Fusion of soft computing and hard computing: computational structures and characteristic features

Soft computing (SC) and hard computing (HC) methodologies are fused together successfully in numerous industrial applications. The principal aim is to develop computationally intelligent hybrid systems that are straightforward to analyze, with highly predictable behavior and stability, and with computational burden that is no more than moderate. All these goals are particularly important in embedded real-time applications. This paper is intended to clarify the present vagueness related to the fusion of SC and HC methodologies. We classify the different fusion schemes to 12 core categories and six supplementary categories, and discuss the characteristic features of SC and HC constituents in practical fusion implementations. The emerging fusion approach offers a natural evolution path from pure hard computing toward dominating soft computing