Non-linearity, complexity and dynamics have become a focal point of research in spatial analysis, especially in the analysis of spatial data. Regardless of what we are dealing with, the need to handle systems with a high degree of complexity is now the rule rather than the exception. With our spatial systems becoming more and more complex and highly fluid, non-linearity prevails and evolution is full of surprises. It is essential to develop approaches which can effectively analyse complexity, non-linearity and dynamics in spatial systems in general, and in particular spatial classification and knowledge acquisition.
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- Neural and Evolutionary Computation Methods for Spatial Classification and Knowledge Acquisition
- Springer Berlin Heidelberg
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