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These models can continuously learn from new data, automatically refining their predictions over time [15].
The multilayer architecture allows the ANN to process and analyze complex multidimensional data, gradually revealing hidden patterns.
The reduction in required input parameters may also facilitate future generalization to new materials or loading paths, especially when only limited data are available.
"A review of the application of machine learning and data mining approaches in continuum materials mechanics." 
"Analysis of the experimental data on a low cycle fatigue under nonproportional straining." 

On top of these efforts, device innovation not only brings chip size reduction, but also directly brings material cost reduction.
Data on commercial 1200V SiC MOSFET are also plotted in Fig. 2.
Fig. 3 shows the impact of the reduction of on-resistance on the active area.
With a fixed temperature coefficient of α=1.8, 50% reduction in on-resistance promises 29% reduction in active area.
Yield enhancement, and wafer cost reduction results in additional 60% chip price reduction (compare chip 2, and 3).

Staged construction response was simulated according to the practical excavation process, and strength reduction theory was used to analyze the basal heave stability problem.
Then two sixth-degrees of polynomial curves are obtained after fitting formula using the data from Table 2.
Finally, basal upheaval damage will be taken place if soil strength reaches the ultimate state because of plastic parameter reduction
(3) The plastic zone increases with the reduction of plastic parameters.
Both the calculated safety factor and plastic zone will be larger and larger with the reduction of plastic parameters.

But when we treated for more than 30seconds we didn’t observe a significant reduction of contact angle.
In opposite to the PDMS, the treatment done at 0.1 mbar showed a reduction of contact angle (blue data in the figure 2).
We observed that for PDMS when the pressure increased from 0.1mbar to 0.4mbar there was a reduction of the surface contact angle.
The reduction of pressure increase the mean free path of charged plasma species.
The ion bombardment change the surface morphology which could be a nanotexturing of PET surface and then the reduction of contact angle [12].

The percentage of biofilm reduction was 23-45%.
Figure 1 displays the percentages of bacterial biofilm reduction.
Biofilm formation of cariogenic bacteria on orthodontic retainer PMMA resin Bacteria 0 Vanillin (%) 0.1 0.5 S. sobrinus S. mutans L. acidophilus L. casei 1.053+0.002 0.905+0.017 0.748+0.007 1.051+0.005 1.068+0.014 0.845+0.048 0.512+0.010* 0.720+0.012* 0.802+0.031* 0.617+0.006* 0.410+0.003* 0.677+0.008* data expressed as mean optical density + SD * significant difference from 0% vanillin Figure 1.
It was found that 0.5% vanillin-incorporated resin exhibited significant inhibitory effect against all tested cariogenic bacteria (23-45% biofim reduction).
The significant inhibition was seen only on lactobacilli (31% biofilm reduction).

Introduction The optimization problem of load distribution in the finishing-mill rolling process is how to get a serious of data about the slab thickness hi; and the data will make the whole system state most optimal.
In general, the rolling schedule is a chart full of experiential data which people get from the load distribution of actual production[1].
The data relying on this method is reasonable, but not optimal.
Simulation We combined 470 rolling data to establish and 16 data to check up the predict thickness model.
So once checking data outputs, the model usually educes unreasonable error.

One measure to analyse the strength of the CFS structure under high temperature is through the Finite Element Method (FEM) and a prediction data that is close to the actual material properties at the elevated temperatures are needed, consequently, the material properties of the CFS Grade G450 with the thickness of 1.90 mm were tested.
The values of reduction factor are tabulated in Table 2.
For this purpose, the reduction factor and stress-strain model produced by [5] and [7] were considered.
Comparison of the proposed reduction factor by previous research and recommended by [8] Table 2.
The reduction factors were almost similar for all previous studies and EC3-1.2 for elastic modulus.

GIS can provide good function of information technology for EIA, based on its strong ability on processing spatial data and attribute data.
Spatial data can describe the position of the object, while attribute data as a qualitative or quantitative factor can describe the feature of the specific object [4].
Environmental information is the basic data of project EIA.
In this way, the classified management and organic connection of spatial data and attribute data can be realized.
GIS can describe spatial topological attributes of objects (spatial data) and the multiple attributes of the spatial objects (attribute data) [10].

The result means that WT-SVD method can strike a balance between data compression and preservation of small valid information in feature extraction of three-dimensional fluorescence spectra of mineral oils.
With decomposing data into the low-frequency and high frequency parts in different directions, WT can maximize the retention of effective small components’ information in the original data, but the coefficient matrix is relatively large in scale.
Diagram of 3-D fluorescence spectrum measurement system Data Preprocessing.
After numerical filtering used to restrain spurious interference, in order to unify spectral scale and get comparability in the global data domain, range normalization of EEM data based on the matrix is performed to transform the data into the [0,1] range, as shown in the Eq. 1: (1) Fig. 2 is the 3-D fluorescence spectrum contour based on the EEM matrix of 97# gasoline sample of some concentration after interpolation smoothing, called as ‘spectrum fingerprint’.
Wavelet Transform (WT) has zooming capability with high local resolution, low distortion characteristics, for data decomposition.

Then it is verified by real operational data of the capital airport under bad weather.
It proved that the model could be used to arrange for flights to alternate reasonably when a large hub airport encountered a severe airside capacity reduction.
A Case Study In this section the actual flights operation data of Capital Airport are used to simulate the above programming model.
Bad weather is the main reason of airport capacity reduction.
The following Table 1 lists the alternating statistical data of 20 alternative flights selected between 23:00 and 24:00 on November 27, which flew to the capital airport from all over the country.