Bikash K Behera
Biographic Data
| ID | 10054258 |
|---|---|
| NAME | Bikash K Behera |
| GIVEN NAMES | Bikash K |
| FAMILY NAME | Behera |
| SIGNATURE | BEHERA B K |
| AFFILIATIONS | Welspun (India) |
| ORCID | 0000-0003-2629-3377 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
SentiQNF
Sentiment analysis (SA) is an essential component of natural language processing (NLP) and is used to analyze sentiments, attitudes, and emotional tones in various contexts. It provides valuable insights into public opinion, customer feedback, and user experiences. Researchers have developed various classical machine learning (ML) and neuro-fuzzy approaches to address the exponential growth of data and the complexity of language structures in SA.…
QFDNN
Social financial technology focuses on trust, sustainability, and social responsibility, which require advanced technologies to address complex financial tasks in the digital era. With the rapid growth in online transactions, automating credit card fraud detection and loan eligibility prediction has become increasingly challenging. Classical machine learning (ML) models have been used to solve these challenges; however, these approaches often enc…
No prominent works on this page.
QFDNN
Social financial technology focuses on trust, sustainability, and social responsibility, which require advanced technologies to address complex financial tasks in the digital era. With the rapid growth in online transactions, automating credit card fraud detection and loan eligibility prediction has become increasingly challenging. Classical machine learning (ML) models have been used to solve these challenges; however, these approaches often enc…
SentiQNF
Sentiment analysis (SA) is an essential component of natural language processing (NLP) and is used to analyze sentiments, attitudes, and emotional tones in various contexts. It provides valuable insights into public opinion, customer feedback, and user experiences. Researchers have developed various classical machine learning (ML) and neuro-fuzzy approaches to address the exponential growth of data and the complexity of language structures in SA.…
Artificial Intelligence (2 works) · Computer Science (2 works) · Physics (2 works) · Quantum (2 works) · Algorithm (1 work) · Artificial neural network (1 work) · Fuzzy control system (1 work) · Fuzzy logic (1 work) · Imbalanced Data Classification Techniques (1 work) · Machine learning (1 work)