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This paper presents an adaptable controlling approach on account of the mathematic modeling and the quantitative analysis of experimental data on a ring-coupling controlling structure.
Put forward an algorithm to predict the current value trend of offset using historical data, and adjust the motor torque given value according to the predictive value, further improving the synchronization performance.
The control structure is a close-loop control for synchronization indicator, and can effectively improve the synchronization performance combined with the data driven control algorithm.
PLC is used to achieve real-time monitoring of the experimental data and varying control methods.
Put forward an algorithm to predict the current value trend of offset using historical data, and adjust the motor torque given value according to the predictive value, further improving the synchronization performance.

total capacity interval type Line interval margin The ratio of the number of unused line interval and the total number of existing line interval and future expansion line interval interval type Smart and green Intelligence level of distribution network Proportion of smart distribution network capacity Statistics the ratio of smart distribution network capacity and the total distribution network capacity benefit type The number of “plug and play” charging stations of end-use equipment Statistics the number of “plug and play” charging stations of end-use equipment in the area benefit type Proportion of smart meters The ratio of smart meters and total meters in the area benefit type Supply capacity of Distributed Energy Capacity of Distributed Energy accessed to the system Distributed Energy capacity interval type Utilization ratio of Distributed Energy The ratio of Distributed Energy average power and Distributed Energy capacity accessed to the system benefit type Energy- saving emission reduction
CO2 emission reduction Calculate CO2 emission reduction by converting the capacity of Distributed Energy accessed to the system benefit type SO2 emission reduction Calculate SO2 emission reduction by converting the capacity of Distributed Energy accessed to the system benefit type Controll- able risk Accident risk Load reduction ratio in N-1 faults The ratio of load reduction in N-1 accident interval type Load reduction ratio in N-1-1 faults The ratio of load reduction in N-1-1 accident cost type Investment risk Dynamic investment pay-back period Time that net earing of project consumes to counter the all investment, the smaller the indicator, the smaller the finance risk of the system investment cost type Internal rate of return Discount rate that makes the cash flow NPV of the series income and expenditure zero, the bigger the indicator, the stronger the system ability to resist economy risk benefit type Ability to withstand risks Ability to withstand natural disasters Ability to withstand
nature disaster in different nature disaster situation, including the design standard of important equipment, disaster protection and Repair resilience ability, etc. qualitative index Ability to against other risk (human or external force damage) Ability to withstand man-made or external damage(e.g., electric equipment damage, theft, etc. caused by line construction), important power plants, substations and equipment security, the secondary protection measures, etc. qualitative index Social benefits The degree of popularity of rural electricity Rural household energized rates Count the proportion of electrical rural residents to the total number of residents benefit type Each household each ammeter rate Count the proportion of the number of rural residents achieved each household each ammeter to the total number of residents benefit type The harmony power supply Customer Evaluation Satisfaction Measure the degree of customer satisfaction reduction caused by power failure benefit type Comprehensive
Consider the case: transformer capacity-load ratio is 100%, the reasonable range of indicator is [4.11,5.27] (MW), which is also consistent with the planning data.

The result showed that: the reduction of energy intensity in the past decades was attributed to the improvement of industries’ energy efficiency, especially the improvement of secondary industries’ energy efficiency.
Based on analysis on dynamic characteristics of energy intensity in three industries of Anhui province from 1995 to 2009, decompositions of energy intensity’s dynamic change was investigated proceed year by year, by the Laspeyres model. 1 Research Method and Data Source 1.1 Disaggregation Model Disaggregation model is one brand-new and mature analysis approach based on input-output techniques.
(7) 1.2 Data Source Using the data of statistic books, GDP , triple industrial value and energy consumption from 1996 to 2009 were collected in Anhui.
Then, according to the given data, energy strength our industrial structure in different phases were calculated. 2 Variational Trend of Energy Strength in Anhui Table 1 shows the variation of energy strength of our industrial structure from 1995 to 2009.

When it arrives the maximum power point or so, the least square method is evaluated basing on the experimental data, then calculated the point.
Finally the maximum relative error is given between the evaluatal value and experimental data.
Although the size of the generator has been reduced, the speed increasing boxes the loss, weight, noise and require regular maintenance which leads to the increase of operating costs and reduction of reliability [4].
The establishment of Grey GM (1,1) model and curve fitting of least squares GM (1, 1) model is the basic model of gray system theory. it is done through the accumulation of raw sequence, to get the new more regular sequence, and then using the differential curve fitting to accurately approach the development trend of the data sequence.
Table 1 The predictive and actual values of GM(1,1) at 8 m/s wind speed one-step predictive two-step predictive three-step predictive four-step predictive five-step predictive GM(1,1) predictive power /W 931 1084 1255 1409 1572 Actual power /W 855 1029 1186 1355 1504 The relative error /(%) 8.89 5.34 5.82 3.99 4.52 Conclusions This paper analyzes the characteristic of ,maximum power curve of wind driven generator .Through gray predictive model with the features of less needed data , high predictive precision and without priori information, this paper puts forward a new method to track maximum power point in direct-drive wind power generation system.

Data integrity and coherence VIII.
The customers can access to the sever cutter technique parameter planning software, the material information, machine tool information, tool information and cutter feeding data base via internet.
One standard workpiece program is used to trigger data gathering and allocation, and manufacturing.
Measuring data is transferred to database (SQL or ORACLE) as quality control tracking information.
(3) The valuable market information, data and knowledge about manufacture can be consistently obtained in order to support Internet utilization rate

Bar chart is the most common graph when we need to process some data counting, analysis and comparing.
Bar charts are used for plotting discrete or discontinuous data which has discrete values and is not continuous.
A bar chart is very useful if you are trying to record certain information whether it is continuous or not continuous data.
According to directness and convenience, it is wide used in representation of same kind data, especially among statistic analysis.
It is a complete package for the interactive reduction, analysis, and visualization of scientific data and images which was widely applied in many fields.

Finally, support vector machine (SVM) is applied to classify the modelling data.
To deal with it, some methods were used to extract features from those large amounts of data.
Secondly, the proteomic expression data are modeled by MMC.
Finally, support vector machines (SVM) method [12, 13] is used to classify the modeling data.
Data Min.

Reduction of the flow from supersonic to such speed is combined with pressure reduction.
The results from the numerical analysis are then validated by comparing with the experimental data.

The concept of composite with technological role based on creating new complex metal matrix with solid particles in granular form has multiple purposes, among which we mention reduction of pollution in steels department and reduction of economic losses through recovery and reusing of granular ferroalloy particles.
Results and discussion The experimental program for obtaining the composite material A6061/SiC comprises data and conditions shown in Table 2.

Data on the mechanical properties of masonry walls from the materials used in Montenegro are scarce.
Some of them were testing in-situ and data of the mechanical characteristics of the stone walls were published.
There is no published data about mechanical characteristics masonry walls made of clay brick block or concrete block from the Montenegro researchers.
Method of processing data obtained by the experiment is defined by the standard.
Appreciation Implementation of the project SROKO "Seismic risk reduction for buildings of stone and brick" is held under the auspices of the Ministry of Science of Montenegro.