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Titlebook: Information and Communication Technologies for Agriculture—Theme II: Data; Dionysis D. Bochtis,Dimitrios E. Moshou,Panos M. P Book 2022 Sp

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樓主: 劉興旺
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發(fā)表于 2025-3-28 16:28:46 | 只看該作者
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發(fā)表于 2025-3-28 19:18:40 | 只看該作者
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
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發(fā)表于 2025-3-28 23:39:22 | 只看該作者
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
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發(fā)表于 2025-3-29 07:08:25 | 只看該作者
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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發(fā)表于 2025-3-29 10:31:07 | 只看該作者
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發(fā)表于 2025-3-29 14:33:50 | 只看該作者
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
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發(fā)表于 2025-3-29 16:22:28 | 只看該作者
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