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.

Occurrence Rule and Forecast Method of Cotton Aphid in Poyang Lake Area in Jiujiang City

[Objective] The aim was to explore occurrence rules and forecast methods of cotton aphid in Poyang Lake Area in Jiujiang City to enrich prediction methods of cotton aphid in the area. [Method] The occurrence rules and influencing factors of cotton aphid in Pengze County in 28 years were analyzed with comparative analysis, correlation analysis and wavelet analysis. Furthermore, a long-term forecast model of occurrence grade of cotton aphid and a short-term forecast model of weather condi- tion suitability were established based on stepwise regression. In addition, a forecast test was conducted in cotton area in the north of Poyang Lake. [Result] The wavelet analysis showed that in recent 28 years, oscillating period at 4 years was significant for the occurrence grade of cotton aphid in the north of Poyang Lake, but insignifi- cant for cotton at seedling stage. The comparative and correlation analyses suggest- ed that occurrence of cotton aphid is of significant correlation with winter climate and weather conditions at middle and short periods. The prediction test indicated that long-term forecast model of occurrence grade of cotton aphid and short-term forecast model of weather condition suitability based on stepwise regression can be made use of in the areas with similar climate. [Conclusion] The research provides theoreti- cal references for prevention against cotton aphid in cotton-planting area.

STUDY ON THE FORECAST METHOD FOR THE IMPACT OF CROSSWAY ON TIDAL CURRENT FIELD IN SEA AREA

This paper’s method simulates the tidal current field near piles to derive and predict the scale oftheir impacts on the tidal current field, and presents the empirically obtained damp coefficient needed inpedicting the current field. The substituted plans used in the prediction are studied using Qingdao.Crossway as an example.

Study on Refined Forecast Method of Daily Maximum Temperature in Wugang City from July to September

[Objective] The aim was to study the refined forecast method of daily highest temperature in Wugang City from July to September. IM[ethod] By dint of ECMWF mode product and T231 in 2009 and 2010 and daily maximum temperature in the station in corresponding period, multi-factors similar forecast method to select forecast sample, multivariate regression multi-mode integration MOS method, after dynamic corrected mode error and regression error, dynamic forecast equation was concluded to formulate the daily maximum temperature forecast in 24 -120 h in Wugang City from July to September. [ Result] Through selection, error correction, the daily maximum temperature equation in Wugang City from July to September was concluded. Through multiple random sampling, F test was made to pass test with significant test of 0.1. [ Conclusionl The method integrated domestic and foreign forecast mode, made full use of useful information of many modes, absorbed each others advantages, con- sidered local regional environment, lessen mode and regression error, and improved forecast accuracy.

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 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.

A Literature Review of Wind Forecasting Methods

In this paper, an overview of new and current developments in wind forecasting is given where the focus lies upon principles and practical implementations. High penetration of wind power in the electricity system provides many challenges to the power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help the power system operators reduce the risk of unreliability of electricity supply. This paper gives a literature survey on the categories and major methods of wind forecasting. Based on the assessment of wind speed and power forecasting methods, the future development direction of wind forecasting is proposed.

Forecasting available parking space with largest Lyapunov exponents method

The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents(largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network(WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1(in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.

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.

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.

A New Type of Combination Forecasting Method Based on PLS——The Application of It in Cigarette Sales Forecasting

Cigarette market is a kind of monopoly market which is closed loop running, it depends on the plan mechanism to schedule producing, supplying and selling, but the “bullwhip effect” still exists. So it has a fundamental significance to do sales forecasting work. It needs to considerate the double trend characteristics, history sales data and other main factors that affect cigarette sales. This paper depends on the panel data of A province’s cigarette sales, first we established three single forecasting models, after getting the predicted value of these single models, then using the combination forecasting method which based on PLS to predict the province’s cigarette sales of the next year. The results show that the prediction accuracy is good, which could provide a certain reference to cigarette sales forecasting in A province.

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.

Research on relations between failure heights of overburden strata and ~] / mining face parameters and forecasting method

The commercial FEM software ANSYS was used to analyze the failure characteristics of overburden strata under the conditions of different lengths of mining faces. It was shown that the parameters of mining faces, especially the length was the important factor to the failure heights and shapes of overburden strata. Fuzzy mathematics and statistical methods were used to analyze the forecasting method of the failure height of overburden strata influenced by the parameters of mining face based on the measured data under the conditions of fully-mechanized mining of general hardness cover rocks. On the basis of these analyses, a new forecasting formula was gotten. The forecasting result conforms to the in situ measured value. The result has a very important application value in safe and high-efficient mining, and has a very important advancing function to theoretical studies.

TIME SERIES NEURAL NETWORK FORECASTING METHODS

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

Study on Precipitation Forecast and Testing Methods of Numerical Forecast in Fuxin Area

This research uses Japan facsimile data in May-September of 2011-2015 in Fumeng and Zhangwu County of Fuxin, Liaoning, China as the site selection for high altitude NECV circulation background, using statistical and synoptic methods testing the combination of test and Analysis on Japanese numerical precipitation prediction and error. The prediction equation of cold vortex precipitation in the region is established by SPSS software. It is predicted whether the product predicts precipitation, water vapor condition and vertical velocity according to the Japanese numerical forecast. The results show that the fitting rate is 88% in the past 5 years, and the rate of cold vortex precipitation in the summer of 2016 is 89%.

A Type of Combination Forecasting Method Based on Time Series Method and PLS

This paper depends on the panel data of Anhui province and its 17 cities’ cigarette sales. First we established three single forecasting models (Holter-Wintel Season product model, Time series model decomposing model and Partial least square regression model), after getting the predicted value of cigarette sales from these single models, we then employ the combination forecasting method based on Time Series method and PLS to predict the province and its 17 cities’ cigarette sales of the next year. The results show that the accuracy of prediction is good which could provide a reliable reference to cigarette sales forecasting in Anhui province and its 17 cities.

Applying the Dynamic Two-Step Method to Forecast Remaining Oil Distribution of Lower Series ,Xiaermen Oilfield

The distribution of remaining oil is often described qualitatively. The remaining oil distributed in the whole reservoir is calculated according to the characteristics of the space distribution of the saturation of remaining oil. Logging data are required to accomplish this. However, many such projects cannot be completed. Since the old study of remaining oil distribution could not be quantified efficiently, the ＂dynamic two-step method＂ is presented. Firstly, the water cut of every flow unit in one well at one time is calculated according to the comprehensive water cut of a single well at one time. Secondly, the remaining oil saturation of the flow unit of the well at one time is calculated based on the water cut of the flow unit at a given time. The results show that ＂dynamic two-step method＂ has characteristics of simplicity and convenience, and is especially suitable for the study of remaining oil distribution at high water-cut stage. The distribution of remaining oil presented banding and potato form, remaining oil was relatively concentrated in faultage neighborhood and imperfect well netting position, and the net thickness of the place was great. This proposal can provide an effective way to forecast remaining oil distribution and enhance oil recovery, especially applied at the high water-cut stage.

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”.

Adaptive Modeling and Forecasting of Time Series by Combining the Methods of Temporal Differences with Neural Networks

This paper discusses the modeling method of time series with neural network. In order to improve the adaptability of direct multi-step prediction models, this paper proposes a method of combining the temporal differences methods with back-propagation algorithm for updating the parameters continuously on the basis of recent data. This method can make the neural network model fit the recent characteristic of the time series as close as possible, therefore improves the prediction accuracy. We built models and made predictions for the sunspot series. The prediction results of adaptive modeling method are better than that of non-adaptive modeling methods.