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- W4312133786 abstract "The conventional way of experimentation and analysis of tribological properties is tedious and expensive. To overcome this and simplify the methods of tribological testing, a new technique has been introduced using Artificial Intelligence. It involves using artificial neural networks to learn the problem and analyze it effectively. A neural network works by parallel processing and evaluates the required parameters with limited data. The quality of predictions in a neural network depends on the available datasets, and it increases proportionately with the provided datasets. This helps in modeling physical mechanisms, which could then be used to simulate an experiment in the long term. Implementation of this technique in the aerospace, automotive industries, and tribological testing will simplify the procedure and reduce the cost of testing. This review on the application of Artificial Intelligence in tribology will help to understand the different models and approaches involved to predict the various tribological properties without performing experiments for a long duration." @default.
- W4312133786 created "2023-01-04" @default.
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- W4312133786 date "2022-12-13" @default.
- W4312133786 modified "2023-09-25" @default.
- W4312133786 title "Artificial Intelligence in the Tribology: Review" @default.
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- W4312133786 doi "https://doi.org/10.1007/978-981-19-5482-5_31" @default.
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