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Business data External data Business data ETL database ETL data Data warehouse Multi-dimensional data sets online analysis(OLAP) Data mining Front-end tool Query tool Reporting tools Analysis tools Figures 1.
Data dimension Data keyword(PK) Data property ...
Raw data Data mart Data warehouse Data mining training library Clean-up phase Process of building a data earehouse Integration stage Data pre-processing process Reduction phase Figures 3 Data pre-processing process model When the traditional data warehouse architecture building data warehouse, external data sources will be directly loaded into the data warehouse trough ETL tools, which has some deficiencies. 1) Since the complexity of the data pre-processing, direct integration will inevitably lead to that the process not only occupies a number of eternal operational database resources and time, but also affects the efficiency of data warehouse loading data. 2) After the source data extraction, cleaning and conversion, when transmitting to the data warehouse if there are system failures or network failures, the whole data pre-processing process will be only redone, which is a great waste of resources
Operational database Operational database Unstrauctured data Data extraction Data preparation area Data conversion Data load Data warehouse server OLAP analysis tools Data mining tools Figure 4.
The attribute X and Y has no relation ad they are independent. 6) Dimension reduction based on information gain.

The data source of an energy flow diagram is from the statistical data in the energy balance sheet for a region.
Investigation of the city’s energy flows and the major industries’ energy consumption, structure and carbon emission can provide data and decision supports to draft CO2 controlling measures for the dominant industries.
However, concerns and practices on CO2 control just starts, research on air pollutants reduction which collaborates with CO2 emission reduction is very necessary.
This model can be used to evaluate the regional air pollutants, CO2 emission and economic investment, and support data collection and decision makings.
In this paper, only current data and conditions were analyzed.

Remove the noise source data set and independent data, processing the missing data and clean dirty data, considering the time sequence and data changes.
In this paper, data cleaning work including missing values, noise data and inconsistent data processing.
The paper use FAP (Fill in with Average Poll result) [2] attribute structure on employment information, so as to evaluate analysis. 5) Data reduction.
Data reduction techniques can be used to obtain a reduced representation of data sets, although it is much smaller, but still close to maintain the integrity of the source data.
Data reduction method is adopted in this paper is: the data cube aggregation and dimensionality reduction. 6) Boolean transformation.

Rule acquisition is a hot topic in the field of data mining.
Introduction Rough set theory proposed by Pawlak [1] is an effective mathematical tool, which can deal with imprecise, uncertain, inconsistent data.
Essentially, there are only distribution reduction and assignment reduction.
Conclusions In the paper, under the model framework of the granularity of the rough set theory, we use rule extraction algorithm to mining the credibility of the implicit rules from the inconsistent decision-making system, identify data with maximum distribution reduction,which decision-making most likely to occur.
Acknowledgment This work has been supported by the National Natural Science Foundation of China (Grant No. 11205029） References [1] Pawlak Z,“Rough Sets theoretical aspects of reasoning about Data,”Dordrecht Kluwer Academic Publishers, New York 1991,pp.9-30

Lower cold rolling reductions before reversion annealing for the grain size refinement are desired in industrial practice.
However, a high cold rolling reduction to create 100% deformation-induced martensite (DIM), as generally presented, is impractical in industrial processing, and the reductions of 30–40% would be more desirable.
No data are, however, for the behavior of slightly cold-rolled reversed structures under cyclic loading.
The latter data have been published earlier in Refs. 4–6.
After 32% cold rolling reduction, there was 30% retained DA left, but only 4% after 63% reduction.

Data Envelopment Analysis Method The Theory of Data Envelopment Analysis Method.
The basic idea of this model is: Form the analysis of the sample input and output data, the model is to determine the effective decision-making unit , and to determine the production frontier.
is the copper loss of transformer Data model of line loss potential analysis of Gansu Power Grid Suppose that Line loss is x1, transformer loss is x2 and others loss is x3.
An output indicators is the whole network line loss rate, the input and output data of each decision-making unit is given by the following matrix.
(5) (6) In this model, X1i, X2i, X3i and yi are the known data.

Thus realize reduction and substitution of coal.
According to the monitoring data of Beijing Meteorological Bureau, air pollution above level six occurred four times in January 2013, and only 5 days were not fog haze day, which took great harm to people.
According to the survey data from Tsinghua University, the annual amount of coal consumption in rural areas of China in 2006 is about 192 million tons, equivalent to 136 million tce.
The survey data show that the rate of solar water heater utilization is the highest which is 84.2%.
It can be seen from the survey data that coal is mainly used for heating and the buildings are generally lack of thermal insulation, which is the key reason for high energy consumption [3].

The Model of the Al reduction cell Mathematical Model.
The finite element method (FEM) model of the reduction cell is shown in Fig.1, but the air around the Al reduction cell is not shown.
The element Source 36 is used to provide current data, and need to predefined geometry; the element Solid 117 includes 20 nodes and is used for the static magnetic analysis.
Fig. 1 Schematic diagram of pre-bake anode Al reduction cell Fig. 2 FEM model of Al reduction cell Calculated Results and Analysis.
Fig. 3 X magnetic intensity of the Al of the Al reduction cell (Tesla) Fig. 4 Y magnetic intensity of the Al of the Al reduction cell (Tesla) Fig. 5 Z magnetic intensity of the Al of the Al reduction cell (Tesla) Fig. 6 Sum magnetic intensity vector of the Al of the Al reduction cell (Tesla) Fig. 7 X magnetic intensity of the electrolyte of the Al reduction cell (Tesla) Fig. 8 Y magnetic intensity of the electrolyte of the Al reduction cell (Tesla) Fig. 9 Z magnetic intensity of the electrolyte of the Al reduction cell (Tesla) Fig. 10 Sum magnetic intensity vector of electrolyte of the Al reduction cell (Tesla) Fig. 11 X magnetic intensity of the cell wall of the Al reduction cell (Tesla) Fig. 12 Y magnetic intensity of the cell wall of the Al reduction cell (Tesla) Fig. 13 Z magnetic intensity of the cell wall of the Al reduction cell (Tesla) Fig. 14 Sum magnetic intensity vector of the cell wall of the Al reduction cell (Tesla) Fig.12~Fig.15 are the X, Y, Z and the magnetic

The abstraction of diagnostic feature from field condition monitoring data is a significant research challenge.
CCM Based Dimension Reduction 3.1 Dimension Reduction The degree of correlation between two parameters is represented by correlation coefficient, whereas CCM represents multi-parameter correlations.
(4)Set the correlation factor threshold T=0.80, and run the reduction steps in Matlab, the dimension is reduced to 9
The original feature vectors have 18 elements each before reduction, all of which belongs to three classes.
The test shows that after reduction the recognition rates are equal or even higher than that of before.

Additionally, the urea and fuel consumption and ammonia leakage have been compared and analyzed respectively, the experiment data indicates that the urea water solution consumption ratio is only 5.7% of fuel for this SCR system, while its average ammonia slip is below 5 ppm.
The engine is operated with a comparably high NOx raw emission, after using SCR system, a large reduction in NOx emission.
However, the experiment data indicates that urea water solution consumption ratio is only 5.7% compared to fuel used for the SCR system.
Marti, NOx-reduction in diesel exhaust gas with urea and Selective Catalytic Reduction, Comb.
DaCosta, Urea thermolysis and NOx reduction with and without SCR catalysts, Applied Catalysis B: Environmental 46 (2003) 17-34