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Recently, some researchers have used genetic algorithm, data envelopment analysis, desirability function approach etc. for multi response optimization in various fields of engineering [8-10].
Grey data processing must be performed before calculating the grey correlation coefficients.
The grey relational coefficient can be expressed as: γ ((k), yi (k))= ∆min+ ξ∆max∆oj k+ξ∆max (3) Where; Zij is the sequence after the data processing, j = 1,2...n; k = 1,2...m, n is the number of experimental data items and m is the number of responses. yo(k) is the reference sequence (yo(k) = 1, k = 1,2...m); yj(k) is the specific comparison sequence.
Data analysis is made using MINITAB R14 software at 95% of confidence.
[9] Hung-Chang Liao, A data envelopment analysis method for optimizing multi-response problem with censored data in the Taguchi method, Computers & Industrial Engineering, 46 (2004) 817–835

In practice, the measured response data are mixed with inevitable input and output random noise, which causes inequality in the equation of motion and thus ill-conditioning of the inverse problem, distorting the identified stiffness and damping matrices.
In fact, in this method of noise reduction, the part of U(ω) which is almost noise-free is saved.
Comparison of the identified value with the actual damping value shows a substantial reduction in the error.
An eigensystem realization algorithm for modal parameter identification and model reduction.
System identification of Vincent Thomas Bridge using simulated wind response data.

The heterogeneous rate constant of electron transfer (ket), exchange current density (io) and time constant (τ) were calculated from data obtained from electrochemical impedance spectroscopy and found to have values of 2.3 x 10-5 cm s-1, 1.6 x 10-4 A cm-2 and 2.4 x 10-4 s rad-1, respectively.
Electrocatalytic Oxygen Reduction Reaction (ORR).
Kinetic data from EIS Nature of electrode ω (rad s-1) τ (s rad-1) io (A cm-2) ket (cm s-1) Bare GCE 9.01 1.1 x 10-1 5.82 x 10-7 8.4 x 10-8 GCE/FeCo 4159.0 2.4 x 10-4 1.6 x 10-4 2.3 x 10-5 Electrocatalytic Oxygen Reduction Reaction.
(B) Kouteky-Levich plot for oxygen reduction.
Swager, Electrocatalytic conducting polymers: oxygen reduction by a polythiophene−cobalt salen hybrid, Chem.

This kind of models needed a huge amount of data.
It also needed a lot of data.
Empirical analysis Based on the models, empirical data should be collected and analyzed.
According to the models and data, the Carbon emission table was compiled in table 2 and table 3.
By analyzing the driving force of carbon emission, this paper provided more intuitive and effective data support for making policies and measures of carbon emission reduction.

In view of this, when processing the economic data, the data completeness should be ensured, the internal differences not destroyed, the hierarchical relationships highlighted and the dynamic development trend of the data focused.
Secondly, it uses the principal component analysis to realize the dimension reduction of the indicators, eliminate the data overlapping information and re-examine the index weight so as to make the indicator system level and weight clear.
Dimensionless data processing Economic system index data often belongs to different dimensions.
Let be the original data matrix， be the dimensionless processing of a data matrix, where .
Because larger data yield more stable communication, then 3.

In order to reduce calculation and data storing, the dimensionality reduction methods are taken as excellent choice.
PCA can eliminate the second-order correlation between data and keep up most information of the raw data.
We also test PCA plus SVM approach using standard benchmark data sets.
The data sets were obtained from UCI machine learning repository [12].
Here we select the data set with low dimensions, which means the is usually no singular.

Timely data recovery and fault exercises with a holistic, multi-level data backup and disaster recovery technology could protect the security of the online system.
Data Backup Strategy Every day the online system stored a lot of production and management information in the database which plays a crucial role on business operations, so the enterprises specially purchased storage device, develop a data backup plan and backup the data by the plan in order to guarantee reliable data storage in the system.
The database uses the full recovery model, so the data of tail-log must be backup before the beginning of the reduction.
Timely data recovery and fault exercises with a holistic, multi-level data backup and disaster recovery technology could protect the security of the online system.
Design and Implementation of financial data importing in the system.

Study on the Data-mining based Mechanism for the Occurrence of Ship Collision Accidents Caused by Human Factors Hongxi Li Dalian Maritime University, Dalian, Liaoning Province, 116026,China Keywords: Accidents Caused by Human Factors; Collision Accident; Bayesian Network; Data Mining; Cause Chain Abstract.
In order to effectively analyze the mechanism for the occurrence of ship collision accidents caused by human factors, an accident causing chain was constructed using the Bayesian network structure and the data mining algorithm.
Data mining algorithm.
Apriori algorithm can effectively mine the frequent item sets of the association rules and discover the associative, valuable data models from the mass data using the prior knowledge of frequent item sets.
Traffic Accident Analysis based on Data Mining Technology [J].

The results indicate that plating the base steel with this kind of deposit leads to a reduction of the fatigue life of the material.
The reduction in fatigue life has been quantified in terms of the Basquin parameters of the materials tested under different conditions.
PHT samples, which exceeds the minimum number of specimens required in S-N testing for reliability data according to the ASTM standard 739 (12-24 samples).
b a c b validity of the simple parametric expression of the form earlier proposed by Basquin for the description of this type of data: S=ANf m (1) where A and m represent constants that depend on both material properties and testing conditions.
Table 2 summarizes the values of the parameters A and m for the two sets of data represented in Fig. 2.

High temperature produced by arc and current resistance heat could smelt the charges and create reduction conditions.
The deep reduction furnace undertakes two function including melting metallized pellets and making deep reduction of vanadium oxides in slag.
Thermodynamic parameters about the reduction of vanadium oxides are shown in table 3.
Table 3 Parameters about the reduction of vanadium oxides Serial No.
Chemical reaction Standard gibbs free energy Temperature/K 1 V2O3+C=2VO+CO △G0=255185.46-172.50T 1479 2 VO+C=V+CO △G0=319243.50-162.87T 1960 3 V2O3+C=2V+3CO △G0=868342.32-500.83T 1734 4 V2O3+5C=2VC+3CO △G0=664026.48-481.65T 1379 5 V2O3+3C+N2=2VN+3CO △G0=438776.64-335.87T 1306 Data of table 3 show that the temperature of hot metal should not below 1734 K if you want to obtain a higher vanadium reduction ratio, if not you need to extend reduction time.