Titlebook: Advances in Data-Driven Computing and Intelligent Systems; Selected Papers from Swagatam Das,Snehanshu Saha,Jagdish C. Bansal Conference pr

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Machine Learning Models for Human Activity Recognition: A Comparative Study,ee, andthis is….”. Alice thinks: “The ultra high-speed rabbit showed me many things which I had never seen. Now I will go again to this wonderland, and try to find something new..978-3-319-87091-5978-3-319-61491-5

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On the Dynamics of Non-Spherical Bubblesutilized for recognition. White noise and a retuned voice were employed as data augmentation. An average recognition rate of accuracy 93.25% and WER—Word Error Rate—of 7.84% were obtained by the GRU model, according to the findings.

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Further Elastoplastic Solutionscision, accuracy, loss, F1-score, recall, and AUC-ROC. In addition to this, for enhancing the performance of MLP model,  GridSearchCV has been incorporated to fine-tune the hyper-parameters. During experimentation, the results show that the MLP model incorporated with GridSearchCV optimizer achieves

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Ivan Favero,Jack Sankey,Eva M. Weigantenna selection in Massive MIMO subarray switching architecture. It leverages the benefits of both the SFO algorithm and the elite learning strategy to improve the selection of antennas, thereby optimizing system performance. Sunflower Optimization with elite learning strategy has been proposed an

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Cavity-Enhanced Spectroscopy and Sensingf points among clusters according to their Silhouette coefficients. The result is HWKM+ which, through a small number of restarts, is capable of generating a careful clustering solution with compact and well-separated clusters. The current implementation of HWKM+ rests on Java parallel streams. The