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Comparison of the Accuracy of Ground Reaction Force Component Estimation between Supervised Machine Learning and Deep Learning Methods Using Pressure Insoles.

• Authors : Kammoun, Amal^1,2 (AUTHOR) ; Ravier, Philippe¹ (AUTHOR) ; Buttelli, Olivier^1,3 (AUTHOR)

• Source: Sensors (14248220). Aug2024, Vol. 24 Issue 16, p5318. 20p.

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Assessment of Supervised Machine Learning Techniques for Predicting Groundwater Availability in Mexican Aquifers.

• Authors : González Sánchez, Alberto¹ ; Ontiveros Capurata, Ronald Ernesto¹

• Source: International Journal of Combinatorial Optimization Problems & Informatics. Nov2024, Vol. 15 Issue 4, p7-18. 12p.

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Energy parameter modeling in plug-in hybrid electric vehicles using supervised machine learning approaches

• Authors : Bukola Peter Adedeji

Subjects: Multiple Linear Regression; Artificial Neural Networks; Random Forest

• Source: e-Prime: Advances in Electrical Engineering, Electronics and Energy, Vol 8, Iss , Pp 100584- (2024)

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Supervised Machine Learning Techniques for Breeding Value Prediction in Horses: An Example Using Gait Visual Scores.

• Authors : Bussiman, Fernando¹ (AUTHOR) ; Alves, Anderson A. C.¹ (AUTHOR) ; Richter, Jennifer¹ (AUTHOR)

• Source: Animals (2076-2615). Sep2024, Vol. 14 Issue 18, p2723. 22p.

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Diagnosed and subjectively perceived long-term effects of COVID-19 infection on olfactory function assessed by supervised machine learning.

• Authors : Lötsch, Jörn^1,2 (AUTHOR); Brosig, Oskar³ (AUTHOR); Slobodova, Jana⁴ (AUTHOR)

Subjects: *Artificial neural networks; *Supervised learning; *Machine learning

• Source: Chemical Senses. 2024, Vol. 49, p1-14. 14p.

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Objective Supervised Machine Learning-Based Classification and Inference of Biological Neuronal Networks.

• Authors : Barros, Michael Taynnan^1,2 (AUTHOR) ; Siljak, Harun³ (AUTHOR); Mullen, Peter³ (AUTHOR)

Subjects: *Biological classification; *Supervised learning; *Biological networks

• Source: Molecules. Oct2022, Vol. 27 Issue 19, p6256. 23p.

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Supervised Machine Learning Approaches for Predicting Key Pollutants and for the Sustainable Enhancement of Urban Air Quality: A Systematic Review.

• Authors : Essamlali, Ismail¹ (AUTHOR) ; Nhaila, Hasna¹ (AUTHOR); El Khaili, Mohamed¹ (AUTHOR)

Subjects: *Supervised learning; *Air pollutants; *Machine learning

• Source: Sustainability (2071-1050). Feb2024, Vol. 16 Issue 3, p976. 26p.

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Automatic Detection of Sand Fouling Levels in Railway Tracks Using Supervised Machine Learning: A Case Study from Saudi Arabian Railway.

• Authors : Alsahli, Ali¹ (AUTHOR); Alsulmi, Mohammad² (AUTHOR)

• Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ). Apr2023, Vol. 48 Issue 4, p4925-4935. 11p.

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A Review on IoT Intrusion Detection Systems Using Supervised Machine Learning: Techniques, Datasets, and Algorithms.

• Authors : Abdulla, Azeez Rahman¹ ; Jameel, Noor Ghazi M.¹

• Source: UHD Journal of Science & Technology. Jun2023, Vol. 7 Issue 1, p53-65. 13p.

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IOT-Based Medical Informatics Farming System with Predictive Data Analytics Using Supervised Machine Learning Algorithms.

• Authors : Rokade, Ashay¹ (AUTHOR); Singh, Manwinder¹ (AUTHOR); Arora, Sandeep Kumar¹ (AUTHOR)

• Source: Computational & Mathematical Methods in Medicine. 8/30/2022, p1-15. 15p.

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