Titlebook: Big Data Intelligence for Smart Applications; Youssef Baddi,Youssef Gahi,Loai Tawalbeh Book 2022 The Editor(s) (if applicable) and The Aut

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拋媚眼

Conducting a Cardiopulmonary Exercise Test,tructure and function of the brain and which have proven effective in capturing the recurring characteristics of time series. In this context, we developed a model based on Recurrent Neural Networks for the prediction of equivalent noise levels produced by a road infrastructure. The model based on t

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Cell Culture for Commercial Settings,e accuracy of almost 2% and a decrease of the prediction error. Based on the findings it can be concluded that the automated optimisation strategies are more efficient and provide a better set of parameters to use within an ANN model, so that an improved prediction accuracy can be achieved. Using th

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迅速成長

Introduction to Cell and Tissue Cultureayes, Support Vector Classifier, Decision Tree, Random Forest, K-Nearest Neighbor, Logistic Regression had used to differentiate the depressed and non-depressed users. Finally, Support Vector Classifier outperforms among all of the investigated and evaluated techniques with 79.90% accuracy, 75.73% p

MUTED

https://doi.org/10.1007/b102298adopting Big Data that can be resolved using Blockchain. Afterward, we overview the Blockchain technology by projecting its components, workflows, classification, and related characteristics. Finally, we present the importance of combining Big Data and Blockchain through reviewing the novel implemen

BYRE

癡呆

https://doi.org/10.1007/b102298he optimized and best prediction to find out the Fake news. To evaluate the proposed framework, three use cases with three different datasets has been developed during this study. The proposed framework will also help to understand what amount of data is responsible for detecting fake news, trying t

Presbyopia

1860-949X through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners..978-3-030-87956-3978-3-030-87954-9Series ISSN 1860-949X Series E-ISSN 1860-9503