Search results

Research on Evaluation of Soil Fertilities of Farmland at County Level in Nongan Based on Data Mining Li Ma, Guifen Chen, Liying Cao, Yueling Zhao Jilin Agricultural University, Changchun, Jilin, China Mary19801976@sohu.com,752922110@qq.com,24426266@qq.com,14964585@qq.com Keywords：Evaluation of Soil Fertilities of Farmland; Rough set; Decision tree; Data mining Abstract：This research used the method of rough set and decision tree in data mining, building the evaluation model of soil fertility, to evaluate NongAn of Jilin province farmland productivity.
Select HAYATA 452 final, 11 paddy, vegetable 9, located in the county's 26 towns, farmland will generate sample data underlying database.
But in soil domain knowledge, a lot of data, such as soil humus layer thickness or floating-point values, are continuous values or the form of floating point Numbers, so the data must be processed before performing discrete attribute reduction, in order to accelerate the efficiency of knowledge acquisition.
With Soil data, the condition attribute is the 24 item properties as the evaluation factors above, the decision attribute is the soil fertility level, the rough set attribute reduction process is: Obtain the nuclear of condition attributes, and use it as the initial reduction.
In this paper, decision tree method is used to construct the decision tree model, using the rough data after intensive Jane，after reduction of the soil data input the decision tree algorithm, do decision tree structure and pruning, to get fertility level of the decision tree.

In OFDM data is transmitted simultaneously through multiple frequency bands, the effects of multipath delay spread can be minimized.
OFDM has been proposed for many radio systems such as the next generation mobile communication, wireless LAN, digital audio/video broadcasting, and high-speed cellular data.
The Papr in Ofdm Systems In OFDM systems, the baseband time domain signal consisting of N subcarriers may be written as , (1) Where is the subcarrier spacing, NT denotes the useful data block period.
Partial Transmit Sequences (PTS).In the PTS approach, the input data block is partitioned into V non-overlapping subblocks, which are combined to minimize the PAPR [4].
However, for both schemes, to recover the data, the receiver must to know which vector had actually been used.

The hydrogen reduction reaction kinetic parameters of different particle’ sizes Cu2O were calculated by DTA-TG-DTG data.
(4) Namely (5) Use TG data calculate α, rise temperature velocity β was 15℃·min-1, was obtained by TG and DTG data.
Reaction progression was defined as: n = 1.26I1/2 (6) By the DTA curve data, according to equation (6) the reaction progression n was can obtained.
Use α data, β data, data, n data and equation (5) the k was calculability obtained.
Fig. 3 DTA-TG-DTG curves of sample 1#~3# Using DTA-TG-DTG curves data and equation (2) calculated the different size the cuprous oxide hydrogen reduction reaction apparent activation energy E and frequency factors A.

Analysis on Efficiency Evaluation of Regional Energy-saving and Emission-reduction Based on DEA Model Shuang Wang Economics and Management College, Dalian University, Dalian, 116600, China wshuang1021@sina.com Keywords: Energy-saving and emission-reduction; DEA; Evaluation index system Abstract.
Introduction The concept of "energy-saving and emission reduction" was first proposed in "Eleven-Five" program and made energy-saving and emission reduction work closely together.
CICA in Canada has listed energy-saving and emission-reduction and audit evaluation in different industry, in which multiple aspects of energy-saving and emission-reduction and audit evaluation indicators was included in utilities, manufacturing, and traffic industry etc.
The Brief Review of Evaluation Method  Data envelopment analysis, DEA has developed into a kind of non-parametric frontier efficiency analysis method on the basis of the relative efficiency evaluation by A.Charnes and W.W.Copper scholars etc. this method is often used in input and output system of the production and living for management, decision-making and efficiency and benefit evaluation, etc, at present which has become a widely used and effective analysis tool in the field of management science and system engineering.
It mainly uses the linear programming method, on the basis on the original sample data are divided into input index and output index, gets to evaluate effectively to decision making units(DMU), for the purpose is to reflect whether the DMU can  achieve the decision-making results of “spending as little as possible, to get maximum benefit”.

a15500092211@163.com, b15010203158@qq.com, cearly4932@163.com, d345319286@qq.com, echhdai@163.com Keywords: Multivariate Data Visualization, Clutter reduction, Parallel Sets, measurement ratio, corresponding degree for categorical measures Abstract.
Classic part-labeled data visualization method Parallel Sets is applied to represent visualization of multivariate data with measures.
Introduction Multivariate data with measures of metric attributes [9] has been explored in depth in data mining (DM).
Sales data from supermarket are used to prove the efficiency of the improved algorithm.
TVBPS：A Method Based On The Parallel Sets to Measure Properties of Multivariate Data Temporal Data Visualization [J].

This emission reduction potential optimization model puts forward the best pollutant emission reduction plan to satisfy the business enterprise decision making and guide the effective implementation of the refining chemical industry pollutant emission reduction task.
All kinds of input data, for the calculation of oil refining chemical industry pollutant emissions reduction potential model, have been shown in Table 1 and Table 2.
Table 1 Pollution control equipment parameters for refining and chemical industrial Pollutants Pollution Control Measures Removal Rate(%) Unit Processing Costs (104 t/104 yuan) Buiding Area (m³) SO2 Limestone Gypsum Wet Flue Gas Desulfurization (LGWFGD) 95 1000 500 Mobil Wet Flue Gas Cleaning System (MB-WFGCS) 90 1050 500 Belco Edv Wet Flue Gas Desulfurization (BEDV) 95 950 500 Wet Flue Gas Sulfuric Acid Process (WFGSAP) 97 850 400 THIOPAQ Biological Process (THIOPAQ-B) 97 1000 600 Ammonia Washing Method (AWM) 95 1000 500 Recycling Magnesium Oxide Method (RMOM) 95 900 500 NOx Selective Catalytic Reduction Method (SCR) 85 3336 500 Non Selective Catalytic Reduction(NSCR) 50 840 500 Table 2 Data for pollution reduction potential model of refining and chemical enterprises Pollutants Pollutant Source Industrial Emissions Standards (mg/m3) Wastegas Quantity (m3/h) Pollutant Concentration (mg/m3) SO2 Heating Furnace 850 335 1690 Industrial Boiler — 0.16 0 Catalytic Cracking
According to the above data, combined with the established optimization models and linear programming method, the maximum SO2 and NOx emission reductions of oil refining chemical enterprise were 4810.69 and 1573.04 tons, obtained from the computer.
(2) For Pollutant NOx, the reductions of SO2 is 1573.04 tons by optimization model calculation, the optimal emission reduction scheme is installing Selective Catalytic Reduction Method (SCR) on the Heating Furnace, which is the highest than related industrial emissions standards.

The dimentional data then will be used to model a steel wheel rim model by using CATIA V5.
The shape optimization process will be applied when the data has be transferred to FEM data.
Each optimization is done beginning at the datum and not continuous from previous reduction to allow comparable results.
Static structural analysis had been done to the datum and optimized design to obtain the results of maximum stress, total deformation and mass reduction.
Eventhough the maximum stress of optimal design selected is not as lower as datum, but if compared to the higher reduction target, 15% of reduction target is the better option.

Studying the Possibility of Obtaining Titanium Powder of Various Sizes by Alumino-Thermic Reduction L.I.
In the reduction process granules of titanium powder and corundum were obtained.
The temperature was register using the NI USB-TC01 Thermocouple Measurement Device from National Instruments and firmware Temperature Logger, all data from the device was output to a computer.
In the Table 1 shows data on the change in powder weight after alkaline treatment.
The best aluminothermic reduction results were obtained during the reduction of sandy and floury rutile with aluminum shavings, i.e. samples №1 and №3 of the charge combination.

This change can be analysis by the torque of wring, the data test under wind-force of 5 grades is shown in Fig.3.
Such result needs more time -load data to satisfy process of data transformation for obtaining the dynamic performance of wring.
For accurately analysing the working load of hydraulic system in typical working conditions, the root mean square value is to transform the data from testing and integrates the mean value and standard deviation.
Choosing a set of load data from Table.1, the strength test is imposed to reel and the result shown in Table 2.
The critical load of reel is computed by data in Table.2 due to Eq.3, its value is 520.52 kN, which shows that the component will not damage after one million repeatedly load test.

With this system the user can know the forecasting data and decomposition results so as to make corresponding guiding policy.
Data Structure.
The data structures of “predicting the future carbon intensity” and “target decomposition” contain input and output data structure.
The input data of “predicting the future carbon intensity” is the specific year, the output data is the estimated carbon emission and carbon intensity in that year.
The input data of “target decomposition” is carbon intensity and the current year, the output data is the decomposed carbon emission and the target usage of coal, oil, natural gas and non-fossil fuel.