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Abstract: 9238 traffic accidents data are collected in rural road of China.
Through the data analysis, the main causes of rural road traffic accident are presented.
This paper collects rural road traffic accident data in some provinces of China, analyzes the main features of rural traffic accidents.
Comparison the overall statistics with the survey data: not keep a safe distance in survey area is not a more prominent compared with the national level.
The reason is that more sunny day data are collected and the sunny day are usual in the whole year.

The existence of basic data is a requirement for such an evaluation.
Combination of the assessed data in descriptive KPIs 4.
The use of this data connection is limited to Siemens PLCs.
The data acquisition and processing algorithm collects data from the modules in a predefined frequency (sampling rate), transforms the data into readable information (e.g. converting IEE754) and passes the entire information set via Ethernet to a database.
An integrated data processing algorithm permits to aggregate the consumption data on basis of trigger signals from the machine tool prior to data storage.

Cloud storage needs to have a big breakthrough in the amount of data storage and security compared with the traditional data storage solutions.
Node server is the original server in distribution system, which is responsible for the data storage in data pool and running virtual software.
Node server can learn from a highly scalable data distribution strategy [10] in data storage.
Energy Efficient Resource Management in Virtualized Cloud Data Centers[C].
Energy Efficient Allocation of Virtual Machines in Cloud Data Centers[C].

Then, the data preparation, data preprocessing and the mathematical description of the algorithm for our method were presented.
Data Preparation.
Data Preprocessing.
Data preprocessing phases include: 1) data quality control.
According to related data quality standards, the raw data need to be reorganized and validated.

Four-tier framework is composed of user layer, application layer, underlying support layer and data layer.
Data Layer.
The data involved in the model includes thematic data and real-time collected data.
Thematic data include structure inside the hotel, the lifeline engineering data, demographic and related environmental data etc.
Real-time collected data include the temperature and smoke information data collected in real-time by temperature sensors and smoke sensors.

First, the data set is split into a training set and a test set.
In this study, a random data subset has been chosen to build random forest classifiers.
Therefore there are less training data that present instable behaviour and thus the classification by using one training data set delivered worse results.
The absolute error in frames is sometimes slightly higher using the complete training data.
But it can influence the sequence length of the data.

The data is dispersedly saved and processed.
The layer extracts, integrates and transforms the operating business data in order to organize data around the morality of load and charge and store it into dispatching data warehouse.
Data warehouse takes power grid running data in different areas as data sources.
Thus the most important question is how to gather distributed information sources together into data warehouses so that when data sources change, materialized views in data warehouses can change with original data and dispatchers can make a correct decision in time.
As a result, we can conveniently gather data in partial database into data warehouse.

This is equally true for liquefied natural gas (LNG) transportation in which any possible reduction in capital and operational costs will attract the attention of the ship-owner.
Data could then be generated from this model to facilitate the intended investigation.
According to [1], a mathematical model can produce two types of information: (1) knowledge of the system being modelled, and (2) data observations from a system’s inputs and outputs.
This model was used to generaate data that could be used to train an Artificial Neural Network (ANN).
Data Collection The generation of simulation data for the LNG carrier, started with the selection of the most appropriate independent variables for each component where the selected variables were those which would have the highest impact on the vessel parameters.

Copper(0) nanoparticles in nanoporous nickel phosphate VSB-1 were prepared by the methods of ion exchange and hydrogen reduction.
The Cu 2p core level binding energies were consistent with elemental Cu(0) appear in the X-ray photoelectron spectroscopy (XPS) data.
XPS data are characteristic of elemental Cu(0).

Comparison of our results with data obtained by other methods is in quantitative and qualitative agreement.
Comparison of our results with data obtained by other methods described in section 2.
As it is known [15], the reduction of binding energy with displacement of the impurity atom to edge is called by increasing of average distance between an ion and free electron charge.
Results obtained by the developed method are in the well agreement with the data of other authors.