This paper is devoted to the synthesis and analysis of crisp and fuzzy relational cognitive maps in the intelligent modeling of imprecise systems. The synthesis process is presented in the form of an algorithm of actions. For solving crisp problems, gradient parametric optimization algorithms were developed, while for fuzzy ones, certain random methods were used. Selected results of implementing the developed methods for specific systems are provided.Computer-based decision-making systems in imprecise systems usually operate in two stages [5]. Their operation consists of:
– developing an appropriate model of the analyzed object within its environment, – applying an adequate decision-making method.
Due to the fact that the characteristics of the analyzed systems and their environment are often not fully known (lack of complete information or difficulty in developing deterministic models, inability to obtain full measurement data, etc.), taking the aforementioned actions is significantly hindered. (…)
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Source: Logistyka Magazine
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