Abstract
The authors set a timely problem that concerns development of decision making models, which allow formalizing expert subjective ideas about technical index level of engineering products. The authors proposed a formalization model of expert knowledge about technical index level of engineering products on the basis of fuzzy sets. The model has a method of membership-function construction for linguistic variable terms on the basis of exponential functions.
Highlights
The first paragraph after a heading is not indented (Bodytext style)
It is proposed to use methods of a fuzzy set theory, which helps model smooth change of an object, and unknown functional relationships presented as qualitative connections
Formalization model of expert knowledge about a technical index level of engineering products When scientists describe a decision making process in its hard formalized stages they take into account the following:
Summary
The first paragraph after a heading is not indented (Bodytext style). Manufacture of innovative products is connected with many science-based engineering solutions, some of which could not be provided with a pure mathematical tool. To support a decision making process it is necessary to form a method and model complex for decision support, which can process expert estimations and knowledge [1]. That is why a timely problem is development of methods and models for decision making, which allow formalizing qualitative and quantitative evaluations, formalizing subjective expert ideas about any engineering product characteristic. 2. Formalization model of expert knowledge about a technical index level of engineering products When scientists describe a decision making process in its hard formalized stages they take into account the following:. A decision making process is characterized by some input parameters and one output parameter; some information given by experts about decision making strategies in standard situations is described by a set of conditional statements in terms of fuzzy and linguistic variables that connect input and output variables [3]. If an expert arranges statements about a value of an output variable depending on values of two input variables, the system of standard fuzzy statements can be as follows (1): L~(1)
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