Search results

In accordance with the statistical data from Baoshan Iron & Steel Group Company, the content of steel slag is the amount of each additional 10kg/t in the raw sintering material, the phosphorus content of sinter will increase by about 0.0038%, the phosphorus content of molten iron will increase accordingly 0.0076%[2].
Therefore, we can add a reducing agent to the sintering process, after the reduction of phosphorus is removed in the form of gas.
Current Situation of Reducing Dephosphorization in Steel Slag Microwave dephosphorization Lv Yan et al[5] adopted the microwave method to do the experimental study of microwave carbothermal reduction phosphorus of slag.
Li Guangqiang, Zhang Feng et al[7] study dephosphorization of the converter slag to adopt the high temperature carbothermal reduction method and analyse the dephosphorization effect of converter slag in the induction furnace at 1650℃ and 1800℃.
273.15=1287℃ After adding SiO2, the starting temperature of reduction can be decreased, and the temperature can be reached at the combustion layer, so the reaction can occur in the sintering process.

At present, the development of power industry is facing the pressure of energy saving and emission reduction.
Power industry as the large user of energy production and consumption is the key field of energy saving and emission reduction.
At present, energy conservation and emission reduction is arduous task in the "11th five-year" plan.
It is of great significance for energy conservation and emission reduction in power industry to finish "11th five-year" plan.
[13] National Coal-fired Units Technical Association, “Competition data analysis of national thermal power plant units (600MW grade) in 2008,” Electric Power Technology,vol.6,pp.1-3,2009.

Reduction of cracks is important for the improvement of slab quality.
The heat treatment method was also employed to restore the plasticity margin destroyed in cold plastic deformation and to avoid damage by Kolmogorov et al [13], and experimental data indicated that the micro-damages in metal materials heal.
(1) where, is the shear strength, is the reduction ratio.
When the reduction ratio reaches 20~30%, as the reduction ratio further increases, the size and the number of dimple fracture zones increase (Fig. 7 (c) and (d)).
When the reduction ratio is less than 10%, the shear strength of crack healing zone increases linearly direct to the reduction ratio, and as the reduction ratio further increases, the amplification of shear strength of crack healing zone gradually decreases

It was approved that the prediction precision was obviously enhanced compared with the practical data for vertical rolling force.
Thickness is 200 mm, width is taken from 40 mm to 1600 mm, rolling reductions are 20 mm and 50 mm.
Fig. 3 and Fig. 5 shows the changes of vertical rolling fore with the change of the thickness, width, reduction of slab.
Taking Tselikov empirical formula from experience of experimental data as regression model, rQ is obtained through regression by MATLAB.
Vertical rolling forces of 1780 hot strip mill in some steel are calculated using the obtained formula in the article, the results noticeably improved the accuracy compared to the field data.

Clay is the primary cause for resistivity reduction in most of the low resistivity pay cases.
The resistivity data must correct for the influence of these conductive minerals to decrease the calculated water saturation to extra reasonable ranks associated with water free hydrocarbon production [2].
The reasons of low resistivity pay’s occurrences can be described through the study of geological, petrophysical and reservoir engineering data.
Thus the reduction in resistivity would be larger in this type of formation.
The data in Table 2 shows that calcium oxide (CaO) is present in major quantities while other minerals are present in trace amount.

It can reduce the data dimension, and also retain the key messages of the data set.
For data point xi, if data point xk make R(i,k)+A(i,k) meet the maximum of R(i,j)+A(i,j), j=1,…,N, then data point xk is the clustering center of xi.
By this way, the data dimension is reduced, and most of the data informations are also retained.
Silhouette reflects the tightness of data points within one class and the divisibility of data points from different classes.
So after dimension reduction we get a better clustering quality.

The corresponding data are collected in Table 1.
On cathodic scanning, compound 1 exhibits one reversible reduction wave at -0.66 V versus Calomel and the second irreversible reduction wave at -0.89 V.
Compounds 5 also exhibit two reduction waves.
The optical band gap (Eog) levels, the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO) of these compounds were determined from their electrochemical data and their absorption data.
TABLE 1 OPTICAL AND ELECTROCHEMICAL PROPERTIES AND BAND GAP DATA OF COMPOUND 1 AND 2 Compound λonset(nm) E0g(eV) LUMO(eV) Ered(eV) HOMO(eV) 1 5 543.93 581.40 2.28 2.13 -3.74 -3.80 -0.66 -0.60 -5.93 -6.02 Eog= 1240/λabs onset

But, [8] verifies the non-existence of the energy the environmental Kuznets curve by using the world's total energy consumption and GDP data of 113 countries.
Due to the missing of total energy consumption data in  Hunan, therefore, Hunan province relevant data is not listed  in Central region.
Furthermore, in view of the division of  Chongqing from Sichuan in1996, Sichuan and Tibet do not have an associated energy consumption data, therefore, the above three provinces are not included too.
[9] Phu Nguyen-Van.Energy consumption and income: A semiparametric panel data analysis.
An Empirical Study of the Environmental Kuznets Curve for China’s Carbon Emissions——Based on Provincial Panel Data,Vol.9(2011),p.66-76.

When the number of training samples are large,solvingwill take more time and space.However,increase remembrance algorithm can avoid this problem,its general description is: When there are n samples in training data,given,,,,equation(9),(10) can be written as: (11) (12) (13) When the number of samples in training data increases two,that is to include sample into original training data w,we have: (14) (15) (16) Here,,, is constituted by plus 1 column and 1 row,that is: (17) From equation(14) to equation(16)，we can know that,if we know,we can solve the value of ,,.In order not to calculatedirectly,but calculate it
, it doesn't insert all samples as support vector at a time, but increases two training samples in turn by the entropy biggest principle based on the initial training sample data.
Experiment and Result Analysis The origin and selection of sample.These research data of this article are from the CSMAR database,this article chooses 167 listed company of A stock market between 2002 and 2007 as research sample randomly from Shanghai and Shenzhen two stock markets, rejects finance class samples and samples whose data are not entire, and takes these left 152 samples as the final research sample.Thereinto,50 samples are test samples, other 102 samples are training sample.
Preprocessing of target data.This article uses traditional factor analysis method and neighbourhood rough sets reduction method to preprocessing pre-election indexes respectively.
It uses reduction algorithm based on neighborhood rough set to select targets on the basis of standardizing the 31 candidate target.In order to compare with the classical rough set method, we introduce CART classification learning algorithms in the experiment,the specific steps are:for the classical rough set attribute reduction,first use Equal frequency binning algorithm of Rosetta software to discretize data,then use Johnsonreducer algorithm to attribute reduce discretized data;for neighborhood rough set attribute reduction,use forward greedy numerical attribute reduction algorithm of MATLAB 7.0 to attribute reduce data.Because the attribute reduction number is influenced by the size of neighbourhood δ, this article use 0.1 as steps of δ, δ ranges from 0.1 to 1, and the results shows that, whenδ = 0.9,the classification precision is optimal(get the highest classification precision by the least number of attributes).Table 2 shows the attribute reduction circumstances of the two methods

Reference [1] focused on the numerical simulation of nine roller H-straightening, on the occasion that only one of the roller reductions changes, the other three rollers do not change, then it discussed the impact to residual stress of straightened rail caused by the reduction.
FEM Model Foundation of Rail Straightening Through the data of certain factory, the limited value of original bending curvature radius is 63m.
Experimental Plan Design In rail actual compound straightening process, the reductions of 2#, 4#, 6# and 8# roller in the H-straightener can be adjusted, the reduction of 11#, 13#, 15# and 17# roller in the V-straightener can also be adjusted.
In the on-site actual straightening regulation, 17# roller in the V-straightener does not roll down, the reduction value is 0mm, the active reduction value of 2#,4#,6#,8#,11#,13# and 15# roller are respectively 19.2mm,11.2mm,7.9mm,3.5mm,12.0mm,6.0mm and 2.5mm.
Tian: Experimental Design and Data Process (Chemical Industry Press, Beijing 2005).