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Traffic Control and Transport Planning: - A Fuzzy Sets and Neural Networks Approach (Paperback, Softcover reprint of the original 1st ed. 1998)
Loot Price: R5,461
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Traffic Control and Transport Planning: - A Fuzzy Sets and Neural Networks Approach (Paperback, Softcover reprint of the original 1st ed. 1998)
Series: International Series in Intelligent Technologies, 13
Expected to ship within 10 - 15 working days
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When solving real-life engineering problems, linguistic information
is often encountered that is frequently hard to quantify using
"classical" mathematical techniques. This linguistic information
represents subjective knowledge. Through the assumptions made by
the analyst when forming the mathematical model, the linguistic
information is often ignored. On the other hand, a wide range of
traffic and transportation engineering parameters are characterized
by uncertainty, subjectivity, imprecision, and ambiguity. Human
operators, dispatchers, drivers, and passengers use this subjective
knowledge or linguistic information on a daily basis when making
decisions. Decisions about route choice, mode of transportation,
most suitable departure time, or dispatching trucks are made by
drivers, passengers, or dispatchers. In each case the decision
maker is a human. The environment in which a human expert (human
controller) makes decisions is most often complex, making it
difficult to formulate a suitable mathematical model. Thus, the
development of fuzzy logic systems seems justified in such
situations. In certain situations we accept linguistic information
much more easily than numerical information. In the same vein, we
are perfectly capable of accepting approximate numerical values and
making decisions based on them. In a great number of cases we use
approximate numerical values exclusively. It should be emphasized
that the subjective estimates of different traffic parameters
differs from dispatcher to dispatcher, driver to driver, and
passenger to passenger.
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