Implementing an expert system to evaluate technical solutions innovativeness
V. K. Ivanov, I. V. Obraztsov, B. V. Palyukh

TL;DR
This paper introduces an expert system and algorithm for quantifying innovativeness of technical solutions, handling incomplete and fuzzy data, with a focus on technological novelty, relevance, and implementability.
Contribution
It proposes a novel multi-agent expert system and algorithm for evaluating innovation indicators using interval estimations and evidence theory.
Findings
Developed specialized software for innovation analysis.
Demonstrated the system's application on a real technical product.
Validated the approach's effectiveness in handling incomplete data.
Abstract
The paper presents a possible solution to the problem of algorithmization for quantifying inno-vativeness indicators of technical products, inventions and technologies. The concepts of technological nov-elty, relevance and implementability as components of product innovation criterion are introduced. Authors propose a model and algorithm to calculate every of these indicators of innovativeness under conditions of incompleteness and inaccuracy, and sometimes inconsistency of the initial information. The paper describes the developed specialized software that is a promising methodological tool for using interval estimations in accordance with the theory of evidence. These estimations are used in the analysis of complex multicomponent systems, aggregations of large volumes of fuzzy and incomplete data of various structures. Composition and structure of a multi-agent expert system are…
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