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Several methods for generating and displaying such meteorological data have been developed.
Boiler model data.
Table 3 and 4 contain data used for the boilers.
Energy price data.
[16] Nord Pool Spot ASA. http://www.nordpoolspot.com/Market-data1/Downloads/ Historical-Data-Download1/Data-Download-Page/.

The pretreatment tasks are done including the point cloud data reduction Chord where the deviation sampling method is used.
Fig.1 Broken mold’s point cloud data Pretreatment of Broken Mold’s Point Cloud Data CMM measurement non-contact measurement inevitably imports data errors during the scan. especially in some sharp edges and border.
So it is necessary to pre-process the gathered discrete point cloud data to get satisfying data.
That is the data points should be reduced, reduced noise, aligned and relocated, however, the feature data of broken area should not be reduced to prevent data loss data distortion.
Fig.3 Point cloud data reduction of broken mold Surface Remodeling of Broken Mold After finishing the point cloud pretreatment, firstly , the mold contour is built.

The data obtained showed that the inclusion of PET aggregate reduce the strength performances of concrete.
All the data obtained were combined into one single graph to develop a preliminary mix design nomograph for PET concrete.
The modulus of elasticity is calculated based on data of strain stress recorded experimentally.
Meanwhile, the reduction of MOE ranging from 13.69% to 67.74%.
While others is developed by referred to best line fit to all data plotted into the nomograph.

This showed that in acidic pH conditions the thermodynamic driving force for metal reduction is significantly low.At pH 4, the values of reduction increased to 63.1 %.
For pH 7, 8,9 and 10, the percentage reduction further increased to 95.2%, 93.1% 88.6%and 80.2%, respectively.
The complexation of copper with citric acid,favored the reduction of copper due to decreased electron hole recombination.
It is reported[5] that the reductions of Cu(II,I), Cu(I,0) and Cu(II) couples are more favorable with increasing pH.
A large number of experiments show that TiO2 all have the same maximum resources quantity, the largest in the data, catalytic efficiency increases, and increase with the data big, than the largest after data, catalytic efficiency has slightly lower, this is mainly because of the suspension of TiO2 incident light to cover.

A parameter reduction method based on fuzzy rough sets was proposed.
Fundamentals on Fuzzy Rough Sets A structural data used for classification learning can be written as an information system, denoted by , where U is a nonempty and finite set of samples {x1, x2 ,..., xn}, called a universe, A is a set of attributes (also called features, inputs or variables) {a1, a2, ... , am} to characterize the samples.
The objective of rough set based attribute reduction is to find a subset of attributes which has the same discriminating power as the original data and has not any redundant attribute.
Fig.2 Dependency Function There are 6 parameters in the reduction set.
A forward greedy search algorithm is proposed for attribute reduction.

Optimal Uncorrelated Unsupervised Discriminant Projection Yu’e LIN 1,a ， Yongcun GUO2,b 1School of Computer Science and Engineering, Anhui University of Science and Technology Huainan, 232001, China 2College of Mechanical Engineering, Anhui University of Science and Technology Huainan, 232001, China alinyu_e@126.com, bguoyc@aust.edu.cn Keywords: manifold-based；dimensionality reduction；face recognition；small sample size problem；uncorrelated Abstract.Unsupervised Discriminant Projection (UDP) is a typical manifold-based dimensionality reduction method, and has been successfully applied in face recognition.
PCA constructs a low-dimensional representation of the original data via minimizing the reconstruction error.
But both PCA and LDA fail to explore the essential structure of the data.
A lot of researchers are attracted to straightforwardly find the inherent nonlinear structure of the data and then many manifold-based learning algorithms are proposed.
Defining affinity matrix is as follows (1) Where represents the neighborhood relation between data sampleand .

Extension data mining is a combination of Extenics and data mining [5-7].
It’s shown by studies that the existing data mining theory and technology will be developed and new data mining theory and technology will be generated by the combination of Extenics and data mining.
In a database, the transformation used on certain data will also cause transformations of correlated data.
Actually, in the studies on text data, image or video data, and Web data, it should also be considered that the influence of transformations on data is a field that should be involved in the extension data mining.
Data Mining Technology.

OFDM can achieve high data rates with achievable complexity.
Cipher generators at each location create high data rate "random" optical bit streams (cipher) from the specified key at the same bit rate as the data stream to be encrypted.
The optical cipher and data bits are then combined by an exclusive-OR operation at the data rate to generate the encrypted bits.
Finally, the encrypted optical data stream is transmitted to the receiving point.
In fact, the complexity of the all-optical encryption system remains relatively constant as the data rate increases, thus making the system the most attractive at the highest data rates.

These data were interpreted to find the potential region for adsorption or desorption of the fluorosurfactant and its influence on metal deposition.
An EcoChemie µ-Autolab II potentiostat with NOVA 1.7 software was used to carry out potential sweeps and record data.
Figure 2 shows that the addition of surfactant has cause a shift in reduction potential.
The CV trace shows that Cu reduction now occurs at -0.43 V.
These data show that the surfactant adsorption blocks the Cu discharge.

Analysis of the mangrove roots coordination pattern had been conducted by gathering data at study site located at Kemaman, Terengganu and the data had been plotted in Gambit software for simulation purpose in Fluent Inc software.
From the simulation, the study found that the numerical model results were approximately consistent with the measured data of tsunami inundation flow around the mangrove forest at Pekarang Cape.
The data created in the AutoCAd software were plotted with 1:2.5 ratio compare to the actual side observation data in order to validate the simulation data with the in-house experiment data.
Henceforth, the AutoCAD data was transfer into Gambit software for meshing purpose.
For data validation, an in-house experiment using 1:2.5 scale models of mangrove trees will be conducted to validate the data obtained by the simulation.