Application of machine learning in corrosion inhibition study

Thankappan Sasilatha; Susai Rajendran; Senthil Kumaran Selvaraj; Časlav Lacnjevac; Rajendran Joseph Rathish

doi:10.5937/zasmat2203280R

Authors

Thankappan Sasilatha AMET University, Department of EEE, Kanathur, Chennai, India Author
Susai Rajendran St. Antony's College of Arts and Sciences for Women Thamaraipady, Department of Chemistry, Corrosion Research Centre, Tamil Nadu, India + Pondicherry University, Puducherry, India Author
Senthil Kumaran Selvaraj Vellore Institute of Technology (VIT), Department of Manufacturing Engineering, School of Mechanical Engineering-SMEC, Tamil Nadu, India Author
Časlav Lacnjevac University of Belgrade, Faculty of Agriculture, Serbia Author
Rajendran Joseph Rathish PSNA College of Engineering and Technology, Dindigul, India Author

DOI:

https://doi.org/10.5937/zasmat2203280R

Keywords:

Artificial Intelligence, Machine learning, Deep learning, Neural Networks, Algorithms, The Input Layer, The Hidden Layer and The Output Layer

Abstract

Artificial intelligence is a branch of science concerned with teaching machines to think and act like humans. Machine learning is concerned with enabling computers to perform tasks without the need for explicit programming. Machine Learning enables computers to learn without the need for explicit programming. Machine Learning is a broad field that encompasses a wide range of machine learning operations such as clustering, classification, and the development of predictive models. Machine Learning (ML) and Deep Learning (DL) research is now finding a home in both industry and academia. Machine Learning technologies are increasingly being used in medical imaging. To detect tumours and other malignant growths in the human body. Deep Learning is making significant contributions to the advancement of industrial robotics. Machine learning algorithms are used in the self-driving car industry to guide the vehicle to its destination. Deep Learning and Machine Learning are also used in corrosion science and engineering. They are used to choose the inhibitor molecules from a large pool of available molecules.

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