International Conference on Simulation and Modeling in Engineering with Blockchain (ICSMEB - 27)

This track focuses on the latest methodologies in simulation techniques specifically tailored for blockchain applications in engineering. Participants will explore how these advancements can enhance the reliability and efficiency of blockchain systems.

This session will delve into the role of predictive modeling in engineering, emphasizing the integration of blockchain technology. Discussions will center on case studies that showcase improved decision-making and operational efficiencies.

This track will investigate supervised and unsupervised learning techniques applied to blockchain-enabled engineering systems. Participants will analyze the impact of these machine learning approaches on system performance and anomaly detection.

This session will highlight the application of deep learning techniques in engineering simulations, particularly within blockchain frameworks. Attendees will examine how these innovations can lead to more accurate modeling and predictive capabilities.

This track will focus on methods for anomaly detection in engineering processes that utilize blockchain technology. Participants will discuss the implications of these methods for enhancing system monitoring and risk assessment.

This session will explore advanced feature extraction techniques relevant to blockchain applications in engineering. The discussions will emphasize how effective feature extraction can improve model evaluation and performance.