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tit all "Machine Learning Techniques"
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141
A novel spatiotemporal prediction approach to fill air pollution data gaps using mobile sensors, machine learning and citizen science techniques
Enthalten in npj climate and atmospheric science Bd. 7, 19.12.2024, Nr. 1, date:12.2024: 1-12
142
A study on machine learning techniques for the schema matching network problem
Enthalten in Sociedade Brasileira de Computação: Journal of the Brazilian Computer Society Bd. 27, 23.11.2021, Nr. 1, date:12.2021: 1-29
143
A survey of machine learning techniques for improving Global Navigation Satellite Systems
Enthalten in European Association for Speech, Signal and Image Processing: EURASIP journal on advances in signal processing Bd. 2024, 28.6.2024, Nr. 1, date:12.2024: 1-40
144
A Survey on Machine Learning Techniques for Heart Disease Prediction
Enthalten in SN Computer Science Bd. 6, 1.4.2025, Nr. 4, date:4.2025: 1-17
145
A systematic review on machine learning and deep learning techniques in the effective diagnosis of Alzheimer’s disease
Enthalten in Brain Informatics Bd. 10, 14.7.2023, Nr. 1, date:12.2023: 1-15
146
Accurate compressive strength prediction using machine learning algorithms and optimization techniques
Enthalten in Journal of engineering and applied science Bd. 71, 2.1.2024, Nr. 1, date:12.2024: 1-20
147
Active learning on stacked machine learning techniques for predicting compressive strength of alkali-activated ultra-high-performance concrete
Enthalten in Archives of civil and mechanical engineering Bd. 25, 12.11.2024, Nr. 1, date:1.2025: 1-35
148
Addressing IT Capacity Management Concerns Using Machine Learning Techniques
Enthalten in SN Computer Science Bd. 3, 29.10.2021, Nr. 1, date:1.2022: 1-15
149
Advanced and hybrid machine learning techniques for predicting compressive strength in palm oil fuel ash-modified concrete with SHAP analysis
Enthalten in Scientific reports Bd. 15, 10.2.2025, Nr. 1, date:12.2025: 1-23
150
Advanced machine learning techniques for cardiovascular disease early detection and diagnosis
Enthalten in Journal of Big Data Bd. 10, 17.9.2023, Nr. 1, date:12.2023: 1-29
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