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In this paper,the total flow calculation formula is derived by the knowledge of hydraulics, the relation of discharge discount rate is calculated through dimensional analysis and the average single hole discharge formula is established based on some experimental data.
The results of the test data and engineering data showed that the formula results and the test results are quite identical.
Figure 3 gives when the pipe diameter D = 3.5cm, slope I = 1 ‰, drip hole spacing S = 0.3m, under the first head H = 0.4m the relationship between the relative length-diameter pipe and ψ1 , inside , and for a defined diameter pipe and pipe layout length, check this article, we can see ， ,from the data fitting , combined Eq. (13) available （14） or （15） Fig. 3 The relation of ψ1 and Finally, explore the porous pipe opening rate η how to affect the reduction coefficient ψ.
Based on some experimental data fitting a porous pipe discharge reduction coefficient ψ formula: On this basis, the porous pipe total discharge and the average single hole discharge formula are established.
Xinjiang Production and Construction Corps water-saving office and the author’s experiment data show that the results get by formula and experiment are agreement, and in the process of dimensional analysis and formula fitting assume which is correct.

Data in Cleveland database comes from the Cleveland clinic foundation, is provided by Robert Detrano.
Thus, each data sample contains 20 attributes, all data samples are divided into two classes.
Second, run the attribute reduction algorithm based on the rough set theory, take 13 items of properties with better distinguish ability as reduction set, and then construct the corresponding reduction data sets.
References [1] Derchiang Li, Yaohwei Fang, An algorithm to cluster data for efficient classification of support vector machines [J].
Rough sets theoretical aspects of reasoning about data [J].Kluwer Academic Publishers, Dordrecht,1991, 39(1):110-113

(vij) = vij/max(v1j ,v2j,…vnj)*P(Fj) (3) After pretreatment of evaluation data, we can design an appropriate fuzzy clustering algorithm of entity data
Example Analysis (1) We set up the evaluation system shown in Fig.1.According to the evaluation system the factors set is established and the simulation data is shown in Table 1.
Row data is the teaching elements to be evaluated, and column data is the evaluation factors.
After the process of factors reduction a clustering evaluation algorithm based on fuzzy set has been proposed, which could decrease the data size and improve the accuracy and efficiency.
Fuzzy UTASTAR: A method for discovering utility functions from fuzzy data.

Evaluation data sources.
There are kinds of evaluation data sources in the MONE evaluation [8], such as experts’ experience data, infield simulation data, and outfield test data and so on.
Usually only one type of evaluation data are used, which allows multiple data sources support too simplistic.
But some data source cannot be used in evaluation directly [11].
How to express these data uniformly is a key problem.

China amgyang@mail.csu.edu.cn, byzq860618@126.com Keywords: Self-Anchored Suspension Bridge; Vehicle Braking Force; Viscous Dampers; Vibration Reduction.
Furthermore dynamic responses analysis and vibration reduction optimization of the bridge subject to vehicle braking force are investigated.
At last, the effect of vibration reduction with optimal parameters of viscous dampers is verified.
The empty load rate of heavy car is considered as 40% according to traffic statistical data.
Effect of Vibration Reduction On the basis of the optimal parameters C =8000 kN·s/m and α ＝0.4 of the dampers, the results of vibration reduction of Pingsheng bridge subject to vehicle braking force are calculated.

According to Gomperts model for rectangular aperture, the sound reduction index of a wall with slits can be predicted.
CUI Cheng-xun[7] studied on the sound reduction index of doors with aperture at bottom by comparing measured data and prediction extensively.
The total sound reduction index of the partition with silts can be calculated from the area-weighted sound reduction index as shown in equation (1).
From these Figs, It is indicated that the most significative decrease on sound reduction index curve is found for the slit occurrence, the increases of the width and length of the slits produce an additional but limited decrease sound reduction index below the frequency of 800Hz.
Above this frequency, the additional sound reduction index drop down rapidly, and the curves of sound reduction index exhibit the dips whose frequencies are about 2000 Hz.

Band selection algorithm is most important in data dimension reduction of hyperspectral image.
The surface image data of the hundreds of spectral bands can be got by hyperspectral sensor to form a data cube.
Band selection methods are used first to do dimension reduction and filtration, and then data fusion is done to reduce the amount of data and improve the classification quality and precision.
Data fusion quality evaluation is the important step in data fusion.
The experimental data is cut out from the big image.

Model Order Reduction in Computational Multiscale Fracture Mechanics M.
amcaicedo@cimne.upc.edu, boliver@cimne.upc.edu, cahuespe@intec.unl.edu.ar, dolloberas@cimne.upc.edu Keywords: Model Order Reduction, Reduced-Order Cubature, Fracture, Computational Multi-scale modeling, Continuum Strong Discontinuituy Approach.
This technique uses a directional derivative of a scalar field, based on a location variable (in our case, the average of mesoscale dissipated energy) whose zero level set defines the crack path. 2.2 Model Order Reduction techniques The reduction process is divided into two sequential stages.
These data, together with the material and geometrical parameters, define the set of input parameters for the first and second stage (online part).
High-performance model reduction techniques in computational multiscale homogenization.

Table 1 shows the data of elemental mass for both nanocomposites, where a slight increase in mass of oxygen is seen for rGO/Fe3O4/SiO2. the mass of carbon and ferum was decreased, possibly lost during addition of SiO2 [22].
EDX mass data of nanocomposites.
The rGO/Fe3O4/SiO2/GCE possesses incomplete and discrete semicircle (Fig. 4 (a)) compared to bare GCE electrode, hence providing data that charge transfer resistance (Rct) was greater in bare GCE compared to the electrocatalyst deposited electrodes.
(a) Comparison of electrochemical impedance spectroscopy, (b) bode phase plot and (c) proposed electrochemical circuit based on Nyquist data of bare GCE, rGO/Fe3O4/GCE and rGO/Fe3O4/SiO2/GCE in 5.0 mM K4[Fe(CN)6] of 1.0 M KCl as electrolyte media.
From the obtained data through CV of ORR in Fig. 5, the electron transfer from oxygen was calculated with assist of Randles-Sevcik equation (3) as follows, (3) For the reduction of oxygen that occurs in working electrode, it was known from the calculation that the electron transfer for bare GCE, rGO/Fe3O4/GCE and rGO/Fe3O4/SiO2/GCE were 1.3, 2.3 and 3.7, respectively.

In sum, the power consumption of electric buses and sedans are 126 kWh and 17 kWh per 100km, which are close to the news report and data statistics in China right now [12, 13].
The data of fossil energy consumption and CO2 emission are shown in Table 1.
According to data from China Statistical Yearbook 2011 and China Energy Statistical Yearbook 2011, 800 million toe of coal are consumed in power generation and heating in 2010, correspondingly 8.998 million tons of SO2 and 1.99 million tons of soot are emitted in electricity generation industry.
The data of pollutant emissions for PVBs are unavailable since the National Bureau of Statistics China did not release any vehicle emission data.
The emission data of PVBs can be obtained through National Standards from Standardization Administration of China in this paper.