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1.
随着云计算、大数据、人工智能等IT新技术的不断发展,依托其构建的电力调控云规模不断扩大,相应的电力调控云应用服务数量也随之成倍增加,使得它们电力调控云的运维复杂度加大,运维任务量加重,基于人工的运维模式效率低下、出错率较高。持续集成、持续部署(CI/CD)平台可对电力调控云进行高效、精准的自动化维护。通过引入一种面向电力调控云的高效运维方法,执行完成电力调控云产品的自动化构建、版本控制、批量部署等运维任务。最后通过对电力调控云平台的仿真实验,验证了该方法可以减轻运维任务量,提升工作效率。  相似文献   
2.
Abstract. This paper obtains the joint limiting distribution of residuals and squared residuals of a general time‐series model. Based on this, we propose a mixed portmanteau statistic for testing the adequacy of fitted time‐series models. In some cases, it is shown that this statistic can be simply approximated by the sum of well‐known portmanteau statistics. The finite‐sample performance of the new test is compared with those of well‐known tests through simulations.  相似文献   
3.
Abstract. Conditions under which sums, products and time-aggregation of ARMA processes follow ARMA models are derived from a single theorem. This characterizes these processes in terms of difference equations satisfied by their autocovariance function. From this we obtain necessary and sufficient conditions for a function of a Gaussian ARMA process and the product of two possibly dependent Gaussian ARMA processes to be ARMA. We show that the sum and product of two ARMA processes related by a Box and Jenkins transfer function model belong to the ARMA family.  相似文献   
4.
Forecasting the international trade of rice is difficult because demand and supply are affected by many unpredictable factors (e.g., trade barriers and subsidies, agricultural and environmental factors, meteorological factors, biophysical factors, changing demographics, etc.) that interact in a complex manner. This paper compares the performance of artificial neural networks (ANNs) with exponential smoothing and ARIMA models in forecasting rice exports from Thailand. To ascertain that the models can reproduce acceptable results on unseen future, we evaluated various aggregate measures of forecast error (MAE, MSE, MAPE, and RMSE) during the validation process of the models. The results reveal that while the Holt–Winters and the Box–Jenkins models showed satisfactory goodness of fit, the models did not perform as well in predicting unseen data during validation. On the other hand, the ANNs performed relatively well as they were able to track the dynamic non-linear trend and seasonality, and the interactions between them.  相似文献   
5.
This paper shows how existing methods of time series analysis and modeling can be exploited in novel ways to monitor and forecast the COVID-19 epidemic. In the past, epidemics have been monitored by various statistical and model metrics, such as evaluation of the effective reproduction number, R(t). However, R(t) can be difficult and time consuming to compute. This paper suggests two relatively simple data-based metrics that could be used in conjunction with R(t) estimation and provide rapid indicators of how the epidemic’s dynamic behavior is progressing. The new metrics are the epidemic rate of change (RC) and a related state-dependent response rate parameter (RP), recursive estimates of which are obtained from dynamic harmonic and dynamic linear regression (DHR and DLR) algorithms. Their effectiveness is illustrated by the analysis of COVID-19 data in the UK and Italy. The paper also shows how similar methodology, combined with the refined instrumental variable method for estimating hybrid Box–Jenkins models of linear dynamic systems (RIVC), can be used to relate the daily death numbers in the Italian and UK epidemics and then provide 15-day-ahead forecasts of the UK daily death numbers. The same approach can be used to model and forecast the UK epidemic based on the daily number of COVID-19 patients in UK hospitals. Finally, the paper speculates on how the state-dependent parameter (SDP) modeling procedures may provide data-based insight into a nonlinear differential equation model for epidemics such as COVID-19.  相似文献   
6.
《Lubrication Science》2017,29(7):441-454
The present study investigates hydrodynamic lubrication by ferrofluids of finite journal bearings using the Jenkins model. A magnetic field created by displaced finite wire is used. A numerical solution for the modified Reynolds equation using the finite difference method is obtained. Static characteristics of finite journal bearings are analyzed using 2 control parameters: magnetic force coefficient and Jenkins viscosity. The obtained results are compared to those from Neurenger‐Rosensweig model. It is shown that pressure, load capacity, attitude angle, and side leakage increase and friction factor decreases when increasing the value of each control parameter at low and medium eccentricity ratios. However, the Jenkins viscosity parameter decreases the load capacity and increases the friction factor at high eccentricity ratios.  相似文献   
7.
J.  R.  Y. 《Automatica》2004,40(12):2083-2089
The identification of a SISO linear dynamic system in the presence of output noise disturbances is studied. It is shown that a nonparametric model for the disturbing output noise can be extracted from the raw data, even without estimating a plant model. Next a Box–Jenkins alike identification scheme is proposed using the nonparametric noise model as weighting.  相似文献   
8.
A suitable combination of linear and nonlinear models provides a more accurate prediction model than an individual linear or nonlinear model for forecasting time series data originating from various applications. The linear autoregressive integrated moving average (ARIMA) and nonlinear artificial neural network (ANN) models are explored in this paper to devise a new hybrid ARIMA–ANN model for the prediction of time series data. Many of the hybrid ARIMA–ANN models which exist in the literature apply an ARIMA model to given time series data, consider the error between the original and the ARIMA-predicted data as a nonlinear component, and model it using an ANN in different ways. Though these models give predictions with higher accuracy than the individual models, there is scope for further improvement in the accuracy if the nature of the given time series is taken into account before applying the models. In the work described in this paper, the nature of volatility was explored using a moving-average filter, and then an ARIMA and an ANN model were suitably applied. Using a simulated data set and experimental data sets such as sunspot data, electricity price data, and stock market data, the proposed hybrid ARIMA–ANN model was applied along with individual ARIMA and ANN models and some existing hybrid ARIMA–ANN models. The results obtained from all of these data sets show that for both one-step-ahead and multistep-ahead forecasts, the proposed hybrid model has higher prediction accuracy.  相似文献   
9.
In this paper two multivariate statistical methodologies are compared in order to estimate a multi‐input multi‐output transfer function model in an industrial polymerization process. In these contexts, process variables are usually autocorrelated (i.e. there is time‐dependence between observations), posing some problems to classical linear regression models. The two methodologies to be compared are both related to the analyses of multivariate time series: Box‐Jenkins methodology and partial least squares time series. Both methodologies are compared keeping in mind different issues, such as the simplicity of the process modeling (i.e. the steps of the identification, estimation and validation of the model), the usefulness of the graphical tools, the goodness of fit, and the parsimony of the estimated models. Real data from a polymerization process are used to illustrate the performance of the methodologies under study. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   
10.
Ferrofluid lubrication in porous inclined slider bearing with velocity slip   总被引:2,自引:0,他引:2  
The effects of slip velocity and the material constant in a porous inclined slider bearing lubricated with a ferrofluid were theoretically studied by using Jenkins model. Expressions were obtained for pressure, load capacity, friction on the slider, coefficient of friction and position of the centre of pressure. The increase in slip parameter caused decrease in load capacity as well as friction and increase in the coefficient of friction without altering the centre of pressure much. As the material constant increased, the load capacity decreased, friction and coefficient of friction increased and the position of the centre of pressure shifted slightly towards the inlet of the bearing.  相似文献   
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