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1321 |
Safety Risk Assessment and Risk Prediction in Underground Coal Mines Using Machine Learning Techniques
Enthalten in Institution of Engineers, India. Karnataka State Centre: Journal of the Institution of Engineers (India) / Series D Bd. 102, 7.10.2021, Nr. 2, date:12.2021: 495-504
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1322 |
Sales forecasting by combining clustering and machine-learning techniques for computer retailing
Enthalten in Neural computing & applications Bd. 28, 3.2.2016, Nr. 9, date:9.2017: 2633-2647
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1323 |
Sarcopenia prediction using shear-wave elastography, grayscale ultrasonography, and clinical information with machine learning fusion techniques: feature-level fusion vs. score-level fusion
Enthalten in Scientific reports Bd. 14, 2.2.2024, Nr. 1, date:12.2024: 1-10
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1324 |
Secure routing in the Internet of Things (IoT) with intrusion detection capability based on software-defined networking (SDN) and Machine Learning techniques
Enthalten in Scientific reports Bd. 13, 21.10.2023, Nr. 1, date:12.2023: 1-18
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1325 |
Securing social spaces: machine learning techniques for fake profile detection on instagram
Enthalten in Social network analysis and mining Bd. 14, 8.12.2024, Nr. 1, date:12.2024: 1-14
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1326 |
Segmentation and Metallographic Evaluation of Aluminium Slurry Coatings Using Machine Learning Techniques
Enthalten in High temperature corrosion of materials Bd. 101, 26.10.2024, Nr. 6, date:12.2024: 1497-1512
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1327 |
Seismic characterization of carbonate stringers using machine learning techniques: an example from the western flank of South Oman Salt Basin
Enthalten in Scientific reports Bd. 14, 28.12.2024, Nr. 1, date:12.2024: 1-18
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1328 |
Sense disambiguation for Punjabi language using supervised machine learning techniques
Enthalten in Sādhāna Bd. 44, 31.10.2019, Nr. 11, date:11.2019: 1-15
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1329 |
Sentiment classification on product reviews using machine learning and deep learning techniques
Enthalten in International journal of system assurance engineering and management Bd. 15, 10.11.2024, Nr. 12, date:12.2024: 5726-5741
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1330 |
Several machine learning techniques comparison for the prediction of the uniaxial compressive strength of carbonate rocks
Enthalten in Scientific reports Bd. 12, 5.12.2022, Nr. 1, date:12.2022: 1-13
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