced myelinated fiber density, notable axonal edema and vacuolar degeneration in K141N HSPB8 transgenic mice, suggesting axonal involvement in the peripheral nerve damage in these animals. These findings indicate that the KI4mHSPB8 transgenic mouse successfully models Charcot-Marie-Tooth disease type 2L and can be used to study the pathogenesis of the disease.

AR Model Based on Time Series Modeling for Predicting Egg Market Price in 2021

Eggs,as a meat consumer product in China,are closely related to the vegetable basket project.Exploring and predicting the future trend of egg market price is of great significance for stabilizing egg price and market supply.In this study,the time series AR model was used for fitting the egg market prices in the 66 d from January 1 to March 7,2021,and the delay operator nlag18 was used for white noise test,giving pr>probability of chisq<0.005.The time series was not a white noise series,and then the stationary series was used for modeling.The optimal model was selected as the AR series(BIC(3,0)),and finally,the egg market price model AM was obtained as X_(t)=9.0556+(1+0.8926)ε_(t),which was the optimal model.The model showed that the egg price fluctuations in 2021 will be clustered,and the later price will be significantly affected by external factors in the previous period.The dynamic prediction results of the model showed that the egg price would stop falling in March 2020,and the egg price would continue to slow down in March.

Age related macular degeneration: from evidence based-care to experimental models

To describe the current aging population in China and globally,especially as it applies to age-related macular degeneration(AMD).To review the current standards of care for treating both wet(exudative)eAMD and dry(atrophic)aAMD.And to introduce a model for experimentation that is based on the Age-Related Eye Disease Study(AREDS)using eye bank tissue.A literature search that outlines current aging populations,standards of clinical treatment as defined by large,multicenter,randomized clinical trials that present level-I data with a low risk for bias.An experimental model system of AMD is presented that enables scientific analysis of AMD pathogenesis by applying grading criteria from the AREDS to human eye bank eyes.Analysis includes proteomic,cellular,and functional genomics.The standard of care for the treatment of eAMD is currently defined by the use of several anti-vascular endothelial growth(anti-VEGF)agents alone or in combination with photodynamic therapy.Monotherapy treatment intervals may be monthly,as needed,or by using a treat-and-extend(TAE)protocol.There are no proven therapies for aAMD.AMD that is phenotypically defined at AREDS level 3,should be managed with the use of anti-oxidant vitamins,lutein/zeaxanthin and zinc(AREDS-2 formulation).By understanding the multiple etiologies in the pathogenesis of AMD(i.e.,oxidative stress,inflammation,and genetics),the use of human eye bank tissues graded according to the Minnesota Grading System(MGS)will enable future insights into the pathogenesis of AMD.Initial AMD management is with lifestyle modification such as avoiding smoking,eating a healthy diet and using appropriate vitamin supplements(AREDS-2).For eAMD,anti-VEGF therapies using either pro re nata(PRN)or TAE protocols are recommended,with photodynamic therapy in appropriate cases.New cellular information will direct future,potential therapies and these will originate from experimental models,such as the proposed eye bank model using the MGS,that leverages the prospective AREDS database.

基于ARIMA模型的辽河流域生态足迹动态模拟与预测

将能值与生态足迹理论相结合,引入能量折算系数,通过能值密度构建能值-生态足迹模型,并应用此模型对辽河流域2001—2010年生态承载力和生态足迹进行计算。生态承载力计算主要是自然生态承载力和本地产品产出承载力,其中自然生态承载力主要考虑可更新资源的承载力,本地产品产出承载力主要包括生物资源产出承载力和工业产品产出承载力。生态足迹的计算主要包括消费足迹和污染足迹,消费足迹主要测算生物资源消费、能源消费和水资源消费足迹。污染足迹主要测算废气和生活废水、工业废水对自然生态系统带来的负荷。测算结果表明:2001—2010年辽河流域人均生态承载力和人均生态足迹均有所增加,但是生态足迹的增长速度远远大于生态承载力,致使流域内自2001与2009年生态略有盈余外,其余年份均出现生态赤字,处于不可持续发展状态。以能值-生态足迹模型测算结果为基础,基于EViews采用自回归综合移动平均模型(ARIMA),对流域内10年的生态足迹和生态承载力进行动态模拟。首先通过ADF与PP单位根检验时间序列的平稳性;其次分析序列的自相关函数图和偏自相关函数,初步确定AR和MA的阶次;再根据R2、AIC及SC准则,进行模型参数估计并诊断分析;最后确定最佳模拟模型。以ARIMA模型预测2011—2015年辽河流域生态足迹和生态承载力的演变趋势。预测结果表明,人均生态足迹在未来5年内会继续呈直线式增长,到2015年达到7.387 8 hm2,是2001年的2.16倍;而人均生态承载力在2011年之后开始下降,生态赤字继续扩大,到2015年增长到-4.167 67,约为2005年的10倍,流域内不可持续发展形势会更加恶化。最后提出辽河流域生态安全建设的对策。能值-生态足迹模型测算结果与实地调研基本相符,较真实反映了辽河流域可持续发展状况。基于ARIMA模型模拟预测结果可为未来流域开发和建设提供参考依据。

基于ARIMA模型的区域水生态足迹时间序列分析

20世纪末以来,生态足迹理论应用研究成为生态经济学的一个热点,而生态足迹指标的可预测性一直是研究中争论的一个焦点。通过分析1949—1998年广州市的水生态足迹变化,并对计算结果进行ARIMA模型时间序列预测分析,以揭示广州水资源利用和水产品消耗的发展变化规律,并根据其发展变化规律预测广州市未来水生态足迹的变动。结果表明,ARIMA(2,2,2)模型能较好的拟合广州市1949—1993年期间水生态足迹变化,经1994—1998年实际计算结果验证所建模型,误差在5%左右;应用ARIMA(2,2,2)预测广州市1999—2008年的人均水生态足迹,结果分别为:0.5935,0.656 2,0.714 7,0.779 0,0.840 2,0.901 55,0.964 11,1.025 57,1.087 44,1.149 43 hm2,预测结果表明广州市1999—2008年期间的人均水生态足迹仍呈较快上升趋势,居民对于水产品的需求提高以及城市发展、人口增加等社会经济因素是导致这种趋势产生的主要原因。

应用ARIMA模型对呼吸系统疾病月住院量及住院费用的预测

目的应用自回归移动平均模型(autoregressive integrated moving average model,ARIMA)分析和预测上海市居民呼吸系统疾病月住院量及住院费用情况。方法通过对2005-2011年呼吸系统疾病逐月住院人数与费用数据建立ARIMA模型,利用该模型预测2012年1-12月的呼吸系统疾病住院量与住院费用,用平均预测相对误差作为预测效果的评价指标。结果 ARIMA(0,1,1)(0,1,1)12与ARIMA(0,1,1)模型是上海市居民呼吸系统疾病月住院量及住院费用的最优拟合预测模型,用该模型进行回代预测,预测值与实际值吻合程度较高。结论 ARIMA模型较好地模拟了上海市居民呼吸系统疾病月住院量及住院费用在时间序列上的变化趋势,预测结果可为今后呼吸系统疾病的预防和控制提供理论支持。

Multi-agent Based Hierarchy Simulation Models of Carrier-based Aircraft Catapult Launch

With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the program codes.

基于Matlab的AR模型参数估计

基于Matlab用时间序列的最小二乘估计和FPE、AIC、BIC准则对AR(n)模型进行参数估计。用实例说明运用Matlab进行AR(n)参数估计,编程简单。

MULTI-AGENT BASED DISTRIBUTED MANUFACTURING EXECUTION SYSTEM MODEL

A multi-agent based manufacturing execution system (MES) model is presented. It is open, modula-rized, distributed, configurable, integratable and maintainable. By analyzing the MES domain in manufacturing systems, this paper proposes a multi-agent based MES model and analyzes the partitioned functions of MES in the model using unified modeling language (UML) diagrams, and establishes the ongoing implemented MES architecture. This MES can be facilely integrated with the enterprise resource planning (ERP), the floor control system (FCS), and the other manufacturing applications.

基于ARIMA模型的光纤陀螺随机漂移滤波方法研究

对光纤陀螺随机漂移输出进行了非平稳性检验,并建立了非平稳求和自回归滑动平均(ARIMA)模型,在此模型的基础上对光纤陀螺随机漂移进行卡尔曼(Kalman)滤波,并对滤波结果进行Allan方差分析。与基于自回归(AR)模型的Kalman滤波结果进行比较,实验结果表明:基于ARIMA模型的Kalman滤波比基于AR模型的Kalman滤波更能减小光纤陀螺的零偏不稳定性和角度随机游走。

Prediction of Climate Change in the 21^(st) Century in Dalian Area under the Various Emission Scenarios

By using the simulative results of more than 20 climate system models which were provided by the fourth assessment report of the Intergovernmental Panel on Climate Change(IPCC),the climate change in Dalian area in the 21st century under the different scenarios(SRES A2,SRES A1B and SRES B1) were analyzed and predicted with the multi-model's aggregative simulative results via the interpolation downscaling calculation.The results showed that the climate in Dalian would have the obvious warming and wetting tendency in the 21st century as a whole.The annual average warming tendency of air temperature would be 2.45-3.46 ℃/100 years,and the annual precipitation increase trend would be 5.8%-16.3% per 100 years.The warming in winter would be the most obvious,and the precipitation increase would be comparatively obvious in winter and spring.The precipitation decrease would be comparatively obvious in autumn in the previous period of 21st century.In A2,A1B and B1 scenarios,the air temperatures in the late period of 21st century would respectively be 3.46,3.44 and 2.45 ℃ higher than in the ordinary years,and the annual precipitation would respectively be 16.3%,11.8% and 5.79% more than in the ordinary years.