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Simulating Continuous Fuzzy Systems (Hardcover, 2006 ed.)
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Simulating Continuous Fuzzy Systems (Hardcover, 2006 ed.)
Series: Studies in Fuzziness and Soft Computing, 188
Expected to ship within 12 - 17 working days
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1. 1 Introduction This book is written in two major parts. The ?rst
part includes the int- ductory chapters consisting of Chapters 1
through 6. In part two, Chapters 7-26, we present the applications.
This book continues our research into simulating fuzzy systems. We
started with investigating simulating discrete event fuzzy systems
([7],[13],[14]). These systems can usually be described as queuing
networks. Items (transactions) arrive at various points in the s-
tem and go into a queue waiting for service. The service stations,
preceded by a queue, are connected forming a network of queues and
service, until the transaction ?nally exits the system. Examples
considered included - chine shops, emergency rooms, project
networks, bus routes, etc. Analysis of all of these systems depends
on parameters like arrival rates and service rates. These
parameters are usually estimated from historical data. These
estimators are generally point estimators. The point estimators are
put into the model to compute system descriptors like mean time an
item spends in the system, or the expected number of transactions
leaving the system per unit time. We argued that these point
estimators contain uncertainty not shown in the calculations. Our
estimators of these parameters become fuzzy numbers, constructed by
placing a set of con?dence intervals one on top of another. Using
fuzzy number parameters in the model makes it into a fuzzy system.
The system descriptors we want (time in system, number leaving per
unit time) will be fuzzy numbers.
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