Springer Artificial Intelligence: Theory and Applications 973

Explore the intersection of advanced computing and environmental science with Artificial Intelligence: Theory and Applications, part of the Studies in Computational Intelligence series. This volume provides an up-to-date collection of research related to the ATLAS project, focusing on how AI helps researchers understand complex phenomena within the environmental sciences. This book addresses the challenges of managing heterogeneous, noisy, and uncertain spatio-temporal data. It is designed for those looking to understand how AI processes diverse and inaccurate data sets to find meaningful patterns. The text moves from foundational mathematics into practical applications, making it a valuable resource for understanding modern computational methods in science. Readers will find detailed coverage of new mathematical frameworks, including aggregation functions, triangular norms, and copulas. The content also explores pseudo-analysis, fuzzy systems, and decision-making processes. By examining generalizations of the Choquet integral, this work provides the mathematical depth needed to handle complex decision-making tasks in real-world environmental research scenarios.