## The fuzzy systems handbook: a practitioner's guide to building, using, and maintaining fuzzy systemsThis new edition provides a comprehensive introduction to fuzzy logic, and leads the reader through the complete process of designing, constructing, implementing, verifying and maintaining a platform-independent fuzzy system model. The book has been extensively revised to bring the subject up-to-date, and features two new chapters: "Building and Using Fuzzy Cognitive Map Models" and "Building ME-OWA Models."The multiplatform CD-ROM contains all the C++ source code from the book’s examples – but its real value is the robust package of fuzzy system related tools and utilities, featuring two notable components. First: Metus Systems’ basic fuzzy modeling software, which includes complete C/C++ source code for creating and executing fuzzy models, a Visual Basic shell that can be used to create fuzzy sets and generate the C/C++ include files, and code for models for pricing, project management, risk assessment, and more. Second: The ME-OWA (Minimum-Entropy, Ordered Weighted Aggregation) decision modeling software from Fuzzy Logic, Inc. This software is used to focus on a single objective function from a set of alternatives given a fuzzy ranking among various alternatives. It is not only an important technique as a stand-alone tool, but is an important methodology in parameter selection (and parameterization ordering) for genetic algorithms and various data mining techniques. It is also an important technique used to establish rule and policy level peer weights in fuzzy models. |

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The Fuzzy Systems Handbook: A Practitioner's Guide to Building ..., Volume 2 No preview available - 1994 |

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2*MfgCosts alpha-cut threshold ambiguity approximate array associated backorderAmt Boolean centroid compatibility index compensatory complement complex composite maximum composite moments concept control block correlation created defined defuzzification Degree of Membership descriptor block dictionary domain value dynamic link libraries evaluated example expected value expert systems FDBptr Figure fuzzy logic fuzzy model Fuzzy Number 30 fuzzy proposition fuzzy region fuzzy rules fuzzy space fuzzy systems FuzzySet hedge height High implication imprecision increased int statusptr intersection knowledge engineer Linear Fuzzy Set linguistic variable Listing Membership u(x method MiddleAged Model Solution operator overlap parameter PI curve plateau pointer predicate Price Solution Fuzzy pricing model represent representation risk assessment S-curve scalar semantics solution fuzzy set solution variable specified surface Tall technique temperature tion truth function truth membership function truth membership value truth table truth value unconditional underlying variable's Visual Basic XSYSctl Zadeh zero