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Obtained outcomes highlighted the remarkable capabilities of the implemented procedure in terms of reliability of temperature predictions and of drastic reduction of the computational time with respect to classic computational models.
Indeed, during the process, the initial heating of the material leads to a reduction of the resin viscosity, allowing excess resin to squeeze out from the reinforcing layers.
The learning and recognizing patterns in large data sets is the key ability of neural networks to achieve learning and memory [21-23].
Physical properties of each constituent, resin reaction kinetics models and parameters are defined according to data reported in [3,5].
The proposed model is tested versus unknown data related to the autoclave temperature heating over time.

The present work focuses on the evaluation of formability of Ti-6Al-4V using the hot single point incremental forming (SPIF) process which seems appropriate to produce small batches of parts due to its flexibility as it allows the reduction of costs and lead times.
In this sense, Ti-6Al-4V is widely used in the aeronautical industry in the manufacturing of high strength lightweight parts, which lead to a reduction of both the fuel consumption and the associated pollution.
Interaction between the forming temperature and the tool step down The feed rate parameter, it could not be included on the ANOVA analysis because of the lack of enough data to analyze its influence.
As it can be observed in Fig. 14, there is a slight decrease of material strength compared to base material data at RT shown in Fig. 3 because of the SPIF operation.
Tensile test data, part P2: strength relief values along tool step direction at 0º (top left) and 90º to RD (top right), elongation along tool step direction at 0º to RD (bottom left), strength relief values along feed rate direction (bottom right) Conclusions The present study demonstrates the potential of Global Hot Single Point Incremental Forming process (using an electric furnace) to deform Ti-6Al-4V.

The selectivity of propylene depended strongly on the phosphorus content in the zeolites; The enhancement of propylene selectivity with increasing phosphorous content was attributed to reduction of strong acid sites on the H-ZSM-5.
Table 1 data also showed that SBET and VP did not change synchronously with the increase of phosphorous content.
Table 1 Pore structure parameters of ZSM-5 zeolites with different phosphorus content Samples S0 S1 S2 S3 S4 S5 S6 SBET/(m2×g-1) 331.8 315.0 301.9 286.2 253.6 212.5 161.9 VP/(cm3×g-1) 0.173 0.170 0.165 0.158 0.150 0.145 0.132 SBET—BET specific surface area;VP—Total pore volume Combining the N2 adsorption-desorption isotherms with XRD data, we knew that impregnated phosphorus entered the channels of ZSM-5 zeolite, reacted with its framework atoms, and caused the shrinkage of zeolite channels, which made the BET surface area and pore volume of phosphorus modified samples decrease.
Table 2 Catalytic Performance of catalyst smaples Sample Name S0 S1 S2 S3 S4 S5 S6 Conversion/% 100 100 100 100 100 100 100 Product Distributions /wt% CO+CO2+CH4 3.73 3.61 2.15 2.49 2.25 3.26 3.02 Total C2~C4 paraffins 7.02 3.83 3.64 3.48 3.02 2.81 2.27 Ethylene 9.07 15.82 15.21 11.23 10.09 12.17 15.64 Propylene 34.38 34.45 38.12 42.38 44.57 45.97 47.01 Butylenes 15.08 14.27 16.56 20.13 24.16 25.11 24.33 C5+ 30.72 28.02 24.32 20.29 15.91 10.68 7.73 Data obtained at 60 minutes on stream time.
The reduction of the concentration of acid sites which are responsible for the hydrogen transfer reaction, decreases the conversion of olefins to paraffins, thus selectivities to propane and butane decreased with increasing phosphorous content in ZSM-5 zeolites.

By comparing data of simulation and experiment on chip morphology characters, it is indicated that they are in good accordance.
c is the critical strain value of adiabatic shear occurrence， p and h the corresponding peak value of strain and stress in the flow stress curve， s the reduction stress value under adiabatic shear, n1, n2, k1, k2 the workpiece material constants.
Table 2 compares the simulation and experimental data of related serrated chip parameters.
It is learned from the comparison of simulation and experimental data of chip character parameters in Table 2 that the error of simulation and experimental data is about 10%.
(2) The error of simulation and experimental data of serrated chip morphology characters is about 10%, which indicates that simulation results are in good accord with experimental data

However, these methods are only for the data reduction and streamlining, no method is adopted to fit the data more effective.
The data measured by using csvread function was imported in MATLAB, and was denoised by wavelet-transformed, saved as .ibl format.
Then the noise data was imported into Pro/E software, small plane characteristics was formed by envelope processing and small plane processing.
Conclusions The experimental measurement was used to data extract the surface with different roughness in turning aluminum products.
Small plane characteristics were formed by data preprocessing, then the double three B-spline was used to surface fitting, the solid model and surface contact model were established finally.

Fuzzy matrixes were constructed according to the investigation data, in which occurrence probability ranking, effect severity ranking and detection difficulty ranking are all weighted analyzed.
Because of lack of relevant data of severity of fault mode of diesel engine in the process of computation, the results have some subjectivity and fuzziness [2].
Table 1 Fuzzy factors grade Factor grade Influence factor I1 I2 I3 I4 I5 Frequency of fault occurrence u1 Often occur Sometimes occur Accidentally occur Infrequence Occur Rare occur Influence severity u2 Fatal Consequence Loss of important function Function reduction Slight influence Rarely influence Difficult degree of test u3 Completely unable to test No test Observe in the test Observe in the previous test Directly observe The highest level of weighting set of each factor can be obtained by the method above, is the probability, severe degree and the weight set of no detectable respectively.

Control of prototype of linear position actuator SMA On the basis of the collected experiment data [1] it was concluded that SMA wires are nonlinear and time variant.
There is a shortage of data on this phenomenon in the literature.
According to Fig. 3 output data is not constant as in the fuzzy logic 1 type but they constitute a set of numbers from a definite interval.
The controller RimpC1 data are as follows: • 2 inputs: set value SV (symmetric distribution with 2 mm - 6 intervals) and error e, • 1 output: manipulated variable MV (value of current density in an impulse), • error fuzzyfication (Fig. 4), Fig. 4.
Finding the exact values of G100% and Gwyl, from the possible set constitutes this reduction fuzzy logic set 2 type to 1 type.

Little further gain reduction occured between 400°C and 500°C.
The value of α is based on a fit to experimental data [11] that agrees well with the Callaway model [12] for the thermal conductivity of a solid.
The value of κ0 was obtained by fitting this curve to recently published data for nitrogen-doped 4H-SiC substrates [1], similar to the material used for this work.
This data is also in good agreement with the Callaway model.
We extracted the junction temperature of a 3 µm x 10 µm device and fitted this data with a theoretical calculation using a simple thermal model.

Authors also present different data on carrier lifetime recovery upon defect annealing [2,3,5-7].
Thus, analysis of the above data shows that there are large scatter in the characteristics of defect which arises in Si and solar cells under light action.
In this paper the new data on the defects, appearing under illumination with the light with a spectral composition close to solar radiation, in silicon with a high content of boron and oxygen are presented.
The data obtained are shown in Fig. 3.
The data obtained also suggest that by the action of light or heat treatment a recombination-enhanced diffusion of oxygen or oxygen-containing defects takes place according to the mechanism proposed in [32].

Then the whole Rankine cycle 4 basic processes are realized. 3.3 Data reduction and analysis The whole ORC systems was taken for reaching the steady condition when all the sensors do not change.
The test data are recordered by data acquisition systems, in which the sample rate is 0.2HZ.
To more clear analyze the thermodynamic process, the data reduction are expressed by the list equation: 1）The total quantity of engine waste heat ,Q Q=Qw+Qe (1) 2）The working fluid absorb heat quantity, Q: (2) 3）The work expander do ,W： (3) 4） Isentropic efficiency of expander ： (4) 5) Heat rejection for the condenser, Qc： (5) 6) Generating efficiency of ORC (6) 7) Net generate efficiency of ORC systems (7) In the above equation, the Qw,Qe are the heat quantity of coolant and
From the ORC systems beginning to generate elecrity to the steady condition, the test data recording time is about 2 hours and 24minutes.