Szczegóły publikacji
Opis bibliograficzny
Aspects-based representative significance of machine Learning algorithms & natural language processing applications in nanotechnology / Pascal Muam MAH // EAI Endorsed Transactions on Intelligent Systems and Machine Learning [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2410-0218. — 2024 — vol. 1, s. 1-9. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 8-9, Abstr. — Publikacja dostępna online od: 2024-10-25
Autor
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 156699 |
|---|---|
| Data dodania do BaDAP | 2024-11-18 |
| Tekst źródłowy | URL |
| DOI | 10.4108/eetismla.4094 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | EAI Endorsed Transactions on Intelligent Systems and Machine Learning |
Abstract
Introduction: The rapid changes in computational power of machine learning algorithms and natural language processing applications have led to multi-scale and many core designs in nanotechnology. Machine learning algorithms and natural language processing applications are easing the burden engineers have to go through to understand nanoparticles. Problem: There is still a challenge to predict and control particles of nanomaterials at nanoscale. Aspect-based climatic conditions are negatively impacting the world with huge modification on nanoparticles, nanomaterials and nanostructures. Objective: Study examines aspects of machine learning algorithms and natural language processing applications that can be used to predict and control particles, and structure of nanomaterials at nanoscale. Method and materials. The study examines significance of machine learning algorithms & applications in nanotechnology, examines aspects of machine learning algorithms & natural language processing applications applied in nanotechnology, and discusses current-future trends of nanotechnology based on learning algorithms & natural language processing applications. Results and conclusions. The findings result in the conclusion that machine learning & natural language processing application in nanotechnology is implementing an advanced microscopic revolution with the potential to metamorphose the world's industrialization and scale human existence. Machine learning algorithms have the potential to predict and classify nanomaterials and natural language processing has the potential to retrieve relevant data hidden within the classified nanomaterials which results has a huge significance in the pharmaceutical industry.
