Forging New Frontiers: Fuzzy Pioneers II

Első borító
Masoud Nikravesh, Lofti A. Zadeh
Springer, 2007. okt. 30. - 433 oldal

The 2005 BISC International Special Event-BISCSE’05 “Forging the frontiers” was held in the University of California, Berkeley, “Where fuzzy logic began”, from November 3-6, 2005. The successful applications of fuzzy logic and it’s rapid growth suggest that the impact of fuzzy logic will be felt increasingly in coming years. Fuzzy logic is likely to play an especially important role in science and engineering, but eventually its influence may extend much farther. In many ways, fuzzy logic represents a significant paradigm shift in the aims of computing - a shift which reflects the fact that the human mind, unlike present day computers, possesses a remarkable ability to store and process information which is pervasively imprecise, uncertain and lacking in categoricity.

The chapters of the book are evolved from presentations made by selected participants at the meeting and organized in two books. The papers include reports from the different front of soft computing in various industries and address the problems of different fields of research in fuzzy logic, fuzzy set and soft computing. The book provides a collection of forty four (44) articles in two volumes.

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Quantum and Fields
DecisionBased Query and Questionnaire Systems
Qualitative Possibility Theory in Information Processing
Fuzzy Modeling of Nonlinear Stochastic Systems by Learning from Examples
FISCRM FISS Metasearcher and GUMSe Architecture
A New Approach for Contradictory Knowledge Management
Fuzzy Cognitive Maps Structure for Medical Decision Support Systems
FuzzyNeuro Systems for Local and Personalized Modelling
Interpolative Realization of Boolean Algebra as a Consistent Frame for Gradation andor Fuzziness
Systematic Design of a Stable Type2 Fuzzy Logic Controller
Soft Computing for Intelligent Reservoir Characterization and Decision Analysis
FuzzyBased Nosocomial Infection Control
Fuzzy Association Rules for Query Refinement in Web Retrieval
Fuzzy Logic in a Postmodern Era
Implementation of Fuzzy Set Theory in the Field of Energy Processes Applied in Nuclear Power Technology
Methods of Possibilistic Optimization with Applications

Dynamic Simulation of a Supply Chain with and without Flexibility in the Lead Time Agreements
Robust Statistics and Fuzzy Industrial Clustering
Fuzzy Label Semantics for Data Mining
Aggregating Subjective and Objective Measures of Web Search Quality using Modified Shimura Technique
Using NTH Dimensional Fuzzy Logic for Complexity Analysis Decision Analysis and Autonomous Control Systems
An Effective Machine Learning Approach

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375. oldal - It is the cause, it is the cause, my soul — Let me not name it to you, you chaste stars ! — It is the cause.
viii. oldal - The Semantic Web is an extension of the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.
39. oldal - Table 3, a simulatedhypothetical model (a Virtual Model) was developed. A series of excellent, very good, good, not good, not bad, bad, and very bad student given the criteria for admission has been recognized. These criteria over time can be modified based on the success rate of students admitted to the university and their performances during the first, second, third and fourth years of their education with different weights and degrees of importance given for each year. Then, fuzzy similarity...
196. oldal - A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation.
38. oldal - Application to Credit Scoring Credit scoring was first developed in the 1950's and has been used extensively in the last two decades. In the early 1980's, the three major credit bureaus, Equitax, Experian, and TransUnion worked with the Fair Isaac Company to develop generic scoring models that allow each bureau to offer an individual score based on the contents of the credit bureau's data. FICO is used to make billions of financing decisions each year serving a 100 billion dollar industry. Credit...
177. oldal - Wl(r) and W2(r), the latter being adjusted through supervised learning based on the output error, and the former being adjusted through unsupervised learning based on similarity measure within a local area of the problem space. The fourth layer of neurons represents fuzzy quantization for the output variables, similar to the input fuzzy neurons representation.
389. oldal - Dubois, D. and Prade, H., Possibility Theory : An Approach to Computerized Processing of Uncertainty, Plenum Press: New York, 1988.
183. oldal - DENFIS evolve through incremental, hybrid (supervised/unsupervised), learning, and accommodate new input data, including new features, new classes, etc., through local element tuning. New fuzzy rules are created and updated during the operation of the system. At each time moment, the output of DENFIS is calculated through a fuzzy inference system based on m-most activated fuzzy rules which are dynamically chosen from a fuzzy rule set. Two approaches are proposed...
177. oldal - The nodes representing membership functions (MFs) can be modified during learning. Each input variable is represented here by a group of spatially arranged neurons to represent a fuzzy quantization of this variable. For example, three neurons can be used to represent "small", "medium" and "large" fuzzy values of the variable.
178. oldal - Wl(rj) connection weights representing the co-ordinates of the center of the sphere in the fuzzy input space, and the W2 (r,) - the co-ordinates in the fuzzy output space. The radius of an input hyper-sphere of a rule node is defined as (1- Sthr), where Sthr is the sensitivity threshold parameter defining the minimum activation of a rule node (eg...

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