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In this paper, a temperature robust alternative approach is being considered by using a PCA statistical data driven model of the guided wave pattern.
In general, it is reported a magnitude reduction when the temperature is increasing [4].
In SHM PCA-based, data is arranged in a matrix X as follows in Eq. 2 Χ=x11 …xi1x12 …xi2……… x1j …xij…xni …xn2 …… …xnj=ϑ1ϑ2…ϑj…ϑn
The first one is based on analyzing the residual data matrix to represent the variability of the data projection in the residual subspace.
The principal components (the first 60) are determined using the data of the extended baseline.

This method firstly relevantly deals with the collecting road signals, then getting Permutation Entropy (PE), and reaches relevant drawing data array.
On the other side, the quality of reference data can also be provided upon construction acceptance while anticipation is given upon road maintenance.
Algorithm Flow Chart shows as follows: Fig.2 Algorithm Flow Chart To testify the validity of the proceeding PE algorithm in examination of vibration signal, we will take the actual data collected from aboard as the original data samples in order to get its PE [11].
The close data point of subsequence is t, and this subsequence will use the largest overlap circumstances, which move the subsequence a data point backwards to get the next subsequence [12].
Calculating PE of each subsequence, then we will get a data point which PE assigns subsequence.

We explore two techniques: principal component analysis (PCA) and forward feature selection (FFS) for dimensionality reduction.
PCA was explored initially since it provides an automated approach to dimensionality reduction, however, it is not easy to gauge significance of individual features in terms of predictive power using PCA, hence the need to explore FFS.
In FFS, we first choose that feature that correlates the best with subjective scores on the training set; then, that feature which correlates the best with subjective data in conjunction with the first feature is chosen.

Some research data show that the framework of the structure of the seismic damage occurs in the column and beam oer-sewn distally, node by the beam end and column end under axial force, bending moment and shear force, they work together and complex stress state.
Part of the test results and the empirical formula by some countries (such as: the United States, Canada, etc.) of the concrete specification. 1) the United States in the early 1950 s, the test floor column concrete strength is lower than the practice of concrete strength, and was started in 1963, in its concrete specification ACI318, f'ce=0.75 f'cc+0.35 f'cs≤f'cc (1) In the formula，f'ce—Beam-column node reduction strength of concrete； f'cs—Strength of concrete slab (beam)； f'cc—The column of concrete strength。
2) Canada CSAA23.3-94 has a similar norms, the calculating formula for f'ce=0.25 f'cc+1.05 f'cs≤f'cc (2) In the formula，f'ce—Beam-column node reduction strength of concrete； f'cs—Strength of concrete slab (beam)； f'cc—The column of concrete strength。

The bending resistance of the girder can be approximately evaluated with the following relations: Upper subpanel Class 1 or Class 2: (4.a) Upper subpanel Class 3 or Class 4: (4.b) where: - is the bending girder resistance considering that the stiffener is perfectly rigid; - K is a reduction coefficient determined in such a way that the stresses (Figure 2) should not be exceeded in the stiffener area:.
The reduction factor K Analysis example A comparative analysis regarding the pure bending resistance of a plate girder with a longitudinal stiffener located in the compression zone of the web is performed in this worked example.
Design data: Girder cross-section: web 2600x12 mm, flanges 650x30 mm; the girder stiffeners are at the distance of 2500 mm and have sufficient stiffness to create nodal lines for the buckled web; steel S355 for all girder elements.

With the same azimuth resolution, it can achieve much wider swath than conventional SAR due to the reduction of PRF. sub-band synthesis algorithm can improve the range resolution while effective phase center sampling is overlapped.
Comparing with conventional SAR, it can reduce the PRF with the same azimuth resolution, the reduction of PRF can widen the width of the swath.
Digital signal processing of synthetic aperture radar data: algorithms and implementation [M].

Data integrity and coherence VIII.
The customers can access to the sever cutter technique parameter planning software, the material information, machine tool information, tool information and cutter feeding data base via internet.
One standard workpiece program is used to trigger data gathering and allocation, and manufacturing.
Measuring data is transferred to database (SQL or ORACLE) as quality control tracking information.
(3) The valuable market information, data and knowledge about manufacture can be consistently obtained in order to support Internet utilization rate

Bar chart is the most common graph when we need to process some data counting, analysis and comparing.
Bar charts are used for plotting discrete or discontinuous data which has discrete values and is not continuous.
A bar chart is very useful if you are trying to record certain information whether it is continuous or not continuous data.
According to directness and convenience, it is wide used in representation of same kind data, especially among statistic analysis.
It is a complete package for the interactive reduction, analysis, and visualization of scientific data and images which was widely applied in many fields.

Finally, support vector machine (SVM) is applied to classify the modelling data.
To deal with it, some methods were used to extract features from those large amounts of data.
Secondly, the proteomic expression data are modeled by MMC.
Finally, support vector machines (SVM) method [12, 13] is used to classify the modeling data.
Data Min.

The GM(1,1) model do the 1-AGO to the original data firstly, and then fitting a index curve to do the forecasting, finally, by doing the 1-AGO can get the predictive value.
Do the data reduction that we can get (1-2) The equation (1-2) is the prediction equation of the GM(1,1) model.
The verhulst model is based on the equal-interval sequence, but because of the various impacts of external uncertainty, the data sampling often shows the non intermittent.
Experiments and Evaluation In order to verify the effectiveness of the proposed model in this paper, we use the electric load data of certain area in recent years to do some experiments.
The original data is shown in Table 1.