By Yun Qiu, Jingchao Fan, Lin Hu, Guomin Zhou (auth.), Daoliang Li, Yingyi Chen (eds.)
The two-volume set IFIP AICT 392 and 393 constitutes the refereed post-conference court cases of the sixth IFIP TC five, SIG 5.1 foreign convention on laptop and Computing applied sciences in Agriculture, CCTA 2012, held in Zhangjiajie, China, in October 2012. The 108 revised papers awarded have been rigorously chosen from various submissions. They disguise a variety of fascinating theories and functions of data expertise in agriculture, together with web of items and cloud computing; simulation types and decision-support platforms for agricultural construction; clever sensor, tracking, and keep an eye on know-how; traceability and e-commerce expertise; laptop imaginative and prescient, special effects, and digital fact; the appliance of knowledge and verbal exchange know-how in agriculture; and common info provider expertise and repair platforms improvement in rural components. The fifty three papers incorporated within the first quantity specialise in selection aid structures, clever structures, and synthetic intelligence applications.
Read Online or Download Computer and Computing Technologies in Agriculture VI: 6th IFIP WG 5.14 International Conference, CCTA 2012, Zhangjiajie, China, October 19-21, 2012, Revised Selected Papers, Part I PDF
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Extra info for Computer and Computing Technologies in Agriculture VI: 6th IFIP WG 5.14 International Conference, CCTA 2012, Zhangjiajie, China, October 19-21, 2012, Revised Selected Papers, Part I
Because the popular Read-Write ware usually uses TI or PHILIPS CMOS chip, such as EM4095, the emission power was limited when the CMOS chip was produced. The Read-Write ware cannot recognize the tag with a longer distance. This way has many limits in some special areas. In this article, the operation of identification and Read-Write is always done in the water, at the same time, the tag is small and the parent fish is usually big, so the Read-Write distance between the tag antenna and the CMOS chip must be limited.
It selects the attribute that have the maximum information gain ratio and classify the training samples, aims at minimizing the system entropy when branching, and improve the computing speed and accuracy. The simulation results that using decision tree to predict dissolved oxygen content are shown as Fig. 1. Fig. 1. DO predict results of decision tree DO Warning Warning refers to measure a factor in present and the future, and predict abnormal state and possible injury . On the early warning process, firstly, we analyze the surrounding environment and conduct early warning on object's internal factors in quality and quantity.
Acknowledgements. Thanks to the domain experts in Beijing Freshwater Fisheries Technology and Engineering Research Center for their long term support. : A Wireless System for Monitoring Polymer Encapsulations. In: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2007, August 22-26, pp. : Neural network architecture for linear programming. In: International Joint Conference on Neural Networks, IJCNN, June 7-11, vol. 3, pp. : A New Method for Learning Decision Trees from Rules.