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26781 - 26790 von 32606

	26781	Machine learning techniques for prediction of multiple sclerosis progression Enthalten in Soft computing Bd. 26, 22.9.2022, Nr. 22, date:11.2022: 12041-12055
	26782	Machine learning techniques for predictive modelling in geotechnical engineering: a succinct review Enthalten in Discover civil engineering Bd. 2, 1.5.2025, Nr. 1, date:12.2025: 1-21
	26783	Machine learning techniques for recycled aggregate concrete strength prediction and its characteristics between the hardened features of concrete Enthalten in Arabian journal of geosciences Bd. 14, 10.11.2021, Nr. 22, date:11.2021: 1-20
	26784	Machine learning techniques for reference evapotranspiration and rice irrigation requirements prediction: a case study of Kerian irrigation scheme, Malaysia Enthalten in Paddy and water environment Bd. 23, 23.7.2025, Nr. 4, date:10.2025: 671-683
	26785	Machine learning techniques for robotic and autonomous inspection of mechanical systems and civil infrastructure Enthalten in Autonomous intelligent systems Bd. 2, 29.4.2022, Nr. 1, date:12.2022: 1-25
	26786	Machine Learning Techniques for Software Maintainability Prediction: Accuracy Analysis Enthalten in Journal of computer science and technology Bd. 35, 30.9.2020, Nr. 5, date:10.2020: 1147-1174
	26787	Machine learning techniques for spatiotemporal traffic prediction in 5G cellular networks Enthalten in Discover applied sciences Bd. 7, 23.9.2025, Nr. 10, date:10.2025: 1-35
	26788	Machine learning techniques for speech emotion recognition using paralinguistic acoustic features Enthalten in International journal of speech technology Bd. 25, 8.7.2022, Nr. 3, date:9.2022: 707-725
	26789	Machine learning techniques for state recognition and auto-tuning in quantum dots Enthalten in npj Quantum information Bd. 5, 21.1.2019, Nr. 1, date:12.2019: 1-10
	26790	Machine Learning Techniques for the Detection of Inappropriate Erotic Content in Text Enthalten in International journal of computational intelligence systems Bd. 13, 11.6.2020, Nr. 1, date:1.2020: 591-603

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