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The data come from SEMI 2011 China PV industry development report [9] and the National Bureau of Statistics.
At the same time, because of limited new data (Table1), the system has much uncertainty [10].
According to the albino equation can calculate the solution of GM (1, 1) differential equations: (2) Restore the data available to the original data series prediction formula: (3) The model is applicable to non-negative homogeneous exponential function of the original data sequence. 2.2 Forecast and analysis of China's installed capacity of photovoltaic applications (1) Data processing The 2005-2010 total energy consumption, and photovoltaic applications comparative analysis of new installed capacity is shown in Table 2.
The data come from China National Bureau of Statistics.
Therefore, if directly use existing data modeling to predict, forecast results can not reflect the reality of the problem characteristics.

For a batch process, each batch of data can be viewed as a two-dimensional data matrix, multi batch data constitute the three-dimensional data matrix , where, I is the number of batches, J is the number of variables, K is the number of samples.
Because conventional PCA method does not adapt batch processes, the developed MPCA method will make the modeling data unfold according to the batch into , each row of X represents all the data in one batch.
Fig. 1 MPCA modeling After the two-dimensional process data unfold, MPCA data processing and analysis procedure is tantamount to the PCA method[6].
represents the principal component obtained by the data using PCA after time k.
Experiment are selected 12 normal batches of historical data.

Fig. 4 Thin sills tested A sample made up of more than 100 data for each feature leads to significant results.
Data Analysis Sequent Depth Ratio for δ≤0.90.
Fig. 9 shows the experimental data and their adjustments.
Moreover, for each compactness ratio δ, on a given configuration of the jump, the experimental data follows the form Y=aFr1.
The experimental data are then located by Eq. 13

The data acquisition system shall store either sampled data or statistic of data sets as follow: - Mean value; - Standard deviation; - Maximum value; - Minimum value.
Selected data sets shall be based on 10-min periods derived from contiguous measured data.
Data shall be collected until the requirements defined in IEC 61400-12-1 are satisfied.
The method of bins is a data reduction procedure that groups test data for a certain parameter into wind speed intervals (bins).
The mean wind speed and power output in each bin is calculated by the average of wind speed data and power output data in that bin.

Therefore, the purpose of this study lies in acquiring quantitative design data that can be put into the practice by comparing and evaluating the strength degradation under the environment where the moisture is absorbed by conducting static and impact collapse test after setting extreme condition for CFRP composite that takes consistent form such as frontal side members that is actually used in vehicle.
As a result of this study showed that the strength reduction of about 50% appears due to moisture absorptions.

Both these properties can be used for effective data reduction.
Several such symmetries are investigated, yielding analytical solutions that are applied and contrasted to experimental data.
Gaussians or polynomials) is appropriate and this allows data to be fitted with a very small number of parameters.
(ii) Reducing residual stress maps of all components to just a few parameters is a very effective way of data compression.
Acknowledgement All experimental data were obtained using Kowari residual stress diffractometer (ANSTO) and data in Fig. 2-4 were collected in collaboration with Drs.

Accordingly, it is necessary to reduce the results of 'constant volume' calculation to the ones of 'constant pressure' to compare them with the experimental data.
The experimental data are shown by (+).
Solid black lines and symbols are experimentally observed data for H-upward (+) and H-downward (×).
On the other hand, the referred experimental data are obtained under the constant pressure condition.
In order to compare both the theoretical results and the experimental data, we develop the translation formula by the reported scaling hypothesis.

Principal component analysis PCA is a linear transformation from a high dimensional data space to a principal component feature space.
It has been widely used as a dimension reduction technique in many applications.
a) Standardization Suppose that there are n samples and p indicators, the matrix of original data is (1) Standardize the collect data according to (2), eliminate the magnitude or dimension difference between variables.
Second, the original index data should be pretreated.
The results of index data using PCA is shown in Table 2.

The relationship between safety and curve speed in SiChuan provinces was analysed using data from the local crash database.
Similarly, field test data have confirmed that a driver’s initial speed prior to entering a curve has a significant effect on their ability to successfully negotiate the curve[3].
However, it has been shown that there is a strong correlation between a vehicle's rollover stability and its rollover crash risk which suggests that if such a speed reduction is occurring it is not sufficient to offset the increased crash risk.

Data were processed using dBFA Suite.
When studying the data in ISO 2631 [10], it is found that there is an exposure limit of 2.5 h/day, for a speed higher then 5.8 km/h in the frequency range of 1÷5 Hz.
All data were processed using dBFA Suite.
Press Inc [5] Năstac, S. and Picu, M., (2010), Evaluating methods of whole-body-vibration exposure in trains, The Annals of “Dunarea de Jos” of Galati, Fascicle XIV Mechanical Engineering, ISSN 1224-5615 [6] Picu, A., (2009), A new method for railways vibration reduction, The Annals of “Dunarea de Jos” of Galati, Mathematics, Physics, Theoretical Mechanics, Fascicle II, ISSN: 1221 – 4531 [7] Picu, A., Bălan, G., Sireteanu, T., (2009), Un studiu asupra vibraţiilor verticale transmise corpului uman, Vol. 1, 23-28, Analele Universităţii din Chişinău [8] Schust, M. et. all., (2006), Examination of perceptions (intensity, seat comfort, effort) and reaction times (brake and accelerator) during low-frequency vibration in x- or y-direction and biaxial (xy-) vibration of driver seats with activated and deactivated suspension, Journal of Sound and Vibration, Vol. 298, Issue 3, 12 pp 606-626 [9] Wuolijoki, E., (1981), Effects of simulated tractors vibration on the psycho-psysiological and mechanical