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Rule data discovery and miming of providing some valuable approach to study the meteorological data quality control, meteorological data Study of Data Mining Model to Multi-Dimensional Time Series Recently, data mining multidimensional time sequence has applied gradually in meteorological fields and made great achievements.
Preprocess the meteorological data Because the data in data mining have multi-dimension, high redundancy, complexity in size and mass data, algorithm and tools of data mining is not directly applied in data mining process must data pretreatment firstly.
There are two data preprocessing step, building meteorological data mining database, data dimension of treatment.
In addition, 2004-2007 data is used as the model training data ,while others are acting as the model test data .
Conclusion This paper presents a new multidimensional time series data mining model, this model meteorological data redundant dimension reduction algorithm is used to decrease redundant size and complexity of the data mining slope extremum piecewise linear fitting method is used to realize the multidimensional meteorological time series segmentation, data compression and eigen value extraction, reduce the difficulty of the data mining method, then use k­means cluster to make the symbols of sequence, The results of experiment show that this model has a great practicability.

Thus, it is more effective to obtain a more realistic data mined from the vast amounts of geological measure data than other methods.
The prediction model established by it shown in Figure 1, is formed by the four sub-modules: data preprocessing, attribute reduction and rule generation and prediction.
Through data cleaning to smooth the geological drilling noisy data samples, and fill the vacancies value of the data sheet, remove isolated points [8].
It can be solved by smoothing methods or replaced noise data by the average data.
In this paper, using the probability distribution law to discrete a continuous multiple condition attribute, according to data distribution between the small segment to determine a threshold value ,and it is more than the discrete segment data value, then merge it with "near" range to, if more than the threshold will be divided into a class. 4 Attribute Reductions 4.1 Distinguish Matrices Attribute reduction directly related to the quality and efficiency of data mining is the core of the algorithm.

Therefore, a demand reduction effort even for DR needs to maintain, if not to improve, the established PUE rating of a data center.
Power Models for Data Center Components.
Efficiently Cooled Data Centers.
Ordinary Data Centers.
For data centers, there are few attempts, if any, that addresses the relationship between power reduction efforts and energy efficiency issues.

In the course of this ongoing collaboration, the organization and dissemination of information and data play a key role.
Therefore, it is necessary to introduce data filtering function during the transmission of information flow between the various departments.
It has three main functions: (1) collect related data and information of disaster from the public, media and specific experts; (2) organize useful data; (3) send the necessary final filtered metadata, data and information to its subordinate.
In all stages of the disaster management process, the applied information and communication technologies includes the internet, information security, computer databases, integrated data management, intelligent data management, audit tools, multi-agent systems, multi-language support, data filtering, mobile communication technology, wired communication technologies, and wireless communication technologies.
Research on sharing of international disaster data and information, Disaster, vol.3, pp.109-113, 2008

Relevant literatures proposed electricity energy-saving key technical support system architecture, such as energy consumption, pollutant emissions supervision and inspection and data analysis support system, energy saving and emission reduction targets, evaluation and assessment technical support system[5].
Since the specific condition for each area is different, emission capacity can be calculated by substituting corresponding data into the simplified model.
Our data is mainly from Jilin Grid Inc.
To calculate the capacity for 2011, the data we need is as following: coal power for 2011’s Jilin is 5.684×1010kWh, or 1.7×107t for coal consumption, wind power is 3.968×109kWh, or 1.19×106t for coal consumption.
Limited by data, we can only calculate operational emission reduction capability for Jilin grid taking one year as the unit time.

First, the data are refined by the data reduction technique, which makes it keep the data structure of the original data and have higher efficiency.
This procedure is called data reduction algorithm (DRA).
Let denote the original data set, denote the data set after reduction and denote the distance from data to data set of .
The fast speed of ERKPCM on three data sets owes to the data reduction technique, which makes it keep the data structure of the original data and have higher efficiency.
In the meanwhile ERKPCM has a high computational efficiency on most of the test data sets because the data size is decreased by the data reduction technique.

Analyze and conclude the relationship data between existing-pipeline-controlled rainfall return period and runoff coefficient, by using source control.
Calculate and conclude the design scale of ecological measures and storage pools, draw the corresponding generalized model, by using peak flow reduction, volume reduction and flow reduction measures.
That includes existing sewer discharge return period improving, peak flow reduction, volume reduction, flow reduction etc.
Fig5 The melts generally model of flood volume reduction Determine the scale of flowing reduction mode Flowing reduction measures include stormwater detention zone, vegetation swales, storage pool etc.
Fig.7 The schematic picture of flood rate reduction Conclusion This paper presents several measures of runoff reduction, which includes existing sewer discharge return period improving, peak flow reduction, volume reduction, flow reduction etc. and analyzes the handling facilities scale of these various measures in Zhangjiakou city, which is selected as a study area.

The data suggested that copper (II) was reduced and the resulting copper (I) complexed, with both reactions probably mediated by sulfur oxy-anions produced indirectly by the bacteria, in the anoxic sulfur column bioreactors.
Chemical reduction and complexation of copper.
Results and Discussion Performance of the iron reduction system.
Theory of reduction of copper (II) and complexation of copper (I).
Conclusions A two-stage bio-reductive process for recovering copper from PLS, devised and tested at the laboratory scale, generated interesting and unexpected data.

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.
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 Multi-covering Information System and Consistent Decision System Reduction of multi-covering information system.
Then we study the reduction of this case.
Pawlak, Rough sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, boston,1991

Key Words: Mg-Sr alloys; Thermodynamics; Vacuum reduction 1.
In the melt-leaching-reduction process, the driving force kinetics for Sr reduction are very low at the reaction temperatures normally used[2].
Thermodynamics Analysis of MgO and SrO Co-reduction 3.1 Method of Gibbs Free Energy Evaluation and Establishment of Oxygen Potential Diagram All the thermodynamics data for Sr compounds and reactions involved in this paper were calculated using a Gibbs free energy function method using original data taken from the Ye-Hu thermodynamics data book.[6] The mathematical model for the evaluation of the Standard Gibbs Free Energy is ΔG Θ =A+BT (1) The oxygen potential diagram of Sr, Mg, Si and Al is plotted in Fig. 4.
The data indicates the following: (1) Tc decreases as pv decreases
H.: The practical thermodynamics data book of inorganic matter.