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While PCA is a linear dimensionality reduction algorithm which means that it can only be used for linear distributed data.
But the PCA algorithm is a linear dimensionality reduction method, whose limit lies in that it can only reduce the dimension of the data with linear character.
PCA algorithm transforms original data into new coordinate system via orthogonal transform, and substitute the original high-dimensional data with several comprehensive data.
The comprehensive data is the principal component.
Fuzzy K-means algorithm divides data with fuzzy.

Reduction of energy costs indicates reduced fuel consumption for the process.
Reduction of operational costs is shown when using dolomite waste instead of dolomite.
Comparison of data in Fig. 1 shows that decarburization of dolomite requires more heat energy than decarburization of mixtures of dolomite and waste coal.
Based on these data, it can be stated that the production of cement from waste dolomite plus waste coal is energetically favorable.
Calculation data: - specific heat energy consumption for firing - 2008 kJ/kg of clinker; - specific consumption of conditional fuel - 70 kg/t clinker; - specific consumption of coal waste - 150 kg/t clinker; - quantity of clinker produced per year - tons per year.

The system uses the thought of data mining, which can provide the decision-making basis for sports teaching; In addition, the system structure of three layers makes the system in good adaptability and function expansibility with reduction of the maintenance workload for later.
Clustering: The data in the database is a single data storage unit, the data can’t be a single meaning of the expression, that these clusters scattered data, induction, consolidation, thereby forming a meaningful subsets [1].
Data mining is the extraction rules based on a database or data warehouse shot data which is used to guide present and future actions.
Data mining is the use of data mining technology, mining process valuable knowledge from databases, data warehouses and other information in a massive database data.
Complete data mining process, including data standardization, data integration, data conversion, data mining, pattern evaluation, knowledge representation and so on.

Automatic control technology in power generation especially in energy conservation and emission reduction is briefly introduced in the paper.
So control sulfur dioxide emission caused by the process of coal consume is key point of energy conservation and emission reduction.
Workshop process flow of smoke desulphurization Control system of wet limestone smoke desulphurization has such functions: data acquisition and storage, auto protection, automatically control and adjustment, production management.
The function of data acquisition and storage mainly include data acquisition, screen display, data process, online performance calculation, event recording and tracking.
The function of automatically protection means that PLC and host computer based on comprehensive analysis to acquired data to decide if there some accidents, then automatically alarm and take action to prevent the accident occur or extend in order to protect people and equipment.

Based on the comparative analysis on the low-noise road surface, noise reduction green belts, noise barriers and other noise reduction methods, the sound barrier is put forward as an important method for reducing the city road traffic noise.
The noise and vibration test and analysis system mainly includes multi-channel data recording instrument and front end, HPS IV Digital Playback System and so on.
Fig. 2 Data recording instrument and front end Fig. 3 HPSIV digital playback system Test point arrangement.
The result reflects the obvious noise reduction effect of the sound barrier.
The sound barrier has better noise reduction effect in the high frequency range.

What the grey theory established is to generate the data model but not the original data model, so the data in the grey prediction is the inverse processing results of the prediction got by the model GM(1, 1) which is used to generate data.
Setting x(0)(1), x(0)(2),..., x(0)(M) are the original data of certain index need to predict.
(3) Where, and B is a constructed data matrix.
For , which is the prediction of the linear accumulation generation series, we can calculate the reducing value of the original data
The choice of the original data.

The reduction effect of terrace is good and grass planting on the ridge of terrace is much better.
Method and data Eight standard runoff plots(Tab.1) of 5m×20m with the horizontal projected area of 100m2 and the slope of 12°were established on a slope.
Runoff volume and sediment volume observation data of eight standard runoff plots from 2006 to 2008(Tab.2, Tab.3) were selected to study the effect of SWC Measures on runoff and sediment reduction.
Different measures had different effect of sediment reduction.
Compared with the CK plot, each terrace had some degree of sediment reduction effect, the reduction rates of 5 plot and 6 plot were 99.6% and 90.7%.

Product Data Management (PDM) is the system which is not only storage place for the data; it is a tool which should make ECs faster and more effective.
The Product Data Management (PDM) is an engineering system which helps mainly the design engineers to handle the created data during the designing process and also during manufacturing.
Also the Product Data Management (PDM) is generally introduced by introducing it background and main properties.
The purpose is that all the data, which is created with different software, can be found from one place, from PDM.
With the help of the PDM the improvements in production, information access and data management may increase.

The issue of emission reduction has become one of the most important missions in China.
As one of the largest sources of energy consumption and pollution emission, the power generation industry plays an important role in the problem of emission reduction.
Example analysis Basic data.
However, since the regional emission reduction task is different, the corresponding regional emission reduction cost is different.
The emission reduction cost in region is much higher than those in other regions, while the emission reduction cost in region is much lower than those in other regions.

Processing methods of the line points cloud data 2.1 Preprocessing technology Generally, the data processing work can be divided into these methods, such as filtering of point cloud data, data multiple visual alignment, feature extraction, and data segmentation.
And the key pre-processing technologies of line point cloud data mainly include multi-view split, noise removal, data reduction and gridding.
Noise reduction processing can make data smooth, reduce the deviation of the model.
The main operation processes is as following: data package, interception of feature section, sheet data import to CAD, extract data as demand.
Summary Against the features of line point cloud data, establish the appropriate track model, by filtering of point cloud data, data multiple visual alignment, feature extraction, and data segmentation.