Statistical and Computational Modeling

Statistical and Computational Modeling is a research topic within Artificial Intelligence. Science Explorer counts 7.2k research works in it since 1950. 10.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of inductive modeling techniques, particularly GMDH-type neural networks and interval models, in various scientific research domains. The papers cover topics such as environmental monitoring, modeling and prediction of complex processes, application of machine learning algorithms, and the use of self-organization techniques. The overarching theme revolves around the utilization of advanced computational methods for sustainable development and scientific analysis.

• Inductive Modeling
• GMDH-type Neural Networks
• Interval Models
• Environmental Monitoring
• Artificial Bee Colony Algorithm
• Machine Learning
• Data Mining
• Modeling and Prediction
• Self-Organization Techniques
• Sustainable Development