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The results are compared to the original training data, as well as newly generated test data.
On this basis, we now want to construct a data-driven model by generating pass design data using the method described before and feed this data into an artificial neural network.
The neural network was tested against the training data and against test data generated by the same procedure as the training data, but at different roll diameters.
However, a data-driven approach is always limited to the data ranges of the provided training data.
In further studies, the data range of the model will be extended to a broader range of sections, reductions and roll diameters.

But it is lower than the theoretical value by 31%.The data Energy consumption monitoring platform is higher than the electricity supply bureau by 12.68% .The data of Sub-item measured close to the calculated value.
The data provided by administration of power supply.
(2) Electricity supply bureau collect data at high voltage side and monitoring and control system collect data at low voltage side
But it is lower than the theoretical value by 31%.The data Energy consumption monitoring platform is higher than the electricity supply bureau by 12.68% .The data of Sub-item measured close to the calculated value.
It should ensure that we provide accurate data to Operations Management Department

Average confidence indexes were obtained falling between 0.15 and 0.25 with 80% or more of the data points exhibiting a confidence index greater than 0.1.
Also the Vickers hardness data are characterized by a continuous increase from HV3=155 after the first pass to HV3=250 after the tenth pass.
The orientation scans shown in Fig. 1 were obtained using a cleanup procedure applied to the raw data.
According to this procedure, questionable data points that could not be indexed were replaced by neighbouring data points that could be indexed with sufficient confidence.
For example, Hughes and Hansen[3] have reported similar data, based on TEM observations on cold rolled nickel, with rolling reductions ranging from 70 to 98%.

Nd2Fe14B particles were obtained from mixture of neodymium oxide, iron oxide, boric acid and CaH2 by reduction-diffusion process.
Results and Discussions Figure 1 shows XRD data for different washing processes and its influence on phase transformation for obtained Nd2Fe14B product.
SEM microphotography of powders obtained after reduction-diffusion (a), washing with only water (b).
Lee, Fabrication of ultrafine Nd-Fe-B powder by a modified reduction-diffusion process, Rare Metals 25 (2006) 223-226
Choi, Influence of Ca amount on the synthesis of Nd2Fe14B particles in reduction–diffusion processes, J.

The cold work to 75% thickness reduction of the as-annealed steel resulted in the hardness increase from 150 HV to 420 HV.
Cold work caused the reduction of the number of surface cracks and disappearance of IGSCC.
The average value was obtained from 8 data among 10 data neglecting the minimum and maximum values.
Tensile SSRT-DO8ppm SSRT-DH1.4ppm SSRT-DH0.4ppm Reduction in Area [%] Vickers Hardness [Hv] 0 25 50 75 0 20 40 60 80 100 100 150 200 250 300 350 400 450 Rolling Reduction[%] Tensile SSRT-DO8ppm SSRT-DH1.4ppm SSRT-DH0.4ppm Reduction in Area [%] Vickers Hardness [Hv] 0 25 50 75 0 25 50 75 0 20 40 60 80 100 100 150 200 250 300 350 400 450 Rolling Reduction[%] Fig. 3 Dependence of reduction in area after SSRT on the hardness of SUS316L.
Cold work caused the reduction of the number of surface cracks and disappearance of IGSCC.

Based on the data obtained during this study, the initial footstep geometry produces data in the form of total deformation (1.383 mm), equivalent stress (21.013 MPa), and safety factor (1.227).
The 10% variation produces data in the form of total deformation (1.4368 mm), equivalent stress (20,564 MPa), and safety factor ( 1.2538).
At the same time, the 25% variation produces data in the form of total deformation (1.3058 mm), equivalent stress (22.27 MPa), and safety factor (1.1577).
This data is entered into the ANSYS Workbench software's Engineering Data section's table.
Based on these data, the best footstep design is a design with a mass reduction of 20% because when compared with other conditions it produces von Mises stress results, the smallest total deformation, while the safety factor is the largest.

Spatiotemporal system can be effectively analyzed through separating data into spatial and temporal or using data as a whole entity.
In either way, we can conclude that both the spatial data and the temporal data will affect the final result (the system).
In Section 3 and 4, spatial data and temporal data representation are discussed.
The nature of time series data includes: large in data size, high dimensionality and necessary to update continuously.
In this method, a rate of m/n is used, where m is the length of a time series P and n is the dimension after dimensionality reduction.

Therefore, this paper adopts the related panel data analysis method .
data sample This paper is focused on the panel data of the energy consumption and GDP of the OECD countries and the BRICs from the year 1986-2009, within which,it converts the annual nominal GDP into the actual GDP(unit average: billion dollars) according to the global GDP constant prices of 2005; annual energy consumption (mainly includes:crude oil, natural gas and raw coal) is converted to million tons of oil according to the related convertion standards of the BP world energy statistics annals(2010) .
Rroot of panel unit test the panel unit root test means making a unit root test on the cross section sequence of variables of panel data as a whole.
The test of the unit root of panel data is similar to that of the time series, with the prior consideration that whether there exists an auto-regressive constraint in the panel data structure.Considering the AR(1) process based on the panel data structure: (2) i=1,2,…,N means the cross section sample; t=1,2,…, Ti means the time span of the panel unit but represnts all the fixed effect and rare trends in all modes; is an auto-regressive coefficient; is error and assumes to be interdependent.
In order to avoid the “fake regression”of the panel data sequence, we should first carry out a panel unit root test on the panel data sequence.

Then the noise reduction theory of sound barrier is introduced in detail.
The data shows that the noise produced by a car in normal driving is 80~90dB , and the traffic flow noise is close to 100dB(A) in rush hour[1].
(a) Settings of simulation condition According to the measured data, the vehicle flow of the main road is 1000 cars per hour, so it can be seen as line sound source.
The noise reduction effect of sound barrier is further reflected.
But the noise reduction effect is not as good as the figure 2(b) and 2(c).

The aim of the current study was to assess effectiveness of automatic braking system quantitatively using real pedestrian accident data selected from IVAC database.
The current study is an attempt to predict the benefits of automatic braking system based on real-world accident data.
Data Set In 2006, a special team from Hunan University carried out a vehicle traffic accident investigation in Changsha located in middle of China.
Drivers of 78 cases did not brake before the collision, accounted for 94% of the data set.
A Method for Estimating the Benefit of Autonomous Braking Systems Using Traffic Accident Data.