000 03230nam a22004815i 4500
001 978-3-642-15600-7
003 DE-He213
005 20140220083747.0
007 cr nn 008mamaa
008 100930s2011 gw | s |||| 0|eng d
020 _a9783642156007
_9978-3-642-15600-7
024 7 _a10.1007/978-3-642-15600-7
_2doi
050 4 _aTA329-348
050 4 _aTA640-643
072 7 _aTBJ
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aGegov, Alexander.
_eauthor.
245 1 0 _aFuzzy Networks for Complex Systems
_h[electronic resource] :
_bA Modular Rule Base Approach /
_cby Alexander Gegov.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2011.
300 _aXIV, 290 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v259
505 0 _aIntroduction -- Types of Fuzzy Systems -- Formal Models for Fuzzy Networks -- Basic Operations in Fuzzy Networks -- Structural Properties of Basic Operations -- Advanced Operations in Fuzzy Networks -- Feedforward Fuzzy Networks -- Feedback Fuzzy Networks -- Evaluation of Fuzzy Networks -- Conclusion.
520 _aThis 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.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aStatistical Physics, Dynamical Systems and Complexity.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642155994
830 0 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v259
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-15600-7
912 _aZDB-2-ENG
999 _c107068
_d107068