Search results

In order to avoid the weighing of the subjective in computational process, this paper introduces a Projection Pursuit model to the real estate investment decision-making to achieve the dimensionality reduction process of multi-index high-dimensional data.
Model based on PP Proposed by Friedman and Tukey in 1974, Projection Pursuit is used to analyze high-dimensional data, in particular the non-normal nonlinear analysis of high dimensional data as a statistical method [4,5].
Projection Pursuit method can overcome the success of high-dimensional data "dimension curse" brought about by serious difficulties, it is because of its analysis of the data in the low-dimensional subspace conducted for 1 to 3-dimensional projection space data points is dense enough, and sufficient data in the projection space can be found in the structure or characteristics.
Projection target function Projection Pursuit Method is integrated p-dimensional data into a for the projection of one-dimensional projection of the direction of the value of : (2) Here: —unit length vector.
Table 1 lists seven original data values in the six programs: Table 1: The real estate investment program of the index value Program Expectations of net present value index Failure rate of investment The risk of loss of value (million) The risk of profit value(million) Expectations of net present value(million) Financial net present value(million) Economic net present value(million) A 3.80% 3.30% 0.0910 0.0920 0.0830 0.0850 0.0790 B 3.75% 3.20% 0.0715 0.0910 0.0820 0.0900 0.0890 C 4.67% 2.50% 0.0920 0.0780 0.0950 0.0860 0.0950 D 2.32% 2.70% 0.0700 0.0800 0.0960 0.0900 0.0980 E 2.21% 2.30% 0.0800 0.0800 0.0850 0.0830 0.0890 F 2.70% 3.50% 0.1000 0.0850 0.0840 0.0800 0.0700 The normalized matrix can be obtained: = Selected the initial parent population size, crossover probability , mutation probability ,,to accelerate the cycle 20 times, reached the maximum indicator function value of 0.4213, the best projection direction: And then substituting into formula (2), you can get the comprehensive

The subject of this paper was to investigate the run-off-effect of metals from can into the solutions and analyze the data retrieved by Electrochemical Impedance Spectroscopy (EIS) and Linear Voltammetry (LV) techniques.
[4] World health organization, food and agriculture organization of the united nations: Prevention and Reduction of Food and Feed Contamination, 1st Edition, FAO and WHO 2012, p. 178

From the microscopic observation data, matrix crack, fiber breakage and delamination are the main impact damages of honeycomb sandwich panels.
The newly developed materials started to be widely used for the industries since the later part of 1990, owing to the excellent advantages in the weight reduction, endurance and the anti-corruption compared with the existing metallic products.

VOCs recovery technology on Chinese oil terminal has been listed as one of five “key energy saving and reduction projects during 12nd five years plan period” by Water Department of MOT, which can bring huge economic benefit.
For responding to the call of national energy safe and emission reduction (ESER), Ministry of Transportation P.R.CHINA (MOT) issued a notification about “Overall program of ESER during 12nd five years period”, and took “VOCs recovery technology project” as one of five key ESER project; the relevant work has been carried out since 2011 by VOCs recovery research group (VOC group).
According to already calculated data that is VOCs recovery can bring appreciable economic benefit and social, environmental benefit, VOCs recovery on oil terminal was deemed to have a vast potential to future development in China [2].
Acknowledgements Some of information was supported by the WTB, PetroChina, Sinopec, some Chines oil terminal and VOCs system producers from both domestic and international, Thanks for their data providing.

Diesel engine components, particularly cylinder heads, are made of cast irons and replacing them with aluminium alloys could result in a significant weight reduction and consequently better fuel efficiency.
Various alternatives such as compensation of the alloy's increased price by reduction or elimination of its post-processing are considered to keep overall manufacturing costs low.
The application of the first derivative curves and adequate data smoothing techniques allowed significant improvement to the resolution of the dilatometer signal.
It was observed that elongation was lower for Alloy B in agreement with other published data indicating that simultaneous increase in Cu and Mg improves ultimate and yield strengths at the expense of ductility [1-2].

In contrast with the experimental data of device B, and the result shows that the lean blowout performance of the device A is superior to the device B at low operating condition.
Especially, the airflow from the primary holes, which has a great impact on the main combustion zone, is divided into multiple parts to achieve a reduction in the size of the main recirculation zone, strengthen the local combustion and reduce the lean blowout limit value.
Table 2 Lean blowout data of devices A, B Test scheme Inlet air flow rate[m3/h] Fuel gas flow rate[L/min] Excess air coefficient SA 115 10 20.1 SB 70.17 15 8.19 In Table 2, the scheme SA is for device A; scheme SB is for device B.

An improved adaptive algorithm for INS/GPS system Lidong Wang1,a ,Ying Zhao1,b,Ni Zhang2,c 1Electronic and Information Engineering College, University of Science and Technology Liaoning Anshan, Liaoning , 114051,China 2Anshan Haihui Automation Company, Anshan, Liaoning , 114051,China awangld5600@163.com , brebeccazhao0217@126.com, c15712367@qq.com Keywords: Kalman filter, adaptive-filter, Sage-Husa algorithm, INS/GPS Abstract: In INS/GPS system, the changing of initial conditions and the quality of the data can affect the convergence of the conventional Kalman filter algorithm.
Algorithm introduction Conventional Kalman filtering algorithm Kalman filter is a linear optimal recursive data processing algorithm.
Kannel: Design and Testing of an Intelligent GPS Tracking Loops for Noise Reduction and High Dynamics Applications.

The human body's dynamic and static data show that the parameter of detail parts specification has great changes, while the parameter of control parts' specification parameter has small changes.
Experimental Size measurement and variable analysis under body static condition Through data collation and variable analysis, dynamic parameters of the human body is obtained, which provides data reference for the restructuring of sheath dress and suitability inspection
The experiment rules out individual differences of limiting the movements due to physical factors in order to ensure the relative stability of the measurement data
Data collection, reduction and analysis Due to initial data collection may overload, after finishing and analysising the variables and parameters, only study and analyse the body surface of related position which may influence the suitability of the sheath dress pattern, which can provide data reference for detail structure of sheath dress pattern of elastic fabric based on dynamic change.
According to the data both under static and dynamic condition, the change of body surface extension parameter of detail specification is larger under moving condition, while there is no obvious change in control parts (see Table 1).

Control of their accuracy parameters is complicated task consisting from some high requirements needed for rotation, positioning, signal processing, object adjustment and data processing.
During the process of calibration the results of measurements are collected and accumulated data is analyzed by information system.
Data management of mechatronic system The amount of data generated by such systems is usually vast in an average complexity of the system.
Adding information entropy parameters helps to determine the uncertainty of performed measurements, therefore improving the accuracy of data processing. 5.
Data processing and information assessment in scales measurement simulation, in: Proceedings, XVII IMEKO World Congress, 2003, pp. 1053–1056

The reduction of strength with increasing tilt angle is explained by superimposed shear stresses
-200 -100 100 200 300 400 -40 -30 -20 -10 10 20 30 40 σ1 / MPa τ12 / MPa Hill Failure Criterion Experimental Data Fiber Tensile Failure Matrix Shear Failure Fiber Buckling Failure -200 -100 100 200 300 400 -40 -30 -20 -10 10 20 30 40 σ1 / MPa τ12 / MPa Hill Failure Criterion Experimental Data Fiber Tensile Failure Matrix Shear Failure Fiber Buckling Failure Figure 5.
Based on three on-axis experiments, a tensile test, a compression test, and a shear test, all necessary input data can be generated which are necessary as input data for the finite element model.
Calculated and experimental data of elastic properties (left) and strength (right) dependent on angle between loading direction and fiber orientation under compressive and tensile loading conditions.
The model can be used efficiently as all necessary input data can be derived from three mechanical tests as tensile, compressive, and shear test.