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Then the data after reducing dimensions was used as the input of artificial neural networks (ANN) to classify steel samples.
So it has increasingly become a difficult problem in LIBS analysis to extract useful information from the raw spectral data and reduce the dimensions of the original data.
Data sets: Two data sets were used to verify the classification ability of the model.
PCA data reduction method is a good analytical approach considering this method does not need human intervention and can be developed as an automatic solution.
Conclusions We acquired spectra of 27 steel samples by LIBS and used two methods to reduce the dimensions of the data.

Energy conservation, consumption reduction and emission reduction are inevitable choice for an enterprise on technology improvement and sustainable development.
It suffers a heavy pressure on the energy conservation and emission reduction.
This suggests that oxygen-enriched combustion indeed have effect on energy saving and consumption reduction. 3.3.2 The influence caused by enriched oxygen on energy consumption of producing clinkers In the normal production, Jiahua cement clinker sintering energy consumption can meet the design index and close to the domestic advanced level during the Oxygen enriched test(generally production line of about 750 kCal / t, the advanced level of 650 kCal / t, the production line design value of 740 kCal /t); (1)Oxygen-enriched during the trial make average clinker claiming reduce energy consumption by 2.07%,every day is equivalent to the 15 tons of coal (if it is a high-quality coal, the coal saving rate will be higher); (2)Test data analysis shows that, oxygen-enriched combustion mainly in the kiln head quarter in coal is obvious, the average of 8.38% firing fuel consumption is decreased , the kiln outlet coal is decreased by 1.49% on average (according to the data in table 13 can be disassembled
The daily amount of CO2 emission reduction is 24.2t / d, according to 320 days per year in calculation.
Every year the CO2 emission reduction is 7744 t/a, which is beneficial for society. .

Efficient data mining model design for a large database in the cloud computing environment ZHAO Zhan-kun Hebei Software Institute, Baoding Hebei 071000 Keywords: cloud computing; Data; mining model; Abstract: Efficient data mining model design for a large database in the cloud computing environment is studied.
Therefore, looking for effective data mining methods for large databases, has a very broad space for development in the field of data processing [2].
Due to the amount of data in the large database is gradually increasing, making data in large database presents a strong diversity under cloud computing attributes environment, leading to during the process of data mining in large database based on the traditional tree-based PSO method, the adopted data main element characteristics and associated features have significant volatility, resulting in unable to obtain accurate data mining results [3].
Reduction method based on a new fuzzy rough set in fuzzy information system and its applications to scheduling problems[J].Computers & Mathematics with Applications,2005,51(9-10):1571-1583
Data Preparation for Web Log Mining [J].

Data from different repositories (eq.
Data processing chain from the physical values to the stored data in the data repository.
Recorded building data can be split into two main groups in general, periodic data and event -triggered (or event-related) data.
Example of generated periodic data set (red) based on typical data from an occupancy sensor (blue).
This can be useful if the data is subjected to analyzing processes using binary input data.

Also, more simply (and without material substitution), many suspension and chassis parts can realise secondary mass reductions from reduction in their size that result from mass reductions elsewhere on the vehicle.
Automakers embrace AlMMCs The race for mass reduction.
Likewise, Nissan has a target of a 15% reduction by 2015, representing over 227 kg reduction from their 2008 average light duty vehicle [13].
It was noted that there was need for systematic database that relates properties to processing parameters or between laboratory test data and actual performance.
Validated property data sets for AlMMCs were needed in the form of design allowances for product design, and as inputs for Finite Element Analysis (FEA) as well as for microstructural modelling [37].

Effect of Argillites Reduction Ratio on Ceramic Tile and Paving Clinker of Low-Temperature Sintering A.V.
In given intervals of reduction ratio and firing temperature the index of water absorption capacity of less than 5 % needed for ceramic tile is achieved by size reduction of 0 – 0.315 mm and firing temperature of 1000 °C and higher.
For Vladimirovskoye deposit in given intervals of reduction ratio and firing temperature the index of water absorption of 5 % is achieved by size reduction of 0-0.315 mm and firing temperature of 1050 °C and higher.
Considering that laboratory data, in principle, don`t entirely have to focus on upper limit values, we can use an average index of water absorption capacity of 1.5 % for paving clinker and 3.5 % for ceramic tile.
In this case, the necessary indexes are achieved at higher firing temperatures and finer reduction ratio of the raw material.

However, due to the high sulfate concentration (around 850 mg/L) in influent, sulfate reduction will be stimulated in CWs.
In this study, nitrite and nitrate were used as competitor with sulfate for electron acceptor to prevent the sulfate reduction.
For instance, the cumulative mass removal based on one-year operating data approached 80% for benzene and 88% for total BTEX in a study of pilot scale upward vertical flow mode wetlands equipped with subsurface aeration lines [6].
Results and discussion Both nitrate and nitrite out competed dissimilatory sulfate reduction successfully and there was no difference in the addition of nitrate and nitrite on the influence of sulfate reduction (Fig. 1).
Conclusion Plants can stimulate dissimilatory sulfate reduction by the release of organic carbon from their roots.

It is needed to reduce the input data set by using the data preprocessing method in order to reduce the complexity of the BP neural network computing and speed power load forecasting.
Then for any period i, the influencing factors of power load data and historical load data constitute an object xi={A1,i, A2,i, … , Am,i, yi} on the field U={x1,x2,…,xn}.
Discretization of the Attribute Values of Training Samples Since the rough sets theory can only deals with discrete data, we discretize the data using method of the fuzzy membership function [4].
Data from July 1 to July 15 are the training samples, and data from July 16 to July 22 are the test sample.
Chen: Warehouse and Data Mining (In Chinese).

Reduction of Hematite by Electrical Discharge Assisted Milling D.
Preliminary discharge milling experiments performed under arc conditions have demonstrated that this technique can be employed for initiation of reduction reactions in metal oxides.
However, further reduction of magnetite to FeO [6] during room temperature milling has proved more difficult, in part, due to the large positive free energy change associated with the latter reduction reaction.
XRD outputs were analysed with Traces Software (GBC Scientific) with search-match capability using the International Centre for Diffraction Data (ICDD) powder diffraction file, 2003 Version (PDF-2).
Semi-quantitative EDS analysis of large sample areas revealed increases in average iron content with increases in milling time, confirming that chemical reduction occurred during discharge milling and that the amount of reduction increased with increasing discharge milling time.

Rough set theory Rough set is primarily applied to process and analyze various data of incongruity and inaccuracy to discover intrinsic knowledge and reveal potential rules.
In the grey relational analysis, the data which contain the same features are regarded as series.
(2) We possibly use the existing historical data for analysis.
If there is no existing data, we can by means of questionnaire survey and other methods to collect data
(3) As different data generally have different dimensions,data is required for appropriate transformationin order to make different dimensions compared