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Semistructured decision-making systems (SDMS) are an important class of intelligent systems (IS) in conditions of different types of indeterminacy and, fuzzy indeterminacy in particular. A dominating issue in projection of indistinct logical system is a selection of intelligent database, or rather a rational number of rules and effective values of their membership function. As a result of it the main problems and tasks of information processing system intellectualisation and their ways of solution are presented in this article.

It is considered important to use the prognostic tasks of the mathematical method using modern information and communication technology. Noticeable changes have been made in the development of the computer diagnostic system, for studying types of diseases in the field of veterinary medicine, the occurrence of the causes of diseases, and improving the quality of targeted treatment methods.A prognostic model using a fuzzy set has been created to study clinical factors and the likelihood of secondary osteodystrophy in cows.

In this paper, computational experiments using the fuzzy integral theory and the Z-number combination have been conducted using fuzzy theory. The article was considered for the selection of the best biological and technologically-based selection breeds of cotton in the case of poor decision-making, and the results of the computational work using these two methods were theoretically justified.

Properties and material selection are an important factor in the design of an object. When choosing a material, it is necessary to take into account not only technical and economic factors but also environmental factors should be taken into account. The article dedicated a method for optimizing the choice of building material using a nonlinear rule derivation to the algorithm and nonlinear regression equations. This article presents the choice of parameters based on a fuzzy () inference system and a nonnegative regression model, and solving a system of linear equations by optimizing this parameter.

In this paper, one of the methods for solving the multi-criteria routing problem in multiservice telecommunication networks is presented. This paper proposes a multi-criteria approach that solves the problem of routing in multiservice communication networks and that takes into account not only the technical requirements for resources but also the economic component. To the restrictions imposed on the route - the throughput and the time delay of data transmission in the channel. This approach allows you to build an optimal route for almost any type of service.

The fuzzy integral of a function with a fuzzy measure is a general estimate in the form of a nonlinear convolution of particular estimates of information elements, and the possibility of interconnection of information elements is not excluded. Here is an approach that al-lows the expert to best formalize his fuzzy ideas, trans-forming the language of words into a language of quantitative estimates.

In this article, fuzzy set membership functions have been developed based on the main factors (clinical, morphochemical, rumen contents) to predict the following non-communicable diseases such as ketosis, osteodystrophy, secondary osteodystrophy and hypomicroelementosis in high-yielding cows. The results of the study show the high efficiency of the proposed decision-making algorithm for forecasting, classifying and measuring poorly formalized processes, that are described by fuzzy models. The available knowledge about the existing experimental data makes it possible to increase the adequacy of the fuzzy expert system.

An analysis of existing methods for solving the problems of risk assessment showed that they are based on the lack of computational capabilities and the lack of necessary information about the conditions of the problem. Therefore, in such cases it is advisable to use fuzzy mathematical methods. In this paper, we consider approaches to solving the problem of risk assessment with fuzzy source information.

The fuzzy integral of a function with a fuzzy measure is a general estimate in the form of a nonlinear convolution of particular estimates of information elements, and the possibility of interconnection of information elements is not excluded. Here is an approach that allows the expert to best formalize his fuzzy ideas, transforming the language of words into a language of quantitative estimates.