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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Advances in Data-Driven Computing and Intelligent Systems978-981-99-9524-0Series ISSN 2367-3370 Series E-ISSN 2367-3389

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2367-3370 The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book is useful for academicians, research scholars, and industry persons.978-981-99-9523-3978-981-99-9524-0Series ISSN 2367-3370 Series E-ISSN 2367-3389

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Caves and Karst of Turkey - Vol. 1served that the proposed model (DLN-SD) brings 96.0% precision, 98.0% recall, and 98.0% accuracy and performs best among all three models. It is concluded that the DLN-SD shows an improvement of 15% over AlexNet and 9% over GoogleNet to detect seizures from the EEG dataset.

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Cave and Karst Systems of the Worldp utilized to reflects the characteristics of the human motion. The CNN-based proposed system can steadily outperforms abnormal behavior detection, especially for the lightweight models when given a small among of training samples.

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Geology of the Greenbrier Valley,iction Dataset. The prediction performance of each model was evaluated using mean absolute error (MAE), root mean square error (RMSE), and the coefficient of determination (. score). The results suggested that among all the evaluated models, the XGBoost Regressor model was the most suitable prediction model for soil properties.

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Greg A. Brick,E. Calvin Alexander Jr.l imaging systems, RT-PCR, ELISA, etc. are capable of overcoming these limitations of food safety practices by using the ML algorithms. The ML technique has great potential to overcome food safety issues and future applications in the food sector.