By Wenqin Cao, Haiyan Zhu, Bin Li (auth.), Daoliang Li, Yingyi Chen (eds.)
The three-volume set IFIP AICT 368-370 constitutes the refereed post-conference complaints of the fifth IFIP TC five, SIG 5.1 foreign convention on machine and Computing applied sciences in Agriculture, CCTA 2011, held in Beijing, China, in October 2011. The 189 revised papers awarded have been rigorously chosen from a number of submissions. They conceal quite a lot of fascinating theories and functions of data know-how in agriculture, together with simulation types and decision-support platforms for agricultural construction, agricultural product caliber trying out, traceability and e-commerce expertise, the applying of data and conversation expertise in agriculture, and common info provider expertise and repair structures improvement in rural parts. The sixty two papers incorporated within the first quantity concentrate on determination aid structures, clever structures, and synthetic intelligence applications.
Read or Download Computer and Computing Technologies in Agriculture V: 5th IFIP TC 5/SIG 5.1 Conference, CCTA 2011, Beijing, China, October 29-31, 2011, Proceedings, Part I PDF
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Extra info for Computer and Computing Technologies in Agriculture V: 5th IFIP TC 5/SIG 5.1 Conference, CCTA 2011, Beijing, China, October 29-31, 2011, Proceedings, Part I
The side view of wheat kernel Fig. 3. 3 have presented respectively the color images, binary images and marginal detection images of each view of wheat kernel. Better marginal detection can set a firm foundation for the follow-up Fourier describer. 2 Acquisition of Kernel Marginal Coordinates At First, before doing Fourier describer of kernel shape, the coordinates on marginal images should be ensured, namely, determining each pixel’s position in the images. (x-1 , y+1) (x , y+1) (x-1 , y) (x , y) (x-1 , y-1) (x , y-1) (x-1 , y+1) (x+1 , y) (x+1 , y-1) Fig.
7% samples of the concepts r=-1 in Table 1. 062kw, its credibility is equal to 1. 7% samples of the concepts r=0 in Table 1. Its meaning is: If the clearance value between piston skirt and cylinder material is among 10~36μm, and the clearance value between piston head and cylinder is among 280~340μm, and the 26 R. Dai and X. 388kw, its credibility is equal to 1. 65)—>(r=1) |1 This rule covers 25% samples of the concepts r=1 in Table 1. 714kw, its credibility is equal to 1. 35)—>(r=2) |1 This rule covers 25% samples of the concepts r=2 in Table 1.
However, when value reduction algorithm is carried out, there will be inconsistencies between samples. Therefore decision-making rules are treated as follows. That is part of the decision rules for inconsistency, assuming it can not be simplified, the value of these attributes is fully retained. For the consistent part of the decision-making rule, and inconsistent part of it together, and then only to examine whether the property value of the same part of the decision rule may be eliminated. If you eliminate the value of some properties, its positive field changes, or data table becomes inconsistent, then the property can not be omitted.