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The paper analyses two categories, five terms characters of mountain disaster, which supported by statistics data.
Disaster prevention and reduction to the human settlement construction is basic function, which needs theoretical support by human settlement.
Therefore, the important issues on the mountain town disaster reduction and prevention should be the mountain properties.
Theory Support for Disaster Prevention and Reduction in Southwest Mountainous Cities The Necessary of Theoretical Guidance.
Disaster Reduction in China, 1996,6 (4) , p.39 ~ 41

Introduction The original features extracted from test data in mechanical fault diagnosis can characterize device state[1].
is the number of testing data points.
represents the kernel matrix for the testing data points.
Acceleration signals were measured using the Dewetron 16 channels data acquisition system and the IMI 603C01 accelerometers.
The data was stored in .mat format for further Matlab operation.

It was found that higher content of additives gave larger thermal reduction and larger microsphere (RM1) gave a larger thermal reduction than that of the smaller ones (RM2).
Reading data were recorded every 10 seconds until the reading temperature going to constant.
After that the reading data were collected every 5 minutes for 1 hour and 40 minutes.
This is in accordance with the surface temperature data which indicating that 28 %wt or more of TiO2 can provide sufficient solar reflection and enhances thermal reduction.
It is also suggesting that the single reflectance data is not suitable to represent the thermal protection property of the roof paint.

Reduction of GO by TGA.
In order to ensure the reduction of GO by TGA, hydrochloride reduction of GO was carried out to compare the quality of TGA to that of the hydrochloride reduced GO.
This is attributable to the partial reduction of GO to graphene.
These XPS data suggest that the oxygen-containing functional groups have been partially removed restoring majority of the conjugated graphene network after reduction.
Cheng, The reduction of graphene oxide, Carbon 50(2012)3210-3228

For NIR data has the character of high dimension, nonlinear, and high noise, we often confront the problem of dimensionality reduction when building the classification model on Near-Infrared spectra data.
Recently, nonlinear dimensionality reduction methods are applied in the spectra data like Isomap [5] and LLE [3].
Firstly, preprocess the training data and do nonlinear dimensional reduction by using S-Isomap.
Table 1 NIR spectra data of five brands’ cut tobacco Dataset No. classes No. variables No.samples NIR data 5 1609 80 Dimensions Reduction.
After KLLE dimension reduction process, the information of embedded data has a little loss.

A private cloud is a proprietary network or a data center that supplies hosted services to a limited number of people.
Through the enterprise private cloud, a factory can obtain the device service, the software service, model service, the data service, the information service and knowledge service from the public cloud.
In addtion, the service cloud should supply safe data storage for the users to record, look up, manage, and reuse their manufacture process data.
According to the business requirements from energy-saving and emission reduction and the new related technologies in this area [7-9], these key technologies are: pinch technology for device improvement in energy-efficiency, the coupling modeling technology to describe the nature of the coupling relation between production and energy consumption, computer simulation for calculate the possible energy-consumption value by reproduction in a virtual environment, dispatch optimization technology, evaluation technology for energy-consumption efficiency, data mining technology for energy-saving oriented etc.
Conclusions Both of global climate improvement and manufacture cost-reduction require the people to make endeavor in work of energy-saving and emission-reduction.

Technological Transformation for Loss Reduction in Power Networks in Low-carbon Economy Energy Saving and Consumption Reduction.
Technical transformation for loss reduction could help optimize, refine and quantify loss reduction measures.
Tab. 1 Projected National Percentages of Thermal Power and Average Coal Consumption of Electricity Generating (×10-6) Year 2013 2014 2015 2016 2017 2018 Percentage/% 80.58 79.81 78.93 77.95 76.84 76.12 Coal Consumption/t/kWh 335 332 329 326 322 320 Data from: http://news.bjx.com.cn, http://www.lib.hust.edu.cn/xueke/slsd/wszy/dl.htm, etc.
Tab. 2 Predicted Electricity Saving Amount (×10-6) and Transmission Loss in Distribution Network of the Studied Company Year 2014 2015 2016 2017 2018 2019 Electricity Saving Amount/kWh 32.28 40.56 45.34 49.76 52.18 54.45 Overall Transmission Loss/% 4.8 4.6 4.5 4.4 4.3 4.2 Data from: the studied power supply company.
With the above data and assumptions substituted in the emission reducing model introduced in the last section, the developing trend of low-carbon benefit of the company, by the implementation of technical transformation projects for loss reduction, in the next five years was plotted, as shown in following Figure 1.

H2: Waste reduction subjective norm has a positive influence on RBI.
In general the response rate was 100%, but since ten questionnaires later were discarded because of missing data, the effective response rate was approximately 98%.
Findings and Discussion SEM using AMOS version 20 [11] was applied to the data in order to test the hypothesised saturated model.
Overall fit indices showed that the hypothesis model fit the data well: x2 (df = 184, N = 470) = 411.056 p < .05, CFI = .924, PGFI = .737, RMSEA = .051 (Low = .045, high = .058).
H3: Predicts that, waste reduction perceive behaviour control has a positive influence on reduce behavioural intention, to increase the waste reduction practice.

Crash Reduction Factor(CRF) CRF (Crash Reduction Factor), also known as Crash Reduction Rate, refers to the percentage of reduction in the number of traffic accidents when taking a particular security measures in transport system[1].
The data required is: the average number of accidents in many years before the implementation of safeguard measures which is called aB, the average number of accidents in several years after the implementation of safeguard measures which is called aA.
A certain improvement measures have classified the value of CRF to different type of accidents, which not only improves the accuracy but also provides a variety of research required data.
General types of accidents are: All, Fatality or Injury, Property Damage Only, Head On, Rear End, Side Swipe, Left Turn, Right Turn, Right Angle, Fixed Object, Pedestrian, Red Light Run, Run Off Road, Wet , Night[3].Table1 shows the Statistic data of CRF channelization portion in Missouri State，U.S.A.[4] Table.1 Statistic Data of CRF Channelization Portion in Missouri State，U.S.A.
If it is got that the historical traffic accident data of the road which has been implemented a certain safeguard measure, the number of reduction of accidents can also be calculated after the implementation of a certain safeguard measure, and the calculation formula(Eq.  2) is used for caculating the number of reduction of accidents.

At the same time, it is proved that the attribution reduction is equivalent to the attribution reduction based on the positive region.
However, in practical application due to measuring data error, restricting on access to knowledge, We usually face with the incomplete decision table[2].
At the same time, it is proved that the attribution reduction is equivalent to the attribution reduction based on the positive region.
Thus the attribute reduction is .
Approximation reduction in inconsistent incomplete decision tables[J].