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Ergebnis der Suche nach: tit all "Machine Learning Techniques"
im Bestand: Gesamter Bestand

1721 - 1730 von 1742

	1721	Using machine learning techniques to predict the cost of repairing hard failures in underground fiber optics networks Enthalten in Journal of Big Data Bd. 7, 24.8.2020, Nr. 1, date:12.2020: 1-16
	1722	Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data Enthalten in Scientific reports Bd. 14, 4.3.2024, Nr. 1, date:12.2024: 1-11
	1723	Using Machine Learning Techniques to Test the Load Capacity Curve Hypothesis: A Classifier-Lasso Application on Global Panel Data Enthalten in Biophysical economics and sustainability Bd. 10, 19.2.2025, Nr. 1, date:6.2025: 1-18
	1724	Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra Enthalten in BMC bioinformatics Bd. 24, 9.1.2023, Nr. 1, date:12.2023: 1-15
	1725	Utilizing contemporary machine learning techniques for determining soilcrete properties Enthalten in Earth science informatics Bd. 18, 14.1.2025, Nr. 1, date:1.2025: 1-30
	1726	Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques Enthalten in BMC bioinformatics Bd. 25, 27.3.2024, Nr. 1, date:12.2024: 1-17
	1727	VacPred: Sequence-based prediction of plant vacuole proteins using machine-learning techniques Enthalten in Journal of biosciences Bd. 45, 27.8.2020, Nr. 1, date:12.2020: 1-9
	1728	Various optimized machine learning techniques to predict agricultural commodity prices Enthalten in Neural computing & applications Bd. 36, 16.4.2024, Nr. 19, date:7.2024: 11439-11459
	1729	Vehicle-specific power-based emission modeling using unsupervised machine learning techniques Enthalten in Environmental science and pollution research Bd. 32, 23.6.2025, Nr. 27, date:6.2025: 16120-16141
	1730	Versatile time-window sliding machine learning techniques for stock market forecasting Enthalten in Artificial intelligence review Bd. 57, 16.7.2024, Nr. 8, date:8.2024: 1-20