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But compare with these "massive" data, the ability of people to analyze the data and acquire knowledge exist a considerable gap, formed a "data glut" and "information poor" in a passive state.
Wisdom: Effective use of knowledge Meta-knowledge: Knowledge of the rules Knowledge: The rules of the use of information Information: Potentially useful of knowledge Data: Potentially useful information Noise: No obvious information Meta-knowledge Wisdom Knowledge Information Data Noise Fig.1 Hierarchy structure of knowledge In the hierarchy of knowledge, the lowest level (layer 6) is a noise which is almost made up of meaningless by the obscure nature of the data issues and the composition.
Level 5 is the data, some potentially significant issues.
Layer 4 is the information, is the result of a significant data processed.
The minimal attribute reduction sets is the serial code for {2,4,6,7,9,10,11,13,14}, TCF names are {Data communication, The importance of the system, Online data Processing, Multiple screens and multiple operations, Complex input and output, Complex internal processing, Code reusability, The perfect functionality and performance, Easy to maintain and modify}.

Tectonic data marts.
Data preprocessing.
Set of attributes is called after the simple attribute reduction set reduction set is usually not only find an information table reduction set, even seeking the smallest reduction set (the reduction set) with the least number of attributes is a fairly difficult NP-hard problem.
After data preprocessing, the data obtained are shown in Table 2.
We are most concerned about the properties in the sea-battlefield situation submarine threat assessment by the sea-battlefield situation data attribute reduction.

Although the sample of multivariate can provide a lot of information for the scientific research, to some extent, the workload of data collection will increase.
Factor analysis is a method to use the less independent factor variables instead of the original data.
In order to compare the effect of energy-saving and emission reduction, the basic data of power plant 3, 4, 5 should be calculated.
Tab.2 Calculation data of power plants Plant Coal consumption t/h Flue gas/(m3/h) SO2 kg/h NOx kg/h Water consumption t/h Order Power plant 3 186 1116000 68 245.5 300 2 Power plant 4 192 1152000 57.6 138.2 80 1 Power plant 5 181.8 1090800 81.8 272.7 350 3 As is shown in table 2, although the coal consumption of power plant 5 is low, compared to power plant 4, the SO2 and NOx emission per hour is higher.
According to the comparison of the computational data, the proposed evaluation method of this paper can fully reflect the situation of energy-saving and emission reduction.

These problems are caused by large-scale training sample set and outlier data immixed in the other class.
Moreover, for training the sample data mingled with outlier data in the relatively class of sample, it often can not improve the classification capability.
The ideal of SVM is to search for an optimal hyperplane to separate the data with maximal margin.
Of the 8st ACM SIGKDD international conference of knowledge discovery and data mining, Edmonton, Canada, 2002
Of SIAM International Conference on Data Mining，Lake Buena Vista, FL, USA,2004

According to the distribution of SMEs in Ningbo, Our group hands out 1200 questionnaires in total and collected back 1035, 957 of which are valid except the questionnaires whose data are clearly abnormal.
By means of analyzing and comparing information and data which has been collected, our group find out the current SMEs’ actual needs and the problems existed in implementation of relevant policy during the process of energy conservation and emission reduction.
The Main Features of Energy Conservation and Emission Reduction of SMEs in Ningbo 3.1 Basic Situation of SMEs Surveyed Table 1 Industry Distribution of SMEs Surveyed Industry Distributed (A) Machinery &Industrial Products (B ) Clothing & Textile (C) Hardware & Tools (D) House- hold appliances (E) Auto Parts & Accessories (F) Building Materials (G) Office Equipment & Supplies (H) Service (I) Others 13.99% 20.99% 12.39% 7.45% 6.65% 11.01% 7.11% 8.03% 11.93% From: Data of Survey 3.2 Situation of Energy Conservation and Emission Reduction of SMEs Surveyed 3.2.1 High cost and low utilization rate of the SMEs’ energy utilization Table 2 Energy Cost of SMEs Surveyed Energy cost /Total cost of production More than 50% 30-50% 15-30% Less than 15% 5.83% 26.66% 48.33% 19.16% From: Data of Survey As is shown from the above table, the energy cost of the SMEs is high and utilization rate of the energy is low.
Compared with the number of SMEs and their employees, valid sample size of the survey 957 is not enough, as well as the objectivity of some responses to the questionnaire. 3.Limited statistical analysis of the survey data.
Due to the limitations of our relevant professional skills, our group failed to dig out the deeper problems hidden behind the data.

These systems inherit data filtering network (DFN), automatic data interpretation, advanced CCTV camera, intelligent early warning system.
All data confirmed in the local DCEIMS will be provide to victims’ families and the media.
Backup system is used to store data.
Data from various data sources filtered through filter network share to all DCEIMS systems, education institutions and research centers through internet.
Research on sharing of international disaster data and information, Disaster, vol.3, pp.109-113, 2008

The data match perfectly well with each other.
Comparison of the data obtained by Single Pellet (TG) and Multiple Pellet (Muffle Furnace) experiments for CR/89/10C/1 at 1500oC (f-t Plot) Fig 3.
The data and figures of the powder carried out at 1350oC and 1400oC are shown in table and as f – t plots.
From these data extent of O2 removal was calculated and FR ‘f’ was obtained.
Both these data can be utilized for kinetics studies. 2.

Introduction The theory of rough sets [1], proposed by Poland mathematician Pawlak in 1982, is a mathematical method to deal with insufficient and incomplete data.
So it is a set-theory-based technique to handle data, that is, through the known information to approximately describe the uncertainty concept [2, 3].
Reduction of a -consistent covering decision system.
Reduction of an inconsistent covering decision system.
Pawlak, Rough sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, boston,1991

The data of water also shown in this figure.
The data show that coefficient of friction fibers at Re > 25.000 is lower that water data and Blasius equation.
Drag reduction occured if the data is higher than curve A.
The data is greater that curve A.
After Reynolds number about 35.000, the data shows constant.

The configuration mode of the second place is h=7mm, l=8mm, and the drag reduction rate of model with which is 32.16%. 3.Experimental analysis 3.1 Experimental equipment Drag reduction test platform of bionic jet surface include experimental section, power section, jet supply section and data collection section, whose schematic diagram is shown in Fig. 6. 1-piezometer; 2-flowmeter; 3-swivel joint; 4-torque signal coupler; 5-transmitter; 6-acquisition card; 7-computer; 8-frequency transformer; 9-variable frequency motor; 10-coupling; 11-steering box; 12-coupling; 13-water channel; 14-water pump; 15-valve Fig.6 Schematic diagram of experimental platform The way measure torque applied by experiment was converting the fluid resistance stressed on experimental model into torque, so that the data measured could reflect the actual change of resistance.
Then store the signal acquired by torque signal coupler in computer, the data acquired from different models differed from each other, so the torque could be computed by different torque signals, and then the drag reduction rates could be got.
The analog signal output by the torque signal coupler was converted by data collection system [15] into the digital signals identified by computers, based on the torque change of different experimental samples, the data measured could be acquired, dispose and store by computer, and achieve the dynamic display of data. 3.2 Experimental sample Select U-PVC pipe as the experimental carrier, whose height was 100mm, external diameter was 140mm, wall thickness was 10.3mm.
Based on the optimum configuration mode with h=8mm, l=11mm and that of the second place with h=7mm, l=8mm gained from numerical simulation, treat respectively both models with l=8, 11mm and h=7, 8mm as fixed value, select the corresponding models with h=7~11mm and l=7~11mm, as well as a sample with smooth surface to process, the total number of the experimental samples was 21. 3.3 Experimental test method The data should be collected every 0.05s, the times of the total collection are 500 under the same jet velocity.
As is shown in Fig. 9, when h=7mm, the drag reduction rates of models with l=8, 9mm are similar, and when v=1.6m/s, the proximity is best; when v=2.0m/s, the drag reduction rate of model with l=9mm can reach the peak of 22.10%, while the one with l=11mm get minimum of 21.83%, the maximum drag reduction rate and minimum drag reduction rate is within 0.27%, suggests that changes in this case l has little effect on the drag reduction rate.