Mehedi Hasan Ridoy
Biographic Data
| ID | 6953336 |
|---|---|
| NAME | Mehedi Hasan Ridoy |
| GIVEN NAMES | Mehedi Hasan |
| FAMILY NAME | Ridoy |
| SIGNATURE | RIDOY M H |
| AFFILIATIONS | Gannon University |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| 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 Machine Learning Approaches for Credit Card Fraud Detection in the USA
Credit card fraud is a financial threat in America, both for financial institutions and for consumers, and it is growing in severity. Traditional fraud detection methods become less effective in countering emerging fraud trends, and for that reason, sophisticated algorithms in machine learning have to be embraced. This research project strived to develop and compare complex algorithms for fraud detection in credit cards in America. With a variety…
Secure Energy Transactions Using Blockchain – Leveraging AI for Fraud Detection and Energy Market Stability
Peer-to-peer trading and the move to decentralized grids have reshaped the energy markets in the United States. Notwithstanding, such developments lead to new challenges, mainly regarding the safety and authenticity of energy trade. This study aimed to develop and build a secure, intelligent, and efficient energy transaction system for the decentralized US energy market. This research interlinks the technological prowess of blockchain and artific…
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 Machine Learning Approaches for Credit Card Fraud Detection in the USA
Credit card fraud is a financial threat in America, both for financial institutions and for consumers, and it is growing in severity. Traditional fraud detection methods become less effective in countering emerging fraud trends, and for that reason, sophisticated algorithms in machine learning have to be embraced. This research project strived to develop and compare complex algorithms for fraud detection in credit cards in America. With a variety…
Secure Energy Transactions Using Blockchain – Leveraging AI for Fraud Detection and Energy Market Stability
Peer-to-peer trading and the move to decentralized grids have reshaped the energy markets in the United States. Notwithstanding, such developments lead to new challenges, mainly regarding the safety and authenticity of energy trade. This study aimed to develop and build a secure, intelligent, and efficient energy transaction system for the decentralized US energy market. This research interlinks the technological prowess of blockchain and artific…
Business (3 works) · Computer Science (3 works) · Computer security (2 works) · Engineering (2 works) · Machine learning (2 works) · Artificial Intelligence (1 work) · Automotive Engineering (1 work) · Blockchain (1 work) · Blockchain Technology Applications and Security (1 work) · Clean energy (1 work)