Estimation and Approximation Using Neuro-Fuzzy Systems

Estimat ion and Approximation plays an important role in p lanning for future. People especially the business leaders, who understand the significance of estimation, practice it very often. The act of estimation or approximation involves analyzing historical data pertaining to domain, current trends and expectations of people connected to it. Exercising estimation is not only complicated due to technological change in the world around, but also due to complexity o f the problems. Traditional nu merical based techniques for solution of ill- defined non-linear real world problems are not sufficient. Hence, there is a need of some robust methodologies which can deal with dynamic environment, imprecise facts and uncertainty in the available data to achieve practical applicability at low cost. Soft computing seeks to solve class of problems not suited for traditional algorithmic approaches. To address the common problems in business of inexactness, some models are put forward for servicing, support and monitoring by approximating and estimat ing important outcomes. This work illustrates some very general yet widespread problems which are of interest to common people. The suggested approaches can overcome the fuzziness in tradit ional methods by predicting some future events and getting better control on business. This includes study of various neuro-fu zzy arch itectures and their possible applicat ions in various areas, where decision-making using classical methods fail.