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1081 |
Land subsidence prediction in coal mining using machine learning models and optimization techniques
Enthalten in Environmental science and pollution research Bd. 31, 19.4.2024, Nr. 22, date:5.2024: 31942-31966
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1082 |
Landslide identification using machine learning techniques: Review, motivation, and future prospects
Enthalten in Earth science informatics Bd. 15, 3.11.2022, Nr. 4, date:12.2022: 2063-2090
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1083 |
Landslide susceptibility zonation using integrated supervised and unsupervised machine learning techniques in the Bhagirathi Eco-Sensitive Zone (BESZ), Uttarakhand, Himalaya, India
Enthalten in Journal of earth system science Bd. 133, 6.7.2024, Nr. 3, date:9.2024: 1-25
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1084 |
Landslides and flood multi-hazard assessment using machine learning techniques
Enthalten in Bulletin of engineering geology and the environment Bd. 81, 18.8.2022, Nr. 9, date:9.2022: 1-23
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1085 |
Leading dietary determinants identified using machine learning techniques and a healthy diet score for changes in cardiometabolic risk factors in children: a longitudinal analysis
Enthalten in Nutrition journal Bd. 19, 19.9.2020, Nr. 1, date:12.2020: 1-16
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1086 |
Letter to the editor: a response to Ming’s study on machine learning techniques for personalized breast cancer risk prediction
Enthalten in Breast cancer research Bd. 22, 10.2.2020, Nr. 1, date:12.2020: 1-2
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1087 |
Leveraging machine learning and big data techniques to map the global patent landscape of phage therapy
Enthalten in Nature biotechnology Bd. 42, 11.12.2024, Nr. 12, date:12.2024: 1781-1791
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1088 |
Leveraging machine learning techniques and GPS measurements for precise TEC rate predictions
Enthalten in GPS solutions Bd. 28, 29.4.2024, Nr. 3, date:7.2024: 1-16
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1089 |
Leveraging machine learning techniques to analyze nutritional content in processed foods
Enthalten in Discover food Bd. 4, 19.12.2024, Nr. 1, date:12.2024: 1-17
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|
1090 |
Leveraging web scraping and stacking ensemble machine learning techniques to enhance detection of major depressive disorder from social media posts
Enthalten in Social network analysis and mining Bd. 14, 26.12.2024, Nr. 1, date:12.2024: 1-21
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