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We consider a finite-dimensional optimization problem, the formulation of which in addition to the required variables contains parameters. The solution to this problem is a dependence of optimal values of variables on parameters. In general, these dependencies are not functions because they can have ambiguous meanings and in the functional case be nondifferentiable. In addition, their domain of definition may be narrower than the domains of definition of functions in the condition of the original problem. All these properties make it difficult to solve both the original parametric problem and other tasks, the statement of which includes these dependencies. To overcome these difficulties, usually methods such as non-differentiable optimization are used.

This article proposes an alternative approach that makes it possible to obtain solutions to parametric problems in a form devoid of the specified properties. It is shown that such representations can be explored using standard algorithms, based on the Taylor formula. This form is a function smoothly approximating the solution of the original problem for any parameter values, specified in its statement. In this case, the value of the approximation error is controlled by a special parameter. Construction of proposed approximations is performed using special functions that establish feedback (within optimality conditions for the original problem) between variables and Lagrange multipliers. This method is described for linear problems with subsequent generalization to the nonlinear case.

From a computational point of view the construction of the approximation consists in finding the saddle point of the modified Lagrange function of the original problem. Moreover, this modification is performed in a special way using feedback functions. It is shown that the necessary conditions for the existence of such a saddle point are similar to the conditions of the Karush – Kuhn – Tucker theorem, but do not contain constraints such as inequalities and conditions of complementary slackness. Necessary conditions for the existence of a saddle point determine this approximation implicitly. Therefore, to calculate its differential characteristics, the implicit function theorem is used. The same theorem is used to reduce the approximation error to an acceptable level.

Features of the practical implementation feedback function method, including estimates of the rate of convergence to the exact solution are demonstrated for several specific classes of parametric optimization problems. Specifically, tasks searching for the global extremum of functions of many variables and the problem of multiple extremum (maximin-minimax) are considered. Optimization problems that arise when using multicriteria mathematical models are also considered. For each of these classes, there are demo examples.

The paper presents the results of the fundamental research directed on the theoretical study and computer simulation of peculiarities of the quasi-harmonic signal’s phase statistical distribution. The quasi-harmonic signal is known to be formed as a result of the Gaussian noise impact on the initially harmonic signal. By means of the mathematical analysis the formulas have been obtained in explicit form for the principle characteristics of this distribution, namely: for the cumulative distribution function, the probability density function, the likelihood function. As a result of the conducted computer simulation the dependencies of these functions on the phase distribution parameters have been analyzed. The paper elaborates the methods of estimating the phase distribution parameters which contain the information about the initial, undistorted signal. It has been substantiated that the task of estimating the initial value of the phase of quasi-harmonic signal can be efficiently solved by averaging the results of the sampled measurements. As for solving the task of estimating the second parameter of the phase distribution, namely — the parameter, determining the signal level respectively the noise level — a maximum likelihood technique is proposed to be applied. The graphical illustrations are presented that have been obtained by means of the computer simulation of the principle characteristics of the phase distribution under the study. The existence and uniqueness of the likelihood function’s maximum allow substantiating the possibility and the efficiency of solving the task of estimating signal’s level relative to noise level by means of the maximum likelihood technique. The elaborated method of estimating the un-noised signal’s level relative to noise, i. e. the parameter characterizing the signal’s intensity on the basis of measurements of the signal’s phase is an original and principally new technique which opens perspectives of usage of the phase measurements as a tool of the stochastic data analysis. The presented investigation is meaningful for solving the task of determining the phase and the signal’s level by means of the statistical processing of the sampled phase measurements. The proposed methods of the estimation of the phase distribution’s parameters can be used at solving various scientific and technological tasks, in particular, in such areas as radio-physics, optics, radiolocation, radio-navigation, metrology.

The article presents updated technologies for solving two classes of linear resource allocation problems with dynamically changing characteristics of situational management systems and awareness of experts (and/or trained robots). The search for solutions is carried out in an interactive mode of computational experiment using updatable knowledge systems about problems considered as constructive objects (in accordance with the methodology of formalization of knowledge about programmable problems created in the theory of S-symbols). The technologies are focused on implementation in the form of Internet services. The first class includes resource allocation problems solved by the method of targeted solution movement. The second is the problems of allocating a single resource in hierarchical systems, taking into account the priorities of expense items, which can be solved (depending on the specified mandatory and orienting requirements for the solution) either by the interval method of allocation (with input data and result represented by numerical segments), or by the targeted solution movement method. The problem statements are determined by requirements for solutions and specifications of their applicability, which are set by an expert based on the results of the portraits of the target and achieved situations analysis. Unlike well-known methods for solving resource allocation problems as linear programming problems, the method of targeted solution movement is insensitive to small data changes and allows to find feasible solutions when the constraint system is incompatible. In single-resource allocation technologies, the segmented representation of data and results allows a more adequate (compared to a point representation) reflection of the state of system resource space and increases the practical applicability of solutions. The technologies discussed in the article are programmatically implemented and used to solve the problems of resource basement for decisions, budget design taking into account the priorities of expense items, etc. The technology of allocating a single resource is implemented in the form of an existing online cost planning service. The methodological consistency of the technologies is confirmed by the results of comparison with known technologies for solving the problems under consideration.

This paper presents a systematic study of the application of convolutional neural networks (CNNs) as an efficient tool for the analysis of critical and low-temperature phase states in two dimensional spin system models. The problem of calculating the dependence of the average energy $\langle E\rangle_T^{}$ on the spatial distribution of exchange integrals $J_k^{}$ for the Edwards – Anderson model on a square lattice with frustrated interactions is considered.

We further construct a single convolutional classifier of phase states of the ferromagnetic Ising model on square, triangular, honeycomb, and kagome lattices, trained on configurations generated by the Swendsen – Wang cluster algorithm. Сomputed temperature profiles of the averaged posterior probability of the high-temperature phase, form clear S-shaped curves that intersect in the vicinity of the theoretical critical temperatures and allow one to determine $T_c^{}$ for the kagome lattice without additional retraining.

It is shown that convolutional models substantially reduce the root-mean-square error (RMSE) compared with fully connected architectures and efficiently capture complex correlations between thermodynamic characteristics and the structure of magnetic correlated systems.

Explainable Artificial Intelligence (XAI) is a field of artificial intelligence aimed at creating methods and tools for generating interpretable and human-understandable explanations of AI decisions. The relevance of model explainability increases with the deployment of artificial intelligence in critical domains (healthcare, finance, law), where algorithmic opacity can lead to serious consequences for users and society. This work presents an analytical review of the current state of the XAI field, covering theoretical foundations, methodology, and practical applications.

The examined explainable AI methods were selected and systematized based on a multi-level classification of XAI methods by problem formulation (goal, target audience, data type), methodology (application stage, model-specificity, methods, scale), and result form (representation, presentation, evaluation metrics).

A comparative analysis of explainable AI methods for various application domains is conducted. For classical machine learning, SHAP and LIME are examined in detail, revealing their theoretical foundations, computational characteristics, and limitations. For computer vision, gradient-based methods (SmoothGrad, Integrated Gradients), activation visualization methods (Grad-CAM, Grad-CAM++), perturbation-based methods (RISE, Occlusion), and conceptual explanations (TCAV, Network Dissection) are systematized. Special attention is paid to the specifics of applying XAI to natural language processing and large language models, including analysis of the faithfulness of Chain-of-Thought reasoning, natural language explanations, and attribution graph methods. Fundamental limitations of existing approaches to LLM explainability are identified and directions for future research are defined.

The review results demonstrate that XAI methods have reached significant maturity in classical machine learning and computer vision, however, their application to large language models remains an open research problem requiring the development of new explanation paradigms.

In the work is numerically investigated the influence of elastic and strength characteristics of hard materials with coatings of refractory compounds, received electric-spark doping, at influence of temperature and power factors using the finite element method.

The method of calculation of the boundaries of quality classes for quantitative characteristics of systems with any properties is adapted to search for boundaries of three quality classes. In addition to other results, adaptation of the method allowed to determine boundaries between quality classes at simultaneous «unacceptability » of high and low values of indicator characteristic of the system condition and simultaneous «inadmissibility » of high and low values of factors affecting the system.

This article represents numerical simulation technique for determining effective spectral electromagnetic properties (effective electrical conductivity and relative dielectric permittivity) of saturated porous media. Information about these properties is vastly applied during the interpretation of petrophysical exploration data of boreholes and studying of rock core samples. The main feature of the present paper consists in the fact, that it involves three-dimensional saturated digital rock models, which were constructed based on the combined data considering microscopic structure of the porous media and the information about capillary equilibrium of oil-water mixture in pores. Data considering microscopic structure of the model are obtained by means of X-ray microscopic tomography. Information about distributions of saturating fluids is based on hydrodynamic simulations with density functional technique. In order to determine electromagnetic properties of the numerical model time-domain Fourier transform of Maxwell equations is considered. In low frequency approximation the problem can be reduced to solving elliptic equation for the distribution of complex electric potential. Finite difference approximation is based on discretization of the model with homogeneous isotropic orthogonal grid. This discretization implies that each computational cell contains exclusively one medium: water, oil or rock. In order to obtain suitable numerical model the distributions of saturating components is segmented. Such kind of modification enables avoiding usage of heterogeneous grids and disregards influence on the results of simulations of the additional techniques, required in order to determine properties of cells, filled with mixture of media. Corresponding system of differential equations is solved by means of biconjugate gradient stabilized method with multigrid preconditioner. Based on the results of complex electric potential computations average values of electrical conductivity and relative dielectric permittivity is calculated. For the sake of simplicity, this paper considers exclusively simulations with no spectral dependence of conductivities and permittivities of model components. The results of numerical simulations of spectral dependence of effective characteristics of heterogeneously saturated porous media (electrical conductivity and relative dielectric permittivity) in broad range of frequencies and multiple water saturations are represented in figures and table. Efficiency of the presented approach for determining spectral electrical properties of saturated rocks is discussed in conclusion.

The article presents a method for linearization the effective function of material instantaneous deformation in order to generalize the torsional vibration equation to the case of nonlinearly deformable rheologically active shafts. It is considered layered and structurally heterogeneous, on average isotropic shafts made of nonlinearly viscoelastic components. The technique consists in determining the approximate shear modulus by minimizing the root-mean-square deviation in approximation of the effective diagram of instantaneous deformation.

The method allows to estimate analytically values of natural frequencies of layered and structurally heterogeneous nonlinearly viscoelastic shaft. This makes it possible to significantly reduce resources in vibration analysis, as well as to track changes in values of natural frequencies with changing geometric, physico-mechanical and structural parameters of shafts, which is especially important at the initial stages of modeling and design. In addition, the paper shows that only a pronounced nonlinearity of the effective state equation has an effect on the natural frequencies, and in some cases the nonlinearity in determining the natural frequencies can be neglected.

As equations of state of the composite material components, the article considers the equations of nonlinear heredity with instantaneous deformation functions in the form of the Prandtl’s bilinear diagrams. To homogenize the state equations of layered shafts, it is applied the Voigt’s hypothesis on the homogeneity of deformations and the Reuss’ hypothesis on the homogeneity of stresses in the volume of a composite body. Using these assumptions, effective secant and tangential shear moduli, proportionality limits, as well as creep and relaxation kernels of longitudinal, axial and transversely layered shafts are obtained. In addition, it is obtained the indicated effective characteristics of a structurally heterogeneous, on average isotropic shaft using the homogenization method previously proposed by the authors, based on the determination of the material deformation parameters by the rule of a mixture for the Voigt’s and the Reuss’ state equations.