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Titlebook: Computer and Computing Technologies in Agriculture IX; 9th IFIP WG 5.14 Int Daoliang Li,Zhenbo Li Conference proceedings 2016 IFIP Internat

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書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX
副標(biāo)題9th IFIP WG 5.14 Int
編輯Daoliang Li,Zhenbo Li
視頻videohttp://file.papertrans.cn/235/234342/234342.mp4
概述Includes supplementary material:
叢書(shū)名稱(chēng)IFIP Advances in Information and Communication Technology
圖書(shū)封面Titlebook: Computer and Computing Technologies in Agriculture IX; 9th IFIP WG 5.14 Int Daoliang Li,Zhenbo Li Conference proceedings 2016 IFIP Internat
描述The two volumes IFIP AICT 478 and 479 constitute the refereed post-conference proceedings of the 9th IFIP WG 5.14 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2015, held in Beijing, China, in September 2015. The 122 revised papers included in this volume were carefully selected from 237 submissions. They cover a wide range of interesting theories and applications of information technology in agriculture, including intelligent sensing, monitoring and automatic control technology; key technology and models of the Internet of things; intelligent technology for agricultural equipment; computer vision; computer graphics and virtual reality; computer simulation, optimization and modeling; cloud computing and agricultural applications; agricultural big data; decision support systems and expert systems; 3s technology and precision agriculture; quality and safety of agricultural products; detection and tracing technology; and agricultural electronic commerce technology.
出版日期Conference proceedings 2016
關(guān)鍵詞artificial intelligence; classification; clustering; computer vision; computers in agriculture; crops; dec
版次1
doihttps://doi.org/10.1007/978-3-319-48354-2
isbn_softcover978-3-319-83919-6
isbn_ebook978-3-319-48354-2Series ISSN 1868-4238 Series E-ISSN 1868-422X
issn_series 1868-4238
copyrightIFIP International Federation for Information Processing 2016
The information of publication is updating

書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX影響因子(影響力)




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX被引頻次




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX年度引用




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX年度引用學(xué)科排名




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX讀者反饋




書(shū)目名稱(chēng)Computer and Computing Technologies in Agriculture IX讀者反饋學(xué)科排名




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Study on Landscape Sensitivity and Diversity Analysis in Yucheng City,nse to the different scales, or 18 different scales. The detailed results showed that the decreasing trend was presented from 5?m scale to 210?m scale for each index. Furthermore, we also analyzed the scale effects for different landscape index. Finally, based on image by the change of LSI, PAFRAC,
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Study on the Prediction Model Based on a Portable Soil TN Detector,ablished by seven different methods (MLR, PLSR, SVM, BPNN, GA?+?BPNN, GA?+?SVM and PSO?+?SVM). The model established by genetic algorithm (GA) optimizing BP neural network was optimal, with R. of 0.94, R. of 0.78, RMSEC and RMSEP of 0.037 and 0.067. The results showed that the soil total nitrogen co
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https://doi.org/10.1007/978-94-007-5061-6nse to the different scales, or 18 different scales. The detailed results showed that the decreasing trend was presented from 5?m scale to 210?m scale for each index. Furthermore, we also analyzed the scale effects for different landscape index. Finally, based on image by the change of LSI, PAFRAC,
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