Computational And Experimental Process Control By Combining
Neurofuzzy Approximation With Multicriteria Optimization
Author(s)
A. F. Batzias & F.A. Batzias
Abstract
Computational and experimental process
control by combining neurofuzzy
approximation with multicriteria optimization
A.F. Batzias and F.A. Batzias
Department of Industrial Management and Technology,
University of Piraeus, Greece.
Abstract
In this work we have designed / developed I implemented an algorithmic
procedure for computational and experimental process control aiming to find out
the optimal combination of industrial production conditions that satisfy
specifications of a product set by a client or the market. For this purpose, a
Transformation Mechanism (TM) is established which produces a mapping of
processing conditions on product qualities by neurofuzzy approximation; TM is
coupled with the inverse procedure (ITM) which connects a product quality
vector with all possible combinations of production condition vectors. The
clustering I filtering of these combinations gives the alternatives among which a
fuzzy multicriteria method selects the best. Implementation with data provided by
t
Keywords
Related Book
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