USING FUZZY PROBABILITY AND SIMULATION METHODS IN WEB PLANNING MODELS
A Subset of Artificial Intelligence
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This book addresses web systems analysis and planning models from a fuzzy mathematics point of view. The models are primarily queuing systems models directed toward web server analyses. The research divides into two parts based on approaches taken in initial problem definition: transition probability matrices and arrival-service rate stochastic models. Each begins from conventional mathematical formulations into which fuzziness is introduced at some point, affecting further operations on the way to and including solutions. Each approach admits two principal solution methods: optimization and s...
This book addresses web systems analysis and
planning models from a fuzzy mathematics point of
view. The models are primarily queuing systems
models directed toward web server analyses. The
research divides into two parts based on approaches
taken in initial problem definition: transition
probability matrices and arrival-service rate
stochastic models. Each begins from conventional
mathematical formulations into which fuzziness is
introduced at some point, affecting further
operations on the way to and including solutions.
Each approach admits two principal solution methods:
optimization and simulation.The models addressed
single- and multiple-server web systems. In direct
optimization case, it combined fuzzy logic and
Genetic Algorithm, making the approach unique and
promising. In simulation cases, simulation was
directed toward mean values of the rates, it produced
frequency distributions about the means used
heuristically to obtain "two-step" approximations.
planning models from a fuzzy mathematics point of
view. The models are primarily queuing systems
models directed toward web server analyses. The
research divides into two parts based on approaches
taken in initial problem definition: transition
probability matrices and arrival-service rate
stochastic models. Each begins from conventional
mathematical formulations into which fuzziness is
introduced at some point, affecting further
operations on the way to and including solutions.
Each approach admits two principal solution methods:
optimization and simulation.The models addressed
single- and multiple-server web systems. In direct
optimization case, it combined fuzzy logic and
Genetic Algorithm, making the approach unique and
promising. In simulation cases, simulation was
directed toward mean values of the rates, it produced
frequency distributions about the means used
heuristically to obtain "two-step" approximations.
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