Titlebook: Big Data Analytics for Smart Transport and Healthcare Systems; Saeid Pourroostaei Ardakani,Ali Cheshmehzangi Book 2023 The Editor(s) (if a

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书目名称Big Data Analytics for Smart Transport and Healthcare Systems网络公开度学科排名




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书目名称Big Data Analytics for Smart Transport and Healthcare Systems被引频次学科排名




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书目名称Big Data Analytics for Smart Transport and Healthcare Systems年度引用学科排名




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书目名称Big Data Analytics for Smart Transport and Healthcare Systems读者反馈学科排名

考得

Glower

Big Data for Social Media Analysis During the COVID-19 Pandemic: An Emotion Analysis  Based on Influhe COVID-19 pandemic. The study also investigates the relationship between COVID-19 trends or topics and public sentiments on social networks. Machine learning is used to verify the correlation between emotion on social media and the COVID-19 pandemic trends. The study concludes with a prediction mo

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WITH

Robert Fantina,Andriy Storozhuk,Kamal Goyal, reaching an accuracy of 99.89%. The preprocessing stage is proven to be vital for the performance of the LSTM model. As a result, models using our preprocessed nine features are much more accurate on this freight transportation prediction task. Discussions are also raised to understand better frei

药物

SEO Hub: Utilities and Toolsets,red with four classifiers, including Multilayer Perceptron, Decision Tree, Multinomial Logistics Regression, and LR one versus rest. According to the results, the Random Forest model outperforms the benchmarks regarding prediction accuracy. The findings of this chapter help optimise prediction accur

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https://doi.org/10.1007/978-1-4842-1766-5he COVID-19 pandemic. The study also investigates the relationship between COVID-19 trends or topics and public sentiments on social networks. Machine learning is used to verify the correlation between emotion on social media and the COVID-19 pandemic trends. The study concludes with a prediction mo

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加入

Big Data-Enabled Time Series Analysis for Climate Change Analysis in Brazil : An Artificial Neural Nate data and analyze the changing climate trends in the same province. An artificial neural network is established as the model in this project to implement this objective. The performance shows that this model can complete this classification task.

口诀

Optimized Clustering Model for Healthcare Sentiments on Twitter: A Big Data Analysis Approache experiment results indicate that self-organized map model with the TF-IDF extraction method can achieve the best clustering accuracy. Moreover, the optimized model can have great potential to handle large-scale data in real practice.