Application of machine learning in corrosion inhibition study

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

doi:10.5937/zasmat2203280R

Autori

Thankappan Sasilatha AMET University, Department of EEE, Kanathur, Chennai, India Autor
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 Autor
Senthil Kumaran Selvaraj Vellore Institute of Technology (VIT), Department of Manufacturing Engineering, School of Mechanical Engineering-SMEC, Tamil Nadu, India Autor
Časlav Lacnjevac University of Belgrade, Faculty of Agriculture, Serbia Autor
Rajendran Joseph Rathish PSNA College of Engineering and Technology, Dindigul, India Autor

DOI:

https://doi.org/10.5937/zasmat2203280R

Ključne reči:

veštačka inteligencija, mašinsko učenje, duboko učenje, neuronske mreže, algoritmi

Apstrakt

Veštačka inteligencija je grana nauke koja se bavi učenjem mašina da misle i deluju kao ljudi. ašinsko učenje se bavi omogu avanjem računarima da izvršavaju zadatke bez potrebe za eksplicitnim programiranjem. ašinsko učenje omogu ava računarima da uče bez potrebe za eksplicitnim programiranjem. ašinsko učenje je široko polje koje obuhvata širok spektar operacija mašinskog učenja kao što su grupisanje, klasifikacija i razvoj prediktivnih modela. Istraživanje mašinskog učenja ( L) i dubokog učenja (DL) sada pronalazi dom i u industriji i u akademskim krugovima. Tehnologije mašinskog učenja se sve više koriste u medicinskom snimanju. Za otkrivanje tumora i drugih malignih izraslina u ljudskom telu. Duboko učenje daje značajan doprinos napretku industrijske robotike. Algoritmi mašinskog učenja se koriste u industriji automobila koji se samostalno voze da vode vozilo do odredišta. Duboko učenje i mašinsko učenje se, takođe, koriste u nauci o koroziji i inženjerstvu. Koriste se za odabir molekula inhibitora iz velikog skupa dostupnih molekula.

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