A New Multidimensional Time Series Forecasting Method Based on the EOF Iteration Scheme

In this paper a new .mnultidimensional time series forecasting scheme based on the empirical orthogonal function (EOF) stepwise iteration process is introduced. The scheme is tested in a series of forecast experiments of Nino3 SST anomalies and Tahiti-Darwin SO index. The results show that the scheme is feasible and ENSO predictable.

Forecasting Methods to Reduce Inventory Level in Supply Chain

Based on the two-level supply chain composed of suppliers and retailers, we assume that market demand is subject to an ARIMA(1, 1, 1). The supplier uses the minimum mean square error method (MMSE), the simple moving average method (SMA) and the weighted moving average method (WMA) respectively to forecast the market demand. According to the statistical properties of stationary time series, we calculate the mean square error between supplier forecast demand and market demand. Through the simulation, we compare the forecasting effects of the three methods and analyse the influence of the lead-time L and the moving average parameter N on prediction. The results show that the forecasting effect of the MMSE method is the best, of the WMA method is the second, and of the SMA method is the last. The results also show that reducing the lead-time and increasing the moving average parameter improve the prediction accuracy and reduce the supplier inventory level.

Tide forecasting method based on dynamic weight distribution for operational evaluation

Through analysis of operational evaluation factors for tide forecasting, the relationship between the evaluation factors and the weights of forecasters was examined. A tide forecasting method based on dynamic weight distribution for operational evaluation was developed, and multiple-forecaster synchronous forecasting was realized while avoiding the instability cased by only one forecaster. Weights were distributed to the forecasters according to each one＇s forecast precision. An evaluation criterion for the professional level of the forecasters was also built. The eligibility rates of forecast results demonstrate the skill of the forecasters and the stability of their forecasts. With the developed tide forecasting method, the precision and reasonableness of tide forecasting are improved. The application of the present method to tide forecasting at the Huangpu Park tidal station demonstrates the validity of the method.

Time Series Neural Network Forecasting Methods

In this paper,the possibility and key problem to construct the neural network time series model and three time series neural network forecasting methods,that is, the nerual network nonlinear time series model,neural network multi-dimension time series models and the neural network combining predictive model,are proposed.These three methods are applied to real problems.The results show that these methods are better than the traditional one.Furthermore,the neural network compared to the traditional method,and the constructed model of intellectual information forecasting system is given.

Microseismic monitoring and forecasting of dynamic disasters in underground hydropower projects in southwest China:A review

The underground hydropower projects in Southwest China is characterized by large excavation sizes,high geostresses,complicated geological conditions and multiple construction processes.Various disasters such as collapses,large deformations,rockbursts are frequently encountered,resulting in serious casualties and huge economic losses.This review mainly presents some representative results on microseismic(MS)monitoring and forecasting for disasters in hydropower underground engineering.First,a set of new denoising,spectral analysis,and location methods were developed for better identification and location of MS signals.Then,the tempo-spatial characteristics of MS events were analyzed to understand the relationship between field construction and damages of surrounding rocks.Combined with field construction,geological data,numerical simulation and parametric analysis of MS sources,the focal mechanism of MS events was revealed.A damage constitutive model considering MS fracturing size was put forward and feedback analysis considering the MS damage of underground surrounding rocks was conducted.Next,an MS multi-parameter based risk assessment and early warning method for dynamic disasters were proposed.The technology for control of the damage and deformation of underground surrounding rocks was proposed for underground caverns.Finally,two typical underground powerhouses were selected as case studies.These achievements can provide significant references for prevention and control of dynamic disasters for underground engineering with similar complicated geological conditions.

CHGS method for numerical forecasting of typhoon waves-Ⅰ. Spectrum of waves in growing phase

Owing to the fact that the wind speed and direction of typhoon vary rapidly with time and space in typhoon fetch; the nearer to the typhoon eye the greater the wind velocity, and the shorter the wind fetch the smaller the wind time,as a result,the more difficult for the wind wave to fully grow. Hence.in typhoon wave numerical calculation it is impossible to use the model for a fully grown wave spectrum. Lately, the author et at. presented a CHGS method for numerical forecasting of typhoon waves, where a model for the growing wave spectrum was set up (see Eq. (2) in the text). The model involves a parameter indicating the growing degree of wind wave, i. e. ,the mean wave age β. When βvalue is small, the wave energy is chiefly concentrated near the peak frequency, so that the spectral peak gets high and steep; with the increase of β the spectral shape gradually gets lower and gentler; when β=Ⅰ, the wave fully grows, the growing spectrum becomes a fully grown P-M spectrum. The model also shows a spectral “overshooting” phenomenon within the “balance zone”.

A Forecasting Model of Vector Similarity in Phase Space for Flood and Drought over the Huanghe-Huaihe-Haihe Plain in China

To represent well the characteristics of temporal and spatial distributions, chart of 3-dekad moving total precipitation is proposed in this paper first. Then this kind of chart is expanded in terms of Chebyshev polynomial at irregular grids, and the quantitative representation of precipitation is got. Finally the Chebyshev coefficients are forecasted by using the forecasting method of vector similarity in phase space proposed by Zhou (1992). Using above mentioned procedures temporal and spatial distributions of precipitation over the Huanghe-- Huaihe-- H aihe Plain in China are forecasted.

Spare Parts Demand Forecasting:a Review

Spare parts are very common in industry and military fields, and the investigations of spare parts demand forecasting methods have draws much attention in recent years. However,to the best of our knowledge,only few papers reviewed the forecasting papers systematically. This paper is an attempt to provide a novel and comprehensive view to summarize these methods. A new framework was proposed to classify the demand forecasting methods into four categories,including empirical methods,methods based on historical data,analytical methods and simulation methods. Some typical literatures related to each category were reviewed.Moreover, a general spare parts forecasting procedure was summarized and some evaluation criteria were presented. Finally,characteristics of different forecasting methods and some avenues for further research were illustrated. This work provides the managers with a systematical idea about the spare parts demand forecasting and it can be used in practical applications.

Relationship between rock uniaxial compressive strength and digital core drilling parameters and its forecast method

The rock uniaxial compressive strength(UCS)is the basic parameter for support designs in underground engineering.In particular,the rock UCS should be obtained rapidly for underground engineering with complex geological conditions,such as soft rock,fracture areas,and high stress,to adjust the excavation and support plan and ensure construction safety.To solve the problem of obtaining real-time rock UCS at engineering sites,a rock UCS forecast idea is proposed using digital core drilling.The digital core drilling tests and uniaxial compression tests are performed based on the developed rock mass digital drilling system.The results indicate that the drilling parameters are highly responsive to the rock UCS.Based on the cutting and fracture characteristics of the rock digital core drilling,the mechanical analysis of rock cutting provides the digital core drilling strength,and a quantitative relationship model(CDP-UCS model)for the digital core drilling parameters and rock UCS is established.Thus,the digital core drilling-based rock UCS forecast method is proposed to provide a theoretical basis for continuous and quick testing of the surrounding rock UCS.

2009年春末初夏持续高温天气分析及预报模型(英文)

This paper analyzed characteristics of Pingliang City's continuous hot weather from late spring to early summer in 2009.The result showed that,when the daily maximum temperature in some parts of cities had run up to 32℃ or above,the number of days reached the top in recent 40 years.The average temperature,average maximum temperature,surface maximum temperature and surface average temperature in most parts of the city broke history record.Based on the analysis of characteristics of the 500 hPa circulation,which resulted in durative high temperature weather,3 kinds of the high temperature circulation patterns were summarized.It was the continental warm high pressure that resulted in the durative high temperature weather in June,2009.Meanwhile,by using European numerical forecast product and MOS,the forecasting method of high temperature,from June to August,was set up.The method had been used in June,and its high-temperature forecasting accuracy in 24,48,72,96,120 hours had respectively amounted to 76.6%,69.5%,61.4%,58.1% and 51.9%.

A SIMILARITY SCHEME FOR QUANTITATIVE FORECAST OF PRECIPITATION OF TYPHOONS

A quantitative scheme is put forward in our work of forecasting the storm rainfall of typhoons for specific sites.Using the initial parameters,weather situations and physical quantities as well as numerical weather prediction products,the scheme constructs multivariate,objective and similarity criteria for environmental factors for the time between the current and forthcoming moment within the domain of forecast.Through defining a non-linear similarity index,this work presents a comprehensive assessment of the similarity between historical samples of typhoons and those being forecast in terms of continuous dynamic states under the multivariate criteria in order to identify similar samples.The historical rainfall records of the similar samples are used to run weighted summarization of the similarity index to determine site-specific and quantitative forecasts of future typhoon rainfall.Samples resembling the typhoon being forecast are selected by defining a non-linear similarity index composed of multiple criteria.Trial tests have demonstrated that this scheme has positive prediction skill.

Study of evolution forecast of the area of the Huanghe River mouth

From 1979 to 1989, the current Qingshuigou course of the Huanghe River formed a sub - delta which resembles a beak extending into the Laizhou Bay. It covers 618 km2 in area. To meet the needs of developing and constructing the Huanghe River Delta and under the presupposition of keeping the current course for 15-20 a, we forecast mainly by using the OM (1, 1) model that the front border of the sub-delta will be close to 119°30'E and its area will become 923 km2by the end of the year 2000. The Huanghe River will make land 760 km2 in area.

池州市大雾特征分析及预警服务系统(英文)

By analyzing the heavy fog data in Chizhou City in recent 50 years(1959-2007),the general rules of meteorological elements variations were found when the heavy fog happened.The meteorological elements included the temperature,humidity,wind direction,wind speed,air pressure and so on.The conceptual models of high-altitude and ground situation were established when the heavy fog happened in Chizhou City.Based on considering sufficiently the special geographical environment in Chizhou City,we found the key factors which affected the local heavy fog via the relative analyses.By using the statistical forecast methods which included the second-level judgment method and regression method of event probability and so on,the forecast mode equation of heavy fog was established.Moreover,the objective forecast system of heavy fog in Chizhou City was also manufactured.It provided the basis and platform which could be referred for the heavy fog forecast,service and the release of early-warning signal.

Individual and combination approaches to forecasting hierarchical time series with correlated data:an empirical study

Hierarchical time series arise in manufacturing and service industries when the products or services have the hierarchical structure,and top-down and bottomup methods are commonly used to forecast the hierarchical time series.One of the critical factors that affect the performance of the two methods is the correlation between the data series.This study attempts to resolve the problem and shows that the top-down method performs better when data have high positive correlation compared to high negative correlation and combination of forecasting methods may be the best solution when there is no evidence of the correlationship.We conduct the computational experiments using 240 monthly data series from the‘Industrial’category of the M3-Competition and test twelve combination methods for the hierarchical data series.The results show that the regression-based,VAR-COV and the Rank-based methods perform better compared to the other methods.

The dynamic forecast method of convective vorticity vector

In this paper we introduce the convective vorticity vector and its application in the forecast and diagnosis of rainstorm.Convective vorticity vector is a parameter of vector field,different from scalar field,it contains more important information of physical quantities,so it could not be replaced.Considering the irresistible importance of vector field we will introduce the theory of vector field and its dynamic forecast method.With the convective vorticity vector and its vertical component's tendency equation,diagnostic analysis on the heavy-rainfall event caused by landfall typhoon“Morakot”in the year 2009 is conducted.The result shows that,the abnormal values of convective vorticity vector always changes with the development of the observed precipitation region,and their horizontal distribution is quite similar.Analysis reveals a certain correspondence between the convective vorticity vector and the observed 6-h accumulated surface rainfall,they are significantly related.The convective vorticity vector is capable of describing the typical vertical structure of dynamical and thermodynamic fields of precipitation system,so it is closely related to the occurrence and development of precipitation system and could have certain relation with the surface rainfall regions.

A novel IDEA: The impact of serial interval on a modified- Incidence Decay and Exponential Adjustment (m-IDEA) model for projections of daily COVID-19 cases

The SARS-CoV-2 virus causes the disease COVID-19,and has caused high morbidity and mortality worldwide.Empirical models are useful tools to predict future trends of disease progression such as COVID-19 over the near-term.A modified Incidence Decay and Exponential Adjustment(m-IDEA)model was developed to predict the progression of infectious disease outbreaks.The modification allows for the production of precise daily estimates,which are critical during a pandemic of this scale for planning purposes.The m-IDEA model was employed using a range of serial intervals given the lack of knowledge on the true serial interval of COVID-19.Both deterministic and stochastic approaches were applied.Model fitting was accomplished through minimizing the sum-of-square differences between predicted and observed daily incidence case counts,and performance was retrospectively assessed.The performance of the m-IDEA for projection cases in the nearterm was improved using shorter serial intervals(1e4 days)at early stages of the pandemic,and longer serial intervals at mid-to late-stages(5e9 days)thus far.This,coupled with epidemiological reports,suggests that the serial interval of COVID-19 might increase as the pandemic progresses,which is rather intuitive:Increasing serial intervals can be attributed to gradual increases in public health interventions such as facility closures,public caution and social distancing,thus increasing the time between transmission events.In most cases,the stochastic approach captured the majority of future reported incidence data,because it accounts for the uncertainty around the serial interval of COVID-19.As such,it is the preferred approach for using the m-IDEA during dynamic situation such as in the midst of a major pandemic.