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標(biāo)題: Titlebook: Information and Communication Technologies for Agriculture—Theme II: Data; Dionysis D. Bochtis,Dimitrios E. Moshou,Panos M. P Book 2022 Sp [打印本頁]

作者: 劉興旺    時間: 2025-3-21 18:23
書目名稱Information and Communication Technologies for Agriculture—Theme II: Data影響因子(影響力)




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data影響因子(影響力)學(xué)科排名




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data網(wǎng)絡(luò)公開度




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data被引頻次




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data被引頻次學(xué)科排名




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data年度引用




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data年度引用學(xué)科排名




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data讀者反饋




書目名稱Information and Communication Technologies for Agriculture—Theme II: Data讀者反饋學(xué)科排名





作者: orient    時間: 2025-3-21 21:57
Thymios Dimopoulos,Christos Vasilakos,Thanasis Kizos bottom up efforts toward a more critical approach to sustainability on campus.?We ground our recommendations on findings from campus-wide surveys that were taken by over 8,000 undergraduates in 2016, 2019, and978-3-031-30931-1978-3-031-30929-8Series ISSN 2523-3084 Series E-ISSN 2523-3092
作者: epinephrine    時間: 2025-3-22 02:35
1931-6828 hine learning and artificial intelligent technologies. Part 2 is devoted to the integration of these technologies in agricultural production processes by presenting specific applications in the domain. Part 3 e978-3-030-84150-8978-3-030-84148-5Series ISSN 1931-6828 Series E-ISSN 1931-6836
作者: 刺耳    時間: 2025-3-22 05:41
Roberto F. Silva,Angel F. M. Paula,Gustavo M. Mosta?o,Anna H. R. Costa,Carlos E. Cugnasca
作者: CUR    時間: 2025-3-22 11:20
Roberto F. Silva,Gustavo M. Mosta?o,Fernando Xavier,Antonio M. Saraiva,Carlos E. Cugnasca
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作者: 雇傭兵    時間: 2025-3-22 19:38

作者: 圣歌    時間: 2025-3-22 21:36
Machine Learning Technology and Its Current Implementation in Agriculture interaction. This chapter aims to an introduction towards?understanding what machine learning?is, by highlighting its differences with conventional programming and pointing out some of?its fundamental features. Moreover, different types of machine learning algorithms are described, and examples are
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作者: 偽造者    時間: 2025-3-23 13:23
Integrating Spatial with Qualitative Data to Monitor Land Use Intensity: Evidence from Arable Land –from 1960 to 1980 affecting mainly the hilly uplands as more remote and marginal areas are being converted from crops to grasslands or are abandoned, whereas intensification is the main trend for the next 20?years mainly in the lowlands as modernized agriculture (irrigated fields, land aggregation,
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作者: 暫時休息    時間: 2025-3-24 01:58
Use of Unsupervised Machine Learning for Agricultural Supply Chain Data Labelingsets that contained information from the three systems, and the k-means and self-organizing maps (SOM) models were evaluated on clustering the data and generating labels. The use of principal component analysis (PCA) was also evaluated together with the k-means model. Several supervised and unsuperv
作者: confederacy    時間: 2025-3-24 04:20

作者: 昏迷狀態(tài)    時間: 2025-3-24 10:22
sug- gestions was very large and the response - unexpectedly high. Apart from several papers rejected, as being out of scope, over 100 papers were accepted for presentation. A somewhat unconventional way of presenta- tion was introduced to provide ample time for fruitful and well prepared discussion
作者: 冥想后    時間: 2025-3-24 11:31
Patrick Jackmannumber of sug- gestions was very large and the response - unexpectedly high. Apart from several papers rejected, as being out of scope, over 100 papers were accepted for presentation. A somewhat unconventional way of presenta- tion was introduced to provide ample time for fruitful and well prepared discussion978-3-642-84457-7978-3-642-84455-3
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Athanasios Anagnostis,Gabriela Asiminari,Lefteris Benos,Dionysis D. Bochtise a majority (82%) have not had any contact in the recent past. Of the 14 percent who had had an experience with the police in the recent past, a majority, i.e., 67 percent had themselves contacted the police, while 17 percent had been contacted by the police. Adivasis and Muslims are more likely to
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作者: Embolic-Stroke    時間: 2025-3-25 07:23
Mihály Tóth,János Felf?ldi,László Várallyai,Róbert Szilágyith others—that undergirds relational pedagogies strengthens ideas of sustainability that go beyond techno-scientific or managerial approaches. At the same time, critical environmentalism pushes relational pedagogical practices to engage more deeply?with questions of power, social justice and human-e
作者: 自傳    時間: 2025-3-25 07:32
Eleni Mangina,Elizabeth Burke,Ronan Matson,Rossa O’Briain,Joe M. Caffrey,Mohammad Saffarifrom the 2022 data about coverage of a range of environmental topics, how much students reported learning about environmental concerns, and what they wanted to see emphasized in their coursework. One of the major findings is that students of color, by a large margin, want environmental curricula to
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作者: 小步走路    時間: 2025-3-25 17:44
Ignacio Rubio Scola,Sebastián Rossi,Gastón Bourgesf flow regimes, bubble growth and measuring liquid film thickness. However, widely applicable correlations are needed to predict data accurately. The microchannel heat transport phenomena are still far from being clearly understood. More accurate measuring techniques are necessary. More and more fin
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作者: 蒸發(fā)    時間: 2025-3-26 00:18
Athanasios Podarasany forms of CSE and we will overlook different forms of abuse, including the abuse of boys and young men, by allowing attention to focus on only one. Also, CSE has traditionally been understood as an offence committed by adults, whereas more recent work is revealing worrying numbers of young people
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Dionysis D. Bochtis,Dimitrios E. Moshou,Panos M. PDiscuses variety of knowledge regarding extensive and evolving data management in agricultural systems.Provides up-to-date information and knowledge on agricultural data management.Chapter authors are
作者: 混合物    時間: 2025-3-26 22:28

作者: 圓錐體    時間: 2025-3-27 04:08

作者: induct    時間: 2025-3-27 08:33
You Got Data‥‥ Now What: Building the Right Solution for the Problem solutions to maximizing production and productivity. In the last decade, there has been a rapid expansion in Information and Communications Technology that is now capable of answering these challenges and breaking free of dependence upon manual labor and levels of human skill and experience that wo
作者: 半球    時間: 2025-3-27 10:10

作者: Mirage    時間: 2025-3-27 17:34

作者: 情感脆弱    時間: 2025-3-27 21:08
Application Possibilities of IoT-based Management Systems in Agricultureeet quality requirements, to reduce the environmental impact as well as to improve economic efficiency. The Industry 4.0 concept provides various methods in this regard, including data acquisition based on IoT (Internet of Things), or data analytics based on Big Data, to support the decision-making
作者: 高談闊論    時間: 2025-3-28 01:56
Plant Species Detection Using Image Processing and Deep Learning: A Mobile-Based Applicationuter/data scientists and botanists alike. This chapter describes a deep learning Convolutional Neural Network (CNN), which is trained to perform mobile imagery classification on plant species found throughout Ireland. The dataset of plant-classified RGB images underwent significant pre-processing, p
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作者: 懶惰人民    時間: 2025-3-28 07:10

作者: Ophthalmoscope    時間: 2025-3-28 10:36
Air drill Seeder Distributor Head Evaluation: A Comparison between Laboratory Tests and Computationahe National University of Rosario, are carried out. This test bench has been built to evaluate components of air drill seeder’s pneumatic transport and distribution system. Soybean (Glycine max) seeds are used in the experimental tests. In Computational Fluid Dynamics (CFD) simulations, soybean seed
作者: 揮舞    時間: 2025-3-28 16:28

作者: patriarch    時間: 2025-3-28 19:18
Soybean Price Trend Forecast Using Deep Learning Techniques Based on Prices and Text Sentimentster explores the use of deep learning techniques for predicting soybeans price trends in Brazil. A long short-term memory neural network (LSTM) forecasts the price signal. A convolutional neural network (CNN) generates a sentiment signal based on the sentiment analysis of news headlines. A multi-lay
作者: Expiration    時間: 2025-3-28 23:39
Use of Unsupervised Machine Learning for Agricultural Supply Chain Data Labelingated to identifying production batches and locations of the product throughout the supply chain; (ii) environmental monitoring, considering environmental variables in production, storage and transportation; and (iii) processes monitoring, related to the data describing the production processes and i
作者: triptans    時間: 2025-3-29 07:08
assumption of the existence of a creep potential, which can depend only on the basic or, alternatively, on the principal invariants of the stress tensor, if the material is isotropic. These invariants are the elements of the integrity basis for the orthogonal group. For anisotropic solids the repre
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作者: 從屬    時間: 2025-3-29 14:33
Patrick Jackmann- ford (1960), the second one by J. Hult in Goteborg (1970), and the third one by A.R.S. Ponter in Leicester (1980). The fourth Symposium in Cracow, September 1990, gathered 123 par- ticipants from 21 countries and reflected rapid development of the theory, experimental research and structural appl
作者: micronutrients    時間: 2025-3-29 16:22





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