00000cmm a22000004i 4500 UP-99796217611211783 Buklod 20140423080934.0 m go j cr cn |||aaaaa 140423s2011 xx d u (iLib)UPD-00214607888 DLC DML eng DMLUC QA402 G43 2010eb Fuzzy networks for complex systems [electronic resource] a modular rule base approach by Alexander Gegov. Berline Springer c2011. 1 online resource (xiv, 290 p.) ill. (some col.) Studies in fuzziness and soft computing 259 1. Introduction -- 2. Types of Fuzzy Systems -- 3. Formal Models for Fuzzy Networks -- 4. Basic Operations in Fuzzy Networks -- 5. Structural Properties of Basic Operations -- 6. Advanced Operations in Fuzzy Networks -- 7. Feedforward Fuzzy Networks -- 8. Feedback Fuzzy Networks -- 9.Evaluation of Fuzzy Networks -- 10. Conclusion. IP-based subscription, access limited to within on campus computer network. Access via Electronic Resources of the UPD University Library Website. This book introduces the novel concept of a fuzzy network whose nodes are rule bases and the connections between the nodes are the interactions between the rule bases in the form of outputs fed as inputs. The concept is presented as a systematic study for improving the feasibility and transparency of fuzzy models by means of modular rule bases whereby the model accuracy and efficiency can be optimised in a flexible way. The study uses an effective approach for fuzzy rule based modelling of complex systems that are characterised by attributes such as nonlinearity, uncertainty, dimensionality and structure.The approach is illustrated by formal models for fuzzy networks, basic and advanced operations on network nodes, properties of operations, feedforward and feedback fuzzy networks as well as evaluation of fuzzy networks. The results are demonstrated by numerous examples, two case studies and software programmes within the Matlab environment that implement some of the theoretical methods from the book. The book shows the novel concept of a fuzzy network with networked rule bases as a bridge between the existing concepts of a standard fuzzy system with a single rule base and a hierarchical fuzzy system with multiple rule bases. Electronic reproduction. New York SpringerLink 2011. Available via World Wide Web through SpringerLink. Electronic books. Fuzzy systems. Mathematical analysis. Neural networks (Computer science) SpringerLink (Online service). Available for University of the Philippines Diliman via SpringerLink. Click here to access http://link.springer.com/book/10.1007/978-3-642-15600-7 FO Monograph UPD DMLR Electronic Resource