Nur Nahar Rimi
Biographic Data
| ID | 6957228 |
|---|---|
| NAME | Nur Nahar Rimi |
| GIVEN NAMES | Nur Nahar |
| FAMILY NAME | Rimi |
| SIGNATURE | RIMI N N |
| AFFILIATIONS | Trine University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Predicting the Adoption of Clean Energy Vehicles
Switching towards clean energy vehicles (CEVs) is a key measure in curbing greenhouse gas emissions and fighting climate change in the USA. Yet, despite mounting environmental consciousness and policy stimulus, the uptake of CEVs is still quite low. The main aim of this research is the creation of a market analysis framework based on machine learning for the prediction of CEV adoption. Utilizing supervised learning algorithms—Random Forest, Logis…
Advanced Detection and Forecasting of Fake News on Social Media Platforms Using Natural Language Processing and Artificial Intelligence
In the stage of pervasive digital communication, the rapid dissemination of fake news via social media platforms poses significant challenges to public discourse, societal trust, and institutional integrity. Fake news, characterized by fabricated or misleading content, spreads rapidly across platforms like Facebook, Twitter, WhatsApp, influencing political outcomes and public perceptions. Traditional methods of manual fact-checking cannot keep pa…
No prominent works on this page.
Predicting the Adoption of Clean Energy Vehicles
Switching towards clean energy vehicles (CEVs) is a key measure in curbing greenhouse gas emissions and fighting climate change in the USA. Yet, despite mounting environmental consciousness and policy stimulus, the uptake of CEVs is still quite low. The main aim of this research is the creation of a market analysis framework based on machine learning for the prediction of CEV adoption. Utilizing supervised learning algorithms—Random Forest, Logis…
Advanced Detection and Forecasting of Fake News on Social Media Platforms Using Natural Language Processing and Artificial Intelligence
In the stage of pervasive digital communication, the rapid dissemination of fake news via social media platforms poses significant challenges to public discourse, societal trust, and institutional integrity. Fake news, characterized by fabricated or misleading content, spreads rapidly across platforms like Facebook, Twitter, WhatsApp, influencing political outcomes and public perceptions. Traditional methods of manual fact-checking cannot keep pa…
Computer Science (2 works) · Artificial Intelligence (1 work) · Automotive Engineering (1 work) · Business (1 work) · Clean energy (1 work) · Data science (1 work) · Economics (1 work) · Electric Vehicles and Infrastructure (1 work) · Energy Efficiency and Management (1 work) · Energy, Environment, and Transportation Policies (1 work)