全面
发表于 2025-4-1 04:56:26
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Kindle
发表于 2025-4-1 06:11:47
978-3-031-35444-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
抱怨
发表于 2025-4-1 11:17:09
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Concrete
发表于 2025-4-1 18:10:58
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paroxysm
发表于 2025-4-1 20:27:10
Predictive Sentiment Analysis Model Regarding the Variation of the Dollar Exchange Rate, social networks as pillars. In the first phase, NB and RF were used and obtained an accuracy of 90% for both models’ four (04) combinations. For the results of the second phase of the research, better results were obtained with the SVM algorithm, achieving a percentage of accuracy of 92.82% to predict the variation of the dollar exchange rate.
哭得清醒了
发表于 2025-4-2 02:22:37
,Maximising Influence Spread in Complex Networks by Utilising Community-Based Driver Nodes as Seeds,m those communities are then ranked according to a range of common centrality measures. We compare the influence spreading power of these seed sets to the results of selecting driver nodes at a global level. We show that in both synthetic and real networks, exploiting community structure enhances the power of the resulting seed sets.
organism
发表于 2025-4-2 04:10:53
Smart Doorbell with Telegram Notification for Multifamily Dwellings,rge is not present. This system is achieved by using a Raspberry Pi to connect all the devices used and send all the data collected to the respective people, according to a list of identifiers for each group of people living in the building.
空中
发表于 2025-4-2 07:20:27
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Baffle
发表于 2025-4-2 12:57:35
,Soil Organic Carbon Prediction Using Digital Color Sensor in Peru,tiple linear regression, generalized additive models, regression tree cubist, random forest, K-nearest neighbors and neural networks. The results show that the simplest models were competitive with complex models, suggesting to incorporate other predictor variables to improve the models performance.
URN
发表于 2025-4-2 18:42:45
1865-0929 a Science, Machine Learning, Natural Language Processing, Semantic Web, Data-driven Software Engineering, Health Informatics..978-3-031-35444-1978-3-031-35445-8Series ISSN 1865-0929 Series E-ISSN 1865-0937