Bilgilendirme: Sürüm Güncellemesi ve versiyon yükseltmesi nedeniyle, geçici süreyle zaman zaman kesintiler yaşanabilir ve veri içeriğinde değişkenlikler gözlemlenebilir. Göstereceğiniz anlayış için teşekkür ederiz.
 

Advancing Nanomaterials Research: a Comprehensive Review of Artificial Intelligence Applications in Geotechnical Properties

No Thumbnail Available

Date

2024

Journal Title

Journal ISSN

Volume Title

Publisher

Techno-Press

Open Access Color

OpenAIRE Downloads

OpenAIRE Views

Research Projects

Journal Issue

Abstract

This article explores the role of artificial intelligence (AI) in predicting nanomaterial properties, particularly its significance within geotechnical engineering. By analyzing multiple AI-based studies, the review concentrates on the forecasting of nanomaterial-altered soil characteristics and behaviors. Encouraging findings from these studies underscore AI’s ability to accurately predict the geotechnical properties of nanomaterials, though challenges remain, particularly in quantifying nanomaterial percentages and their implications across various applications. Future research should address these challenges to enhance the accuracy of AI-based prediction models in geotechnical engineering. Nonetheless, the growing adoption of AI for predicting nanomaterial properties demonstrates its potential to revolutionize geotechnical engineering. AI’s capacity to uncover intricate patterns and relationships beyond human capabilities enables more precise soil behavior predictions, fostering innovative solutions to geotechnical challenges. Its ability to process vast datasets, adapt to various scenarios, and continuously learn from new information makes AI an indispensable tool for understanding nanomaterial properties and their impact on soil behavior. In summary, the integration of AI and geotechnical engineering represents a pivotal advancement in comprehending nanomaterial properties and their practical applications. As research advances and AI technologies evolve, transformative progress in geotechnical engineering is expected. By harnessing AI’s capabilities, researchers can unlock groundbreaking insights, drive innovation, and shape a more resilient and sustainable future for the geotechnical engineering industry. © 2024 Techno-Press, Ltd.

Description

Keywords

Artificial Intelligence, Geotechnical Engineering, Intelligent Models, Nanomaterials, Prediction

Turkish CoHE Thesis Center URL

Fields of Science

Citation

WoS Q

Q2

Scopus Q

Q2
OpenCitations Logo
OpenCitations Citation Count
N/A

Source

Advances in Nano Research

Volume

17

Issue

6

Start Page

485

End Page

499
PlumX Metrics
Citations

Scopus : 1

Captures

Mendeley Readers : 4

Google Scholar Logo
Google Scholar™

Sustainable Development Goals

3

GOOD HEALTH AND WELL-BEING
GOOD HEALTH AND WELL-BEING Logo

4

QUALITY EDUCATION
QUALITY EDUCATION Logo

7

AFFORDABLE AND CLEAN ENERGY
AFFORDABLE AND CLEAN ENERGY Logo

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
INDUSTRY, INNOVATION AND INFRASTRUCTURE Logo

11

SUSTAINABLE CITIES AND COMMUNITIES
SUSTAINABLE CITIES AND COMMUNITIES Logo

13

CLIMATE ACTION
CLIMATE ACTION Logo

17

PARTNERSHIPS FOR THE GOALS
PARTNERSHIPS FOR THE GOALS Logo