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On the one hand, the less the error of forecast, the better, but its inordinate reduction may be accompanied by significant complication of used mathematical tools [3].
After that possibility of reduction of its error is evaluated.
After that the deviation between the actual data and the linear trend is calculated in percent.
Comparison table of the error of the “seasonal curves” model and the deviation of the load curve from the linear trend Power system Forecast «Seasonal curves», [%] Mean deviation from trend, [%] Krip.,[%] Кocc., [%] Power system 1, [%] 1,65 0,14 0,916 0,953 Power system 2, [%] 1,99 0,30 0,847 0,927 Power system 3, [%] 2,88 0,90 0,759 0,907 Power system 4, [%] 3,57 1,19 0,781 0,892 Power system 5, [%] 3,37 0,86 0,777 0,893 Power system 6, [%] 3,24 1,20 0,776 0,874 Power system 7, [%] 3,49 1,64 0,759 0,907 Power system 8, [%] 3,96 1,68 0,615 0,803 Power system 9, [%] 4,37 2,12 0,574 0,805 Power system 10, [%] 4,37 3,50 0,547 0,748 From the obtained results it is seen that the value of the non-regular component decreases with reduction of the time interval.

After this time, the activity decreases and corrosion products appear causing a adhesion reduction of subsequently applied coatings.
After blasting with cut wire the reduction of the adhesion appears not before 8 hours after blasting because of the different shape of the resulting surface.
The data obtained by this method are further analyzed and may provide important information on the composition of the system in terms of its electrical properties.

The statistical parameters are based on the available literature, test data and survey results.
In this study, only the first three are considered, the load models are based on the available statistical data, surveys, inspection reports, and analytical simulations.
Table.3 The statistics of the resistance model of suspenders for the example bridge Random variable Distribution nominal value Bias factor Coefficient of variation Normal 1570MPa 1 0.05 Normal 5mm 1 0.05 (2) The resistance model of arch ribs The resistance model of arch ribs of the bridge is calculated using[11] (2) where is the design value of carrying capacity, is reduction coefficient of carrying capacity from slenderness ratio, is reduction coefficient of carrying capacity from eccentricity ratio, and is the design value of carrying capacity of each axial compression short column
From equation (2) to (5), Xu Fuyou[12] gives the resistance model of arch ribs, (6) where and are variables and mean value of which reduction coefficient of carrying capacity is derived from influence of slenderness ratio and eccentricity ration respectively, and are variables and mean value of steel resistance respectively, and and are variables and mean value of which resistance uncertainty from concrete restrained by steel tubular is considered respectively.
The load and resistance parameters are treated as random variables, and the statistical parameters are taken from the available literature, test data and survey results.

According to the analysis of the landslide monitoring data, it is revealed that the amount of the cumulative displacement of the landslide depends on the monitoring cycle.
The correlation study mainly got qualitative relation through analyzing statistical data.
The period of collecting landslide displacement monitoring data is fifteen days to thirty days.
The period of collecting data was increased from 30 days to 60,180, 360 days, and the different ST(T is the period of collecting data T days) in one year were got.
When the monitoring period is Tn+1, it is that a value is increased between two monitoring data based on the period Tn.

Reduction of intensity or rigidity and losses of quality of the bridge structures can induce the changes of modal parameters of the structure.
In fact, the structural damage is essentially due to the reduction of intensity or stiffness and losses of quality of the bridges.
Therefore, we must comprehensively consider and analyze the multi-order data.

The modern embedded multimedia electronic devices rely on dynamically-allocated data structures to store and process their data, as a result, the demand of its memory capacity and dynamic are increasing unceasingly.
Up to know, some methods which have been performed are basically based on the optimization to hardware and the algorithm of multimedia applications so that achieves the reduction for searching space, raises the program execution efficiency [1,3], they have not considered optimization of the dynamic data structures.
Dynamic data structures optimization procedure Embedded multimedia applications access and process data using dynamic data structure.
Running the MNSGA-II, we obtain a set of dynamic data structure instantiation , which variable should be instantiation by which dynamic data structure.
In this task we consider a basic memory hierarchy that consists of a main shared memory and a L1 data cache.

Therefore, a reduction in the testing time is very significant.
Therefore, a reduction in the testing time is very significant.
(a) 2-D drawing data of a wave spring (t=0.5 mm) (b) 3-D schematic drawing data of a wave spring (c) etched sheet metal plate (d) Ejected spring Figure 1 Etched sheet metal plate.
Fig. 1(a) presents representative 2-D drawing data, for which a wave type of spring was proposed to effectively disperse the stress.
Fig. 1(b) depicts the 3-D drawing data.

It is therefore found that KIC are nearly constant and there is no reduction in air up to 1973K.
Eq. (3) was fitted to the data on Al2O3/YAG eutectic composite, Al2O3 and sapphire by a least-squares deviation regression analysis of KII /KIC on KI /KIC.
The empirical equation provides fairly good fits to the data on Al2O3/YAG eutectic composite, Al2O3 and sapphire specimen with the constants C=2.18(1773K), 1.70(1573K) and 2.64(1773K), respectively.
On the other hand, Eq. (4) also provides good fits to the data on Al2O3/YAG eutectic composite, Al2O3 and sapphire specimens with the constants m=4.00(1773K), 2.00(1573K) and 1.00(1773K), respectively as shown in Fig. 4(b).
(3) The empirical equation provides fairly good fits to the data on Al2O3/YAG eutectic composite, Al2O3 and sapphire materials.

Prospects for the Use of ANN for the Measurement of LM Microelements The principal advantages arising from the use of ANNs, along with the impedance method, are the following: -the adaptive structure of the INS, which receives information, learns and captures useful links in the complex interaction of input and output information; -the ability to summarize and process incomplete or noisy data on the results of measuring the components of the impedance of the LM samples.
In general, the advantages of the impedance method are automatic registration and processing of results, reduction of research time, simple preparation of samples for research, reduction of working time and materials, documenting measurement results, etc.
Based on the capabilities of the developed analyzer, the following method can be proposed for measuring the components of the impedance of an LM sample: - submission of a constant voltage of a given magnitude to a sample of a LM; - measurement of the voltage level on the sample after passing a direct electric current through it; - measurement of the level of direct current after passing through the sample; - submission to the sample alternating current voltage of known frequency; - measurement of the level of alternating voltage on the sample after passing through it an alternating electric current; - measurement of the level of alternating current after passing through the sample; - processing of measured data and calculation of unknown values.
The reduction in the active state with the help of PPA S3, which connects VS2 to the OS and repeats the whole process in the same way as described in claim 1, except that the AC voltage signal first passes through the RB. 2.2.
It is necessary to highlight the important properties of the device software: the ability to simultaneously measure and analyze the results obtained earlier; process data using a large number of models and techniques; set parameters and calibration dependencies for each LM sample; the possibility of increasing the performance of the device; ensuring the task of compatibility and data exchange with other software.

Furthermore, a comparison with the outcomes emerging from monotonic flexural tests, in terms of maximum flexural capacity and failure mechanisms, will be presented, with the aim of obtaining useful data for assessing the reliability of current design methods and code prescriptions, mainly based on currently available monotonic tests results.
As a general remark, second phase stiffness is similar regardless of the loading procedure adopted, except for G225 panel, where a reduction can be observed in the case of cyclic loading.
If moment decrements registered at the same deflection level are analyzed, after a first significant moment reduction, a progressive attenuation and stabilization of the process can be observed.
As can be observed, cyclic loading causes in general a small capacity reduction, falling within the range 7.6 – 9.7% for glass, aramid-glass and basalt fibers.
As for bond tests, the trend of reduction can be described assuming a nonlinear behavior, with a first larger reduction followed by a progressive attenuation.