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The success of these techniques is also affected by the presence of noise in experimental data.
The methodology is completely data driven; the evolution of the data is estimated without information of physical processes [12].
The data processing phase for damage detection will be discussed in this work.
Data processing Moving Principal Component Analysis (MPCA).
Dubes: Algorithms for Clustering Data, Prentice Hall (1988)

Schematic illustration and specification of residential SOFC-CGS Building data and input loads.
The input load data at 1-minute intervals of the SOFC-CGSs simulation programs [4] includes occupant-related electricity, thermal load by air-conditioning, and the domestic hot water demand for the winter calculation period (from November to next March).
Finally, input load data by power and heat (at one minute intervals) was created based on obtained data for calculating period of winter.
Result and discussion The output data of the SOFC-CGS simulation program is energy demand of electricity and natural gas bought from the company, which can be converted to primary energy by conversion factors.
It claims that primary energy demand reduction is increased with air temperature decrease.

In terms of economy and efficiency, the carbothermal reduction is the best choice due to introduction of inexpensive starting materials [6].
Therefore, the carbothermal reduction process of oxide by carbon has been most widely used to industrial mass production.
In the Al(OH)3+SiO2+C mixture having the stoichiometric molar ratio of Al4SiC4, there were distinct two-step carbothermal reduction reactions; (i) carbothermal reduction of SiO2 between 1300 and 1600 o C, (ii) carbothermal reduction of Al2O3 above 1500 o C.
However, the XRD datum presents clear difference from that of Barczak, indicating the formation of highly oriented powder along the c-axis.
The XRD datum informs that the synthesized Al4SiC4 powder may have hexagonal plate-like morphology, which was confirmed by SEM observation (fig. 3.).

Fuzzy Logic based Sensors data Fusion for Mobile robot navigation S.
The schemes used by Sugeno's car [1] involved the extraction of specific state variables from sensor data before the fuzzy control stage.
Thus, the sensor data have been matched to a world model.
The disadvantages in the robot described by Pin, et al. [2] features 15 ultrasonic rangefinders, without matching data to a world model.
The context data are denoted by a fuzzy set D and the control action is denoted by a fuzzy set C.

According to 2 and Eqs.3, its reduction ratio Rr = 20.
(a) Reduction ratio Rr =20 (b) Reduction ratio Rr =50 (c) Reduction ratio Rr =100 Fig.2.
Planetary gear reducers with simple planet gears The Gear Data of Planetary Simple Gear Reducer In following, the planetary simple gear reducer shown in Fig. 2(a) will be the example to illustrate how to design the two ring gears with different shift coefficients to engage the same planet gear.
Table 1 shows its corresponding gear data.
Gear data of planetary simple gear reducer shown in Fig. 2(a) Planet gear 3 Ring gear 4 Ring gear 5 Teeth No. 16 38 40 Normal Module (mm) 2.0 2.0 2.0 Shift coefficient (mm) 0.2 0.58 -0.18 Pitch Dia.

Variable precision rough set(VPRS) model and formal concept analysis are studied in this paper, include algorithm of reduction attribute and extraction rule.
Step 2: If FL needs to be reduced, then using a rule reduction algorithm to reduce FL. 3.
But the traditional recommendation systems have some shortcomings, such as data sparsity and digging out the potential demand.
The primary content of this dissertation is to apply formal concept analysis technology to obtain all connotative concepts and hierarchy of them automatically from the designated data, which is not under the influence of developer.
The primary content of this dissertation is to apply rough concept lattices technology to obtain all connotative concepts and hierarchy of them automatically from the designated data, which is not under the influence of developer.

Each pair of tracks are installed with a data collector and all data collectors carry out a two-way data exchange with the same measurement controller.
The measurement controller is used to receive and deal with both the weight data from the data collector and the video data from video server.
The equipments required reduce a lot which lead to a greatly reduction of investment costs.
Fig. 1 Traditional data acquisition system Fig. 2 Improved data acquisition system The Improved Data Acquisition System Structure of the Improved System.
● Fast data transmission, the maximum rate is 10Mbps

The characteristics of medical data make large differences between medical data mining and conventional data mining [1].
A Preprocessing for the Massive Data in Hepatopathy Information System Data preprocessing is an important step which usually takes about 70% of the time in the process of a complete data mining [3].
The characteristics of medical data such as privacy, diversity, integrity, redundancy and timeliness make large differences from conventional data mining [4].
Preprocessing of massive data in liver disease patient information system includes as follow: Fig. 1 Data mining and aided diagnosis system of hepatopathy 1) Anonymization and identity transformation: Due to medical information involves the patient privacy issues, besides the need of the general data preprocessing, medical data also requires special data processing such as name-anonymization and identity-transformation for patient records, thus separates the relationship between patients and patient records. 2) Medical Text standard: The explanation that medical experts do for images, signals or other clinical data in medical text information is usually nonstandard, so it is necessary to standardize the text data [5].
C The Classification Algorithm for Medical Image Data We research a new classification method that based on the combination of rough set and SLIQ decision tree, which combine the two methods’ advantages, namely using rough set data reduction, remove the redundant attributes and decision tree method is then used to generate the classification rules effectively.

In the paper, combined with artificial intelligence algorithms, data mining is employed in BOF endpoint control for effective analysis of data characteristics, reduction of noise and irrelevant data terminal on the converter control goals, extraction of useful knowledge from database, and promotion the accuracy of BOF endpoint control.
Data Preparation.
The data set containing 103 records has been obtained by the first data refinement, which the incomplete and incorrect data has been excluded.
Siau .Industrial Management & Data Systems.
Transaction on Knowledge and Data Engineering.

A cost which incorporates both the cost of production processes and the cost arising from the many potential risks associated with any reduction.
The findings illustrate the effectiveness of the proposed approach in the JIT system with focus on simultaneous cost-risk reduction.
Data was collected from fabric-cutting department of Hong Kong-owned apparel manufacturing company to validate the proposed optimisation method.
The objective function (F) of the proposed model is to minimise the total cost of the final product, which includes the product cost and the risk cost resulting from this reduction.
Amer, A Novel Optimisation Model for Simultaneous Cost-Risk Reduction in Multi-suppliers Just-in-Time Systems, J.