Scope of Submission
We welcome submissions from a broad range of disciplines, including but not limited to:
- Data mining techniques in engineering applications
- Predictive analytics for engineering processes
- Big data challenges in engineering sciences
- Machine learning for engineering problem solving
- Data visualization methods in engineering
- Statistical methods for engineering data analysis
- Data mining for quality control in engineering
- Optimization algorithms in engineering design
- Real-time data processing in engineering
- Data mining for predictive maintenance
- Text mining applications in engineering research
- Data-driven decision making in engineering
- Data mining for energy efficiency in engineering
- Integration of IoT and data mining
- Data mining for risk assessment in engineering
- Ethical considerations in engineering data mining
- Case studies of data mining in engineering
- Collaborative data mining in engineering projects
- Data mining for sustainability in engineering
- Future trends in engineering data mining
All papers must be original and not previously published or submitted elsewhere.
