Výsledky vyhledávání - "Mangal, Ankita"

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A comparative study of feature selection methods for stress hotspot classification in materials

Autor: Mangal, Ankita, Holm, Elizabeth A.

The first step in constructing a machine learning model is defining the features of the data set that can be used for optimal learning. In this work we discuss feature selection methods, which can be used to build better models, as well as achieve mo

Externí odkaz: http://arxiv.org/abs/1804.09604

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Applied Machine Learning to Predict Stress Hotspots II: Hexagonal close packed materials

Autor: Mangal, Ankita, Holm, Elizabeth A.

Stress hotspots are regions of stress concentrations that form under deformation in polycrystalline materials. We use a machine learning approach to study the effect of preferred slip systems and microstructural features that reflect local crystallog

Externí odkaz: http://arxiv.org/abs/1804.05924

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Applied Machine Learning to Predict Stress Hotspots I: Face Centered Cubic Materials

Autor: Mangal, Ankita, Holm, Elizabeth A.

We investigate the formation of stress hotspots in polycrystalline materials under uniaxial tensile deformation by integrating full field crystal plasticity based deformation models and machine learning techniques to gain data driven insights about m

Externí odkaz: http://arxiv.org/abs/1711.00118

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Using Big Data to Enhance the Bosch Production Line Performance: A Kaggle Challenge

Autor: Mangal, Ankita, Kumar, Nishant

This paper describes our approach to the Bosch production line performance challenge run by Kaggle.com. Maximizing the production yield is at the heart of the manufacturing industry. At the Bosch assembly line, data is recorded for products as they p

Externí odkaz: http://arxiv.org/abs/1701.00705

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