Concluding Remarks and Further Research

Abstract

Real-world problems are typically ill-defined systems, difficult to model and with large-scale solution spaces. In these cases, precise models are impractical, too expensive, or non-existent. The relevant available information is usually in the form of empirical prior knowledge and input-output data representing instances of the system’s behavior [290]. Soft Computing (SC), including Neural Computing (NC), Fuzzy Computing (FC), Evolutionary Computing (EC) etc., provides us with a set of flexible intelligent computational tools to perform approximate reasoning, learning from data, search tasks etc.