Software for modeling brazing process of spacecraft elements from widely used alloys

Tynchenko, V. S.; Bukhtoyarov, V. V.; Rogova, Daria; Myrugin, Aleksander; Seregin, Yuriy; Бочаров, А. Н.

doi:10.1109/infoteh53737.2022.9751246

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2024

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Cited by 7 publications

References 16 publications

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Deep Learning for Object Detection in Images Development and Evaluation of the YOLOv8 Model Using Ultralytics and Roboflow Libraries

Kukartsev,

Ageev,

Borodulin

et al. 2024

Lecture Notes in Networks and Systems

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Deep Learning for Object Detection in Images Development and Evaluation of the YOLOv8 Model Using Ultralytics and Roboflow Libraries

Kukartsev,

Ageev,

Borodulin

et al. 2024

Lecture Notes in Networks and Systems

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Performance Analysis of Machine Learning Techniques, Pattern Detection and Model Optimisation

Degtyareva,

Borodulin,

Nelyub

et al. 2024

Lecture Notes in Networks and Systems

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Predictive modelling of post-monsoon groundwater quality in Telangana using machine learning techniques

Olentsova,

Kukartsev,

Orlov

et al. 2024

BIO Web Conf.

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Groundwater quality is vital for public health, agriculture, and industry, especially in regions like Telangana, India. This study analyses and predicts post-monsoon 2020 groundwater quality using data from the Telangana State Groundwater Department. We employed Linear Regression and Random Forest Regression to predict key parameters: pH and Total Dissolved Solids (TDS). Exploratory data analysis revealed significant correlations, such as between TDS and Electrical Conductivity (E.C). The Linear Regression model for TDS performed exceptionally well, with an R2 of 0.985, while the Random Forest model also showed strong results. However, both models exhibited moderate accuracy in predicting pH. The study demonstrates the effectiveness of machine learning models in predicting groundwater quality, offering valuable tools for groundwater management. These findings can aid policymakers and environmental managers in making informed decisions to safeguard water resources.

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Software for modeling brazing process of spacecraft elements from widely used alloys

Cited by 7 publications

References 16 publications

Deep Learning for Object Detection in Images Development and Evaluation of the YOLOv8 Model Using Ultralytics and Roboflow Libraries

Deep Learning for Object Detection in Images Development and Evaluation of the YOLOv8 Model Using Ultralytics and Roboflow Libraries

Performance Analysis of Machine Learning Techniques, Pattern Detection and Model Optimisation

Predictive modelling of post-monsoon groundwater quality in Telangana using machine learning techniques

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