Vol 53, No 5 (2019)

This paper discusses two languages for representation of chemical structures and carries out their comparative analysis for the prediction of biological activity using an intelligent JSM-system. The comparison is carried out on three data arrays in terms of the group of parameters.

In this paper, we describe a new probabilistic algorithm for calculating hypotheses as the results of similarities between training examples for a machine learning problem based on a binary similarity operation. Unlike previously proposed probabilistic algorithms, the order of accounting for training examples is fixed for all hypotheses. This algorithm is useful for implementation using a GPGPU. The main result of this paper is the independence of the order of the appearance of training examples of the probabilities of each similarity in the sample.

The logical means of detecting empirical regularities using the JSM method of automated research support are considered. Generators of hypotheses about the causes and hypotheses about predictions that are stored in sequences of expandable fact bases are determined. Many “histories of possible worlds” are considered, where “world” refers to an expandable fact base. This set is used to determine empirical regularities, that is, empirical laws, tendencies, and weak tendencies. Empirical regularities are used to determine empirical modalities of necessity (for empirical laws), possibilities (for empirical tendencies), and weak possibilities (for weak empirical tendencies). The Propositional calculi of the class ERA are proposed, that is, modal logics with two empirical modalities of necessity and possibility such that they imitate abductive inference through the axioms of abduction (◻(p → q) & Tq) → ◻p), (◇(p → q) & Tq) → ◇p), where ◻, ◇, T are operators of necessity, possibility, and truth (“it is true that…”). A series of definitions related to the characterization of data mining using heuristics of the JSM method of automated research support is given.

This paper describes an intelligent system that performs the JSM automated research support method, which is designed to diagnose pancreatic diseases, that is, chronic pancreatitis and pancreatic cancer. A preliminary study is presented; further trends for the development of the system are listed.