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Figure 3: Complex impedance spectrum (Nyquist plots) with the fitted data at different temperatures.
Figure 3 shows the complex impedance spectrum (Nyquist plots) with fitted data at different temperatures.
Table 1: The values of electrical parameters corresponding to the equivalent circuit modeled by fitting processes of the measured data at different temperatures.
It is confirmed by a typical fit of the above equation to the experimental data (Fig. 4).
Wu, POWD: An Interactive Powder Diffraction Data Interpretation and Indexing Program, Version 2.1, School of Physical Sciences, Flinder University of South Australia, SA, Australia

Salwa Ben Ammou(2010) set out a hybrid data analysis method based on the combination of wavelet techniques and principal-components regression.
There are two type of wavelet transforms namely continues wavelet transform (CWT) and discrete wavelet transform (DWT) according to the length of data.
After trained by the historical data of a time series the network can capture the non-linear characteristics of the time series and make forecasting the time series in future according to a given precision.
Empirical results The sample data sets are daily SSE Composite Index at the close from 01/01 2010 to 11/31 2012 which are obtained from the Shanghai Stock Exchange (SSE).The training data started on 01/01 2010 and ended on 06/30 2012, and the testing data started from 07/01 2012 and ended to 11/31 2012.
Risk reduction using wavelets for denoising principal-components regression models .

The monitoring project, a variety of monitoring means integrated methods doesn't conform to the principle of economization, should choose the most representative project monitoring. [5] Remote automatic monitoring method according to the needs of monitoring items commonly buried fixed automatic acquisition monitoring instrument, through the field controller collect monitoring data, and then through the wireless network( satellite network and mobile GPRS network, etc.) are sent to the monitoring center.
Monitoring center set up data receiving, processing equipment, can be displayed real-time acquisition, storage, printing and observation data, and adjust the acquisition project of field data acquisition unit, sampling frequency, etc.
The equations of the partial derivative is zero, sorting and expressed as a matrix (8) In order to assure the accuracy of predicted results, it is best to use the latest data to monitor cycle fitting curve, and to eliminate the effect of random factors on can have the curve regression equation of parameters calculated residual standard deviation s. as shown in equation (9)
This article are based on selected projects using the monitoring project, forecast model and the forecast criterions The displacement - time curve is fitted ,based on the highway field condition, Compared at common forecasting model and the criterion of slope geological disaster in home and abroad, analysised the field monitoring of horizontal displacement and deep displacement data, and then combined with feature points on the two variables curve extrapolation, to predict the time of the landslide, and increases suddenly in the displacement rate of slope safety early warning, timely to the relevant decision-making departments to provide a reference basis, to make it in time to make corresponding countermeasures, the maximum to avoid the people's life and property losses.
Slope stability analysis by strength reduction[J].

Introduction The process computer which conducts the electric furnaces takes the initial and current data through the system of acquisition of data from human operator and sensor in furnaces then the computer analyses on the base of mathematical model of transformation process and the prediction of microstructures and properties a optimum strategy for conduct the industrial furnaces [1,2].
- identifying experimental model driven process, identification is performed on-line in the normal working parts inside the furnace is without the model for process management updated as input data becomes available by measurement
The system for conduct the electric furnace for heat treatments The computer with control the furnaces takes the initial and current data through the system of acquisition of data from sensors in the furnace then the computer analyses on the base of mathematical model a optimum strategy for conduct the electric furnaces.
Material characteristics, mechanical and technological characteristics Characteristics of material (at t = 20 0C) density r0=7753,6 [Kg/m3] Mechanical characteristics hardness = 22 [HRC] specific heat C0=475,42[ Wh/Kg 0C] internal stress = 920 [Mpa] thermal conductivity l0=44,51 [W/m 0C] elongation = 14 [%] reduction of section = 60 [%] charpy value = 60 [J] Technological characteristics critical temperatures the formula ASM [4] the formula Monge [4] formulas from the program Ac1 [0 C] 710,20 725,90 713,20 Ac3 [0 C] 787,26 775,72 787,24 Ms [0 C] - - 331,72 Normalizing heat treatment heating temperature [0 C] 861 heating time [second] 3660 maintaining the temperature during the normalizing [second] 1380 cooling conditions of the piece cooling on air The tuning PID algorithm together with the supervision system was implemented on a PC with system of acquisition of data from conducted system.

The final appraisal value is determined by the linear combination of the formula (5) and (7).That is (8) is the amplified factor of the final data.
Case Studies Acquisition of the Data.
This paper evaluated the regional competitiveness of the biomass energy industry according to the relative data of Yangtze River (A), the South China (B), the Southwest China (C), and Northeast China (D).
We can see from the data above that the region of Yangtze River is rich in biomass energy which also possesses advanced technology, strong financing capability and abundant labor resources.
[2] Estimates from China Statistical Yearbook 2009 and the Rural Energy Statistical Data of the Ministry of Agriculture

The basic parameters of reduction gearbox Determination of the center distance.
The center distance involved a wide range of data because of design and production for gearbox in bulk.
(4) From (1) to (4), combined with mechanical optimization design idea, build the following mathematical model: (5) (6) (7) (8) (9) After determined the mathematical model, we can program with the aid of computer programming software, then search and comparative analysis large amounts of data.
The following table is a set of data which is got by the program.
Table 2 A set of ratios data Ratios 160 180 200 225 250 280 315 355 400 1.25 1.311 1.233 1.233 1.272 1.233 1.4 1.419 1.462 1.462 1.439 1.462 6.3 6.353 6.472 6.240 6.237 6.638 6.290 6.235 6.285 6.240 7.1 7.394 7.074 7.399 7.350 7.182 6.875 7.394 6.869 7.399 Final determination of the gear module.

And at the same time it adopts a proper data fusion method to realize the overall anti-jamming capacity which cannot be achieved by an individual radar when it operates independently.
The essence is observing data from different angles and looking for the optimum pursuit method which can reflect the data characteristic at utmost and dig data information sufficiently.
The projection pursuit method is an effective dimensionality reduction technology which is applied to analysis and deal with the higher dimensional, nonlinear and abnormal problems.
In essential, p dimensional data is integrated into as the value in projected direction.
Through solving the maximum value of projection index function, we can obtain the optimal direction of projection, and fully reveal certain structure features of high dimensional data.

By sampling the sample data trains this neural network for certain steps to achieve error precision, that is the desires of inverse system,which is concatenated ahead of the induction motor speed-controlled system, making a pseudo linear system.
The input given choice covers the whole motor work area, make sure the system can get affluent enough training data.
At the same time, the sampled data should experience the secondary filter for to reduce the errors between measured value and true value
(2) The first step is to deal with the sampling data, and processed data is set as training sample.
In order to accelerate the convergence of neural network training, the first thing is to make input and output sample data of training are normalized

The useful data used for alignment is seriously polluted by harmful base angular motion formed in external perturbation, and it leads to the reduction of systematic reaction speed and precision of navigation.
So it needs to a data preprocess.
The data and frequency spectrum of FOG output shows in Fig. 1, and those of filter data are in Fig. 2.
Then it needs to reject this data and sample again, there we replace it with a random data of previous period, for the real-time character of the procedure.
The data after detection is as Fig. 5.

As a consequence, the experimental values of DHI and theoretical data on DEI are also well comparable.
As DHI0 is independent of temperature, this quantity could be good candidate for comparison to theoretical data.
Solid triangles: experimental data (AES, FIM, 3D APT); empty triangles and/or dashed line: (experimental) prediction; dotted lines: extent of the error of the values determined experimentally; solid circles: DFT values; solid squares: other theoretical data (MS, TB).
A possible explanation might consist in the used type of relaxations in the DFT data.
Other symbols including the reversed triangles are literature data for polycrystalline a-Fe [4,8].