Titlebook: Artificial Intelligence in Models, Methods and Applications; Olga Dolinina,Igor Bessmertny,Vadim Zhmud Conference proceedings 2023 The Edi

LAP

Artificial Intelligence in Models, Methods and Applications978-3-031-22938-1Series ISSN 2198-4182 Series E-ISSN 2198-4190

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Semantic Modeling of Predicate Calculus Based on ,-Tuple Algebraelson that in mathematical logic “semantic concepts are of a set-theoretic nature”. This idea was not implemented for the reason that paradoxes were discovered in set theory. Therefore, it is proposed to use set algebra instead of set theory. The report formulates its differences from theory of sets

Crumple

Method of Iterative-Order Optimization of Multicriteria Problems Using the Local Importance of Criteterative-order optimization algorithm developed by the authors. Decision-making theory is one of the artificial intelligence problems. The theory of the global qualitative importance of criteria is currently well developed, there are many works on this topic. Moreover, numerous computer decision sup

Keratin

Neural Network Representation for Ordinary Differential Equationstensive development of sensing techniques and IoT devices resulted in the accumulation of a large amount of data that brought to the front edge the pure data-driven methods to describe and predict real-world processes. However, pure data-driven methods are unreliable in applications with higher requ

GLUT

Modeling Situations in Spatial Analysistifying a spatial entity and predicting its behavior, the human researcher mentally reproduces the situations known to him in the analyzed spatial area. This operation is called transformation in this work. For intelligent systems, transformation is universal since it involves the transfer of existi

Morose

Fulsome

荒唐

Assessment of the Vine–Copula for the Gamma Poisson Model of Risky Person’s Behavior with Synthetic aracteristic may be used for risk analysis. But sometimes self–reports are the only feasible way to acquire the data on episodes of the behavior, and this approach often leads to imprecise and incomplete data that needs to be handled with an appropriate mathematical model. The paper focuses on the B

dyspareunia

證實

Divergence of Comparative Possibility Distributions as a Numerical Measure of How Difficult it is tog and aggregating qualitative information from different sources (experts, archival records, participant observations, etc.) about the given alternatives, we define a new numerical divergence on the set of comparative possibility distributions. It measures how difficult it is to reach a consensus in