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ANN generated a network between inputs and output with the entered test data.
The experimental data are trained by using the Levenberg-Marquardt (LM) algorithm.
Sufficient accuracy on the test data set or the maximum number of iteration whichever first activated is adopted for the model.
It is recorded that the training is optimized at fifth iterations i.e. sufficient accuracy of test data is achieved shown in Fig. 8.
The FFB is applied with a few data to check the suitability of ANN in the ISF Process too.

Table 1 Characteristic experimental and grain size analysis data.
Characteristic mechanical data and experimental conditions are summarized in Table 1.
The data obtained in the constant strain rate experiments (Fo39-42) were included in the analysis.
Using a conventional power law type strain rate vs. stress relation (έ ~ σ n) the stress exponent, n, was calculated from linear regression leastsquares fits to the data.
As none of our observations point to major dislocation activity, only the grain switching and/or the excess vacancies model appear applicable to our data.

The equilibrium adsorption data and the model parameters were evaluated.
The isotherm study indicates that adsorption data fit well with the Langmuir model and Pseudo second-order kinetics.
Comparisons with literature data Table.3 summarizes some relevant literature data that have been applied to various photo-catalyst adsorbent and operating conditions on adsorption of HA from aqueous solutions.
The data clearly indicated that Mercury lamp (100W) and UV-Vis as a light source shows higher photo-degradation efficiency (>90%).
The isotherm study indicates that adsorption data fit well with the Langmuir model and Pseudo second-order kinetics.

Users’ potential needs are tapped while qualitative data are analyzed with SCAT qualitative tool.
Nagoya University Takashi Otani Professor summarized the analysis method of SCAT for qualitative data that is suitable for small-scale data,and discovered internal relation models through non-digital examination of the observed data[4].In this research,we will use the SCAT analysis tool.
Questionnaires will be designed after qualitative data about users’ goals and behaviors are collected.
SCAT qualitative data analysis tool.
The non-digital slicing analysis of its qualitative data with the application of SCAT qualitative tool is helpful to locate the internal relation models, suitable for the integration of data on a small scale, assist designers work out new design concepts.

These tests are simulated using an initial set of data, arbitrarily chosen.
Material data.
Material data in case of isotropic hardening [K, N, mm, MPa] Temp.
For the second set of data, the shear parameter N of the Hill’s law, which cannot be correctly defined by a tensile test alone, is combined to the Swift law data and the back-stress parameters to be fitted by the inverse method.
For confidential reasons, these data are not specified here.

XRD data showed the support data to confirm the hydroxide phase formation as intermediate for carbonate and accelerate the CO2 chemisorption reaction.
The combination of nano-CuO on BAC become a good adsorbent which can stimulate the CO2 reduction programme as well as reduce the CO2 emissions during BAC production.
Data 11 (1982), 1-409

First, we use c-means clustering to generate fuzzy partitions and eliminate redundant data, and then map the original data set into fuzzy interval, in the end, we extract the fuzzy association rules on the fuzzy data set as providing the basis for proper decision-making.
On the basis of previous studies, in this paper, we put forward the fuzzy clustering method of data preprocessing. first, we use c-means fuzzy clustering to extract the data distribution information ,thus each attribute interval is divided into several fuzzy data partition and then the quantitative data are allocated into fuzzy interval.
Finally, we extract fuzzy association rules in fuzzy data set.
In this paper, we first use fuzzy c-means clustering algorithm to extract the distribution information of the data, and then convert the original transaction data of numerical attributes into the fuzzy partition data sets, second, generate the fuzzy partition for each attribute and eliminate the redundant data, and we get a rough fuzzy partition.
An Independent Rough Set Approach Hybrid with Artificial Bee Colony Algorithm for Dimensionality Reduction[J].

Introduction With the increase of fossil fuel consumption and the energy price uncertainty, the reduction of available existing energy resources and the exacerbation of the ambient atmospheric environment where the inhabitants dwell have attracted much substantial concerns in the last few decades, and consequently the actions for energy conservation and emission reduction are necessitous and essential for sustainable development of the human beings.
Therefore, with the background of energy structure regulation in China, both the heating system and fuels used need updating in order to gain achievement of energy conservation and emission reduction [5].
On the other hand, the effective utilization of different types of coals is also significant to energy conservation and emission reduction in DH.
In an attempt to fulfill those requirements, the DH system for an economic district of a Northeast China metropolis is utilized as the case study, the its “temperature-heat load-duration” diagram is plotted based on basic meteorological data; the economy-oriented optimization technique is then employed to deal with the coal blending and gas usage problem in DH; finally, the air pollutants emission and total heat supply cost variation trends are further discussed under the different thermalization coefficients of the DH system in this paper.
Yamashita, Effects of coal blending on the reduction of PM10 during high-temperature combustion 1, Fuel. 87 (2008): 2997-3005 [14] D.Z.

The reduction factor of pouring thickness is considered excessively and the situation of thickness greater than 4m is not considered.
According to the data comparison, “Building Construction Handbook” and “Technical Specification for Thermal Cracking Control of Mass Concrete of Port and Waterway Engineering”, the temperature rise formulas are modified as following.
The temperature rise reduction coefficients corresponding to different thickness are shown in Table 7.
Table 7 Temperature rise reduction coefficient Pouring thickness [m] 0.50 1.00 1.50 2.00 2.50 3.00 Temperature rise reduction coefficient ξ 0.28 0.46 0.55 0.62 0.68 0.74 Pouring thickness [m] 3.50 4.00 4.50 5.00 5.50 6.00 Temperature rise reduction coefficient ξ 0.80 0.85 0.90 0.95 0.99 1.00 The calculation temperature in center of concrete can be calculated by Eq. (5).
The reduction factor of pouring thickness is considered excessively and the situation of thickness greater than 4m is not considered.

The reduction was ascribed to the phenolics, terpenoids, polysaccharides and flavones or other poyphenol compounds present in the plant extracts.
Reduction takes place in a few minutes as indicated by the gradual change of color from colorless to yellow and reddish brown of the aqueous solution after addition of napier (P. purpureum) leaf extract.
The rate of the Ag+ ions reduction was slow during the first 5 minutes, as indicated by low absorbance at a wavelength around 430nm as shown in Figure 1.
The inset of Figure 1 illustrates the reduction of silver ions takes place at a faster rate and saturation of data occurs at 240 min which would indicate the completion of reaction.
An immediate reduction of silver ions in the present investigation might have resulted to the phytochemicals like flavinoids, alkoloids, saponnins and tannins present in the napier leaf extract.