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The method of MAS technology for grid-based fault location has the following issues: the need to do based on a large number of electrical data, transmission volume upload is not timely; position calculation amount of information to determine a long time; when appearing DG and the IDT putting in use or out of use , the algorithm is not easy to change, affecting the flexibility of MAS.
According to the relevant network data, establish the topological relationship between nodes.
The Grid Fault Location Method Base on MAS of Rough Sets Decision table and the reduction.4 Tuple is a knowledge representation system, Of which: isfinite set of objects, Called the domain; A non-empty finite set, Called the set of attributes, and, and are called condition attributes set and decision attribute set; V is the range of attribute A: is an information function, Take properties offrom any elementof u, find uniquely determinedin the v, make G become Family of equivalence relations, the intersection of all equivalence relations in the G were Called indiscernibility relation on G, use I(G) show, if there,,is independent, Satisfy, is called a reduction of G, use R(G) show, Full reduction of G is defined as the intersection of nuclear, denoted as: .
Discernibility matrix of decision tableis a Matrix, The row i column j element of the decision table of the i-th row and j-line comparisons of: (1) After a reduction of more than one property after the reduction has been combined, Re-use twenty-two property obtained between the minimum information entropy as the best combination of attribute reduction combinations.
Composed of seven samples of the decision table are: Table 2 Fault diagnosis decision table Of the decision table attribute reduction, 3 properties available for the reduction were {CO1,CB1,CO2,CO3}, {RR1,CB1,CO2,CO3},{CO1,RR1,CO2,CO3}。

(3) The value of DI CIe in a wide range of T has been independently deduced from the data on in-diffusion of Au and Zn [11, 12], and the result is consistent with the Eq. (3).
An existence of slow-diffusing Figure 1 Vacancy diffusivity data.
vacancy species is supported by the data on the enhanced self-diffusivity under hot proton irradiation [16].
Interpretation of the RTA data on vacancy (or precipitate) depth profiles depends on the assumed mechanism of Vs loss during the cooling stage of RTA and the post-RTA annealing.
A fast reduction in τ*(T) upon raising T is compensated for by a fast increase in the Cse/Cse* ratio.

In addition, in real parameter estimation problem of the model, data are often corrupted by noise which should be taken into account [3].
In this study, the percentage noise ratio is designed to perform optimization for different level noise, and the noise ration () is given by (9) where represents the component of noise-free data at th time point, represents the experimental data including additive noise, is the number of data points, andrepresents the average value of experimental data .
When we add a certain degree noise (=30%) into test data, as revealed in Fig.2, the simulation results by using the proposed approach are still satisfactory, whose RMSE is below 0.3.
The simulation data is in a close agreement with the test data, even through the simulated data are corrupted by different degree of additional noise.
In addition, this approach is applied to estimate parameter of the experimental data with a certain level artificial noise.

A Framework for Novelty Detection in Jet Engine Vibration Data David A.
Off-line (ground-based) analysis of engine vibration data using these data structures is presented in Section 3.
Domain-Specific Data Description Fundamentals of Jet Engine Operation.
Note that, after dimensionality reduction, graph axes are unitless.
Fig. 4 - Setting novelty thresholds by modelling data density.

Finally, the silver circuit patterns with the lines of 200 µm width were formed on the PI substrate surface due to the reduction reaction of dimethylamine borane (DMAB).
The reduction of silver ions is initiated by the electrons migration from DMAB to silver ions, and silver nanoparticles subsequently form, according to the following reactions.
It can be concluded, base on FTIR data, the surface molecules of the PI film are cleaved to form metal salts of carboxylic acid groups and amide bonds by KOH, and are consequently transformed to carboxylic acid groups by DMAB.
After DMAB reduction, numerous silver nanoparticles assemble on the surface of PI film.
Combined the contact angle data with the results of ATR FT-IR spectra, we can deduce that the difference in contact angle between the PI films before and after DMAB treatment is attributed to the difference in intrinsic wettability between the two ionizable species [30].

They do not however report bulk lifetime data, nor do they investigate different parts of the ingot in detail.
They report limited lifetime data, which perhaps indicate a small improvement upon annealing at 400 °C.
The situation for bottom wafers annealed at 500 °C is less clear-cut, and more data are required.
Data in Fig. 4 demonstrate that the lifetime reductions did not generally correlate with changes in bulk iron concentration, so we attribute the lifetime change to formation of another recombination centre.
Liu and Macdonald suggest the hydrogenation level affects the decay rate of bulk iron, and our bulk iron decay data at 400 °C are much more similar to theirs with SiO2 passivation (very low hydrogen) than the Al2O3 passivation data (moderate hydrogen) and silicon nitride data of Krain et al.

By adding reactive power of before and after the test data comparison, summarized as follows:When the power factor is raised from 0.81 to 0.96 the current is reduced 55A, voltage 3V, depending on the power reduction in 33KVA, reactive power reduced 81KVAR.
Fixed cost: purchased cost of equipment Opportunity cost due to the use of reduction machine, and loss of the sale of tin slag income.
Direct benefits: save the purchasing cost of tin bar.Indirect benefits the tin slag reduction technology, is the company's resource conservation of specific performance, for the company in the industry establish a responsible citizen of the community's good image.
Only a direct economic benefits, calculated monthly investment recovery period: Fixed cost/ (month directly benefit – month change cost - on the opportunity cost) =3.017 Namely: the investment recovery period is 3.017 months. 2) Select the appropriate reduction machine 3) make recovery process and management method Recovery process divides into two types. one is lead-free wave soldering tin slag recycling process the other is lead-free production line tin slag recycling process; 4) formulation of reduction process and management method Each batch of reduction of tin block sampling board testing component.
We will farther promote Green Process activities with cost reduction efforts so that enterprises can function in harmory with the global environment.

anataly_polanco@hotmail.com, bmmtusi@gmail.com, cmbtusi@gmail.com, daolivei@ipen.br, eespinace@ipen.br Keywords: borohydride reduction, DMFC, chemometrics Abstract.
The impregnation method, here called borohydride reduction method, is one of the most widely studied methods for the preparation of electrocatalysts [4,5].
Experimental PtRu/C electrocatalysts with 20 wt% of metal loading and Pt:Ru atomic ratio of 50:50 were prepared by a borohydride reduction method using different conditions.
Fig. 1– (a) X-ray diffraction of PtRu/C electrocatalysts prepared by borohydride reduction in different conditions.
Using the equations 1 and 2 and the data of Table 2 they were calculated the influences of solvent (S) and BH4-:metal ratio (R) separately.

Study Area and Data Study Area (Akita Prefecture).
Satellite Data (Terra/MODIS).
Insitu Data (AMeDAS).
AMeDAS (Automated Meteorological Data Acquisition System) snow depth is an automated measuring data.
Hourly observation data of snow depth are recorded.

It has developed rapidly in the 1990s and become the important data mining methods [2].
In recent years, new methods have come out of data mining, such as SVM etc., however, Rough Sets has an irreplaceable position as it can reach the classification rule without a priori.
P could have more than one reduction.
[3] Xiongfei Li,Jun Li.Data Mining and Knowledge Discovery [M].
A Novel Feature Reduction Algorithm Based on Core Feature Dependence [J].