Abstract
Artificial Neural Network (ANN) and Fuzzy Logic (FL) are two important and useful technologies having their strengths and weaknesses. The combination of fuzzy logic and neural networks constitutes a powerful means for intelligent system development and offers dual advantages of the technologies. This article describes four approaches of neuro-fuzzy systems with their broad design and also presents general structure of a business advisory system using hybrid neuro-fuzzy approach. The system utilizes ANN that considers basic parameters and data from the environment for selection of a small-scale business in the given area and generates rules accordingly. Finally, the article presents sample rules extracted from the neuro-fuzzy system, screens for the interface design and parameters for implementation.
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Akerkar, R., Sajja, P.S. (2010). A Neuro-Fuzzy Decision Support System for Selection of Small Scale Business. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2010. Communications in Computer and Information Science, vol 81. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14058-7_31
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DOI: https://doi.org/10.1007/978-3-642-14058-7_31
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