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1331 |
Simplified reliability analysis of multi hazard risk in gravity dams via machine learning techniques
Enthalten in Archives of civil and mechanical engineering Bd. 18, 9.11.2017, Nr. 2, date:6.2018: 592-610
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1332 |
Single-trial extraction of event-related potentials (ERPs) and classification of visual stimuli by ensemble use of discrete wavelet transform with Huffman coding and machine learning techniques
Enthalten in Journal of neuroEngineering and rehabilitation Bd. 20, 2.6.2023, Nr. 1, date:12.2023: 1-17
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1333 |
Skin Cancer Detection and Classification System by Applying Image Processing and Machine Learning Techniques
Enthalten in Optical memory and neural networks Bd. 32, 25.9.2023, Nr. 3, date:9.2023: 197-203
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1334 |
Soft Clustering for Enhancing ITU Rain Model based on Machine Learning Techniques
Enthalten in Wireless personal communications Bd. 120, 24.5.2021, Nr. 1, date:9.2021: 287-305
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1335 |
Soft computing techniques for predicting the compressive strength properties of fly ash geopolymer concrete using regression-based machine learning approaches
Enthalten in Journal of building pathology and rehabilitation Bd. 9, 19.6.2024, Nr. 2, date:12.2024: 1-29
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1336 |
Soft computing techniques for predicting the properties of raw rice husk concrete bricks using regression-based machine learning approaches
Enthalten in Scientific reports Bd. 13, 4.9.2023, Nr. 1, date:12.2023: 1-21
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1337 |
Software defined networking based network traffic classification using machine learning techniques
Enthalten in Scientific reports Bd. 14, 29.8.2024, Nr. 1, date:12.2024: 1-16
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1338 |
Software Enhancement Effort Prediction Using Machine-Learning Techniques: A Systematic Mapping Study
Enthalten in SN Computer Science Bd. 2, 22.9.2021, Nr. 6, date:11.2021: 1-15
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1339 |
Soil liquefaction in seismic events: pioneering predictive models using machine learning and advanced regression techniques
Enthalten in Environmental earth sciences Bd. 83, 16.3.2024, Nr. 7, date:4.2024: 1-28
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1340 |
Solar Energy Forecasting Using Machine Learning and Deep Learning Techniques
Enthalten in Archives of computational methods in engineering Bd. 30, 24.2.2023, Nr. 5, date:6.2023: 3059-3079
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