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Hybrid expert–fuzzy approach for evaluation of complex systems
Author(s) -
Öztürk Veysi
Publication year - 2009
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.2009.00487.x
Subject(s) - computer science , fuzzy logic , process (computing) , expert system , heuristic , reusability , evaluation methods , data mining , artificial intelligence , machine learning , reliability engineering , software , engineering , programming language , operating system
Evaluation of complex systems is generally complicated and time consuming. Evaluation is needed for nearly all engineering tasks and the obstacles related to evaluation increase in proportion to complexity. New techniques can be used to automate manual evaluation and to overcome the obstacles related to evaluation that cannot be solved (or can only be solved with great difficulty) with conventional computing. In this study, a methodology was developed to handle the heuristic knowledge of experts for evaluation purposes. In this method, knowledge was represented as a reference model of evaluation objectives, production rules, measures, methods and parameters. A ‘common evaluation process’ and ‘common evaluation model’, which simplify and speed up the evaluation process and decrease evaluation cost, were proposed and developed. A hybrid expert–fuzzy system, called ‘intelligent evaluation system’ (INES), which can be used for evaluation of complex systems was developed. To define a process and develop a system that simplifies and speeds up evaluation can save time, decrease cost and provide reusability. As the evaluation of complex systems includes uncertainty in some aspects, fuzzy logic was incorporated with an expert system for reasoning. INES was implemented successfully for the evaluation of an air defence system, which is a complex system used to protect a region from all air threats.