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So it is a kind of effective means for increasing producing magnesium by silicon-thermo-reduction.
There are numerous applications of ANN in data analysis, pattern recognition and adaptive control.
which need to be optimized as follows[6]: the first is reduction time(t), the second is vacuum degree(P) and the last is average reduction temperature(T).
The experimental samples in Table 1 are utilized as the training and simulating data.
On the interface of predicting the rate of producing magnesium, as shown in Fig.4, the user need to input three processing parameters such as reduction time, vacuum degree and average reduction temperature.

Research of Aluminum Reduction Cell Thermal Balanced Intelligent Control System Xiangyang Xia1,a, Jie Li1,b 1 School of Metallurgical Science and Engineering, Central South University, Changsha, Hunan, 410083, China axia_xy@126.com, bsummer719@sohu.com Keywords: aluminum reduction, control system, liquidus temperature, superheat, energy saving.
This control system can reduce the superheat of aluminum reduction cell in a certain range, and reduce production cost of per ton of primary aluminum on maximal degree.
Aluminum Reduction Cell Heat Balance Intelligent Control System Aluminum reduction cell heat balance intelligent control system Schematic was shown in figure 1.
Compared with the previous control system of aluminum reduction cells, the intelligent control system achieves the automatic temperature aluminum reduction cell temperature control, mainly through the sliding mode controller and repetitive controller.
According to the upper computer software to determine the electrolyte temperature and time curve between two points under the electrolyte temperature curve before and after the formation of a straight line, determined in a straight line on the left and the farthest point from the line point and the liquidus temperature to be marked and stored data generation report.

Based on the reviewed articles, it became evident that, although numerous measurement data are available, the usability of the data is limited.
One prominent observation arising from the reviewed literature is the wealth of measurement data available in the field.
However, a critical limitation is often encountered in the utilization of this data for practical noise reduction applications.
Information Data from the articles were organized into nine categories listed below.
The collected data was compared, identifying common and differing trends among the various studies.

The experimental data were analyzed and the turbulence intensity and wind reduction ratios for different gaps of the porous fence were calculated to estimate the shelter effect of a non-planar porous fence model.
And because the length of the test section is 1600mm and within the length there is a good shelter effect according to the experimental data.
On the basis of data analysis of mean wind velocity, the following findings can be obtained: ⑴ In the region behind the porous fence models of the present experiment (x/H=13), the porous fences have obvious effect on wind reduction and dust control. ⑵ For the case of the gap ratio G/H=0.15, the shelter effect of the velocity distribution is better than other gap ratios, even is nearly the same as for no gap case (G/H=0). ⑶ The data of mean wind speed in different height indicate that if the height is less than fence height, the effect on wind reduction and dust control is rather obvious, and the wind speed is stable comparatively.
The wind reduction coefficient and the wind reduction ratio were respectively calculated in accordance with the formula (2) and (3).
Cui in measuring the experimental data.

Variables Selection and Data Description Variables selection.
Our dataset is the panel data of 9 provincial administration of Western China for the period 1990–2009.1 The data is obtained from the China Compendium of Statistic, China Statistical Yearbook 2010 and China Energy Statistical Yearbook.
Data description.
As there is lack of relevant data of Tibet, we analyze the data of the remaining 9 provinces.
We use this method to test the data.

The best drag reduction effect has been gotten with appropriate riblet structure size, with the greatest drag reduction efficiency of 9.65%.
When the viscous drag reduction is greater than the pressure drag increment, the total drag is reduced, reaching the drag reduction effect.
The maximum drag reduction rate is 9.65%.
Distribution of down-stream velocity The Figure 4 shows the curves for the distribution of mean velocity near wall when the velocity of the incoming flow is 40m/s, and these data are obtained in the near-wall region at the same point in the y-direction both the smooth surface and the riblet surfaces.
The riblet structure with an appropriate size can achieve the drag reduction in all operating conditions of centrifugal fan, and the maximum drag reduction rate can reach 9.65%, while under the designed flow, the drag reduction rate is 2.96%.

Spectroscopy study of silver nanoparticles produced by chemical reduction.
The chemical reduction process was carried out at room temperature.
The absorbance data collected were prepared with AgNO3 reagent grade.
In the case of the reduction performed by using NaBH4, the reduction of Ag ions is carried out instantaneously.
Also in this graph the absorption data of Ag NPs in solutions can be observed.

With the use of the kinetic analysis the optimal conditions were defined for the carbon thermal reduction as well as the initial data for the development of the joint carbon thermal reduction processes of zinc and iron oxides.
The data obtained through the industrial testing confirms the appropriateness of the process implementation and allows the cost effectiveness analysis of the zinc containing dust reclaiming.
According to the plant data the zinc content in the blast furnace slurries is 1 – 3 %, and in electric steelmaking slurries - 5 – 20 %.
This allowed obtaining the preliminary data required for the scaled-up experiments with the pellets at the lowest material cost.
To calculate the mass ratio of the initial and roasted samples the chemical analysis data on the total iron content was used as it is of high accuracy, and the iron at the reduction processes changes its valency but does not escape from the material.

Table 1.Summary of performance of each reduction technique.
Method Number of Species,NS Number of Reactions,NR Overall % of reduction in NS [%] Avg. % of reduction in tc [%] εID,MAX [%] DRG 431 1788 79.62 72.73 15.51 DRGASA 376 1501 82.22 78.18 13.91 DRGEP 375 1454 82.87 81.82 34.46 DRGEPSA 363 1404 82.84 83.33 34.47 Mechanism Reduction Scheme A novel five-stage mechanism reduction scheme which was applicable for large-scale mechanismreduction such as the n-hexadecane mechanism was established and presented in this section.
Superior performance of the new reduction scheme is observed with higher reduction scale and shorter computational runtime of CHEMKIN-PRO simulationsas compared to the reduced mechanisms generated from the DRG-based mechanism reduction techniques.
In this section, the reduced mechanism for diesel surrogate was denoted as NHX.ID timing of the NHX combustion was compared to the experimental data provided by Sandia National Laboratories which served as the benchmark for validation of the developed numerical models. #2 diesel (D2) fuel [11] with a CN of 46 and ID timing of 0.34 mswas selected as the reference fuel in this work.
[3] P.Pepiot and H.Pitsch: Systematic Reduction of Large Chemical Mechanisms (2005)

Size of pore after reduction determined by H2 concentration used during reduction where the higher the H2 concentration resulted in large pore size.
However, to perform reduction of NiO, several parameters must be considered namely gas type, gas concentration, gas flow rate, reduction process temperature, reduction process holding time and many more.
The bulk density before and after reduction was measured.
While after reduced under different H2 concentration, XRD data show that all peaks that belong to NiO disappeared and only Ni (ICDD file no: 01-088-2326) peak developed for all samples.
Ghosh, Reduction of nickel oxide powder and pellet by hydrogen, Trans.