Several methods are used for analyzing complex data in catalysis:
- Statistical Analysis: Techniques like regression analysis, ANOVA, and PCA to identify trends and correlations. - Machine Learning: Algorithms such as neural networks, decision trees, and support vector machines to build predictive models and identify patterns. - Multivariate Analysis: Methods that handle multiple variables simultaneously, essential for understanding the interplay between different factors in catalytic systems. - Data Mining: Extracting useful information from large datasets through clustering, classification, and association rule learning.
