The problem of fault estimation in linear non-stationary systems based on the methods of optimal control is studied. To solve the problem, a bank of observers is sensitive to some group of faults and insensitive to others. Each observer provides total estimate of faults to which it is sensitive. The estimate of every fault is a result of the algebraic equation solution. The theoretical results are illustrated by practical example. Contribution of the authors: the authors contributed equally to this article. The authors declare no conflicts of interests.

A robust filtering algorithm for a discrete stochastic system with interval parameters depending of the hidden Markov chain is considered. To represent the interval parameters, a probabilistic approach is used, which is based on the replacement of indeterminate interval-type parameters with independent random variables with a uni-form distribution. Recurrent Kalman filtering schemes and algorithms for estimating the state of jump parameter are used. An example is provided to illustrate the proposed approach.

An algorithm for labeling data is presented to train a classifier capable of identifying support and resistance levels in financial market data. Using data obtained from this algorithm, a CNN-LSTM-MLP model was trained, incorporating causal convolutions, LSTM, and fully connected layers. An experiment with a simple trading strategy demonstrated the practical applicability of the model, accompanied by a 10% increase in profitability com-pared to a basic strategy where the model was not used.

The task of diagnosing industrial products for the presence of thin-length defects such as cracks and abrasions is considered. This problem is solved in the conditions of tomographic reconstruction and belongs to the class of reverse tasks. The classic algorithm of computed tomography has a high complexity in solving this problem, and in the case of a small thickness of the defect, it may not restore it at all. In this paper, software has been developed to solve a special problem of flaw detection based on a modified algorithm that uses a priori information about the reference of the product as a heuristic amplification. The results of computational experiments demonstrate the effec-tiveness of the proposed approach in solving the problem of detecting cracks in the object under study and allow us to conclude that its prospects in the tasks of industrial flaw detector.

It is known that geophysical fields (geomagnetic, gravitational and electromagnetic) in the context of recorded or modeled data are a set of several coaxial vector components characterizing the change in the corresponding parameter in space and time. Currently practiced approaches to organizing the storage of such data are based, as a rule, on one of the data models. At the same time, joint storage of source metadata and geophysical data directly in many cases is associated with inefficient use of associated computing resources. This paper considers an approach focused on separate storage, but joint complex application of metadata and data of geophysical field recording tools, taking into account their multi-vector nature and tensor representation of the analyzed parameters. Using the example of the geomagnetic field, the effectiveness of the proposed approach is considered in the context of optimizing data storage, on the one hand, and increasing the computational speed of executing queries to them, on the other.

In the paper we modified Price Sensitivity Meter (PSM) technique using additional information on Sα-symmetry of price sensitivity curves. New price estimates are unbiased, consistent, asymptotically normal, their variances are smaller than those of the usual ones, so new estimators are more accurate. Confidence intervals for prices are obtained taking into account Sα-symmetry.

The problem of determining the discrepancy of the onboard clock installed on GLONASS satellites relative to the system time scale based on regression models is being considered. It has been shown that the diver-gence behavior of time scales is best described by an additive nonlinear regression model in combination with an autoregressive model, with the mean square error for most satellites not exceeding 0.2 ns.

The mathematical model of the process of deposition of galvanic coating is considered, the distinctive feature of which is the consideration of concentration polarization. The results of studies of the relationship between the polarization of the electrodes, the uniformity of the coating distribution and the process parameters, such as the current density, the distance between the electrodes, the flow rate and the temperature of the electrolyte are presented. The hypothesis of the relationship between the uniformity of the coating and the cathode polarization is confirmed. It is established that the best distribution of the coating is ensured at higher values of electrode polarization.

The problem of constructing a set of all simple paths in fuzzy transport networks connecting two nodes specified in it is considered. Earlier, to solve this and other similar problems for clear transport networks, an effective mathematical apparatus was developed using the concept of a graph of simple paths. It is shown that the problem under consideration can be reduced to the construction of many simple paths in a clear transport network. This reduc-tion is based on the transformation of a fuzzy graph (a fuzzy network model) into a corresponding clear graph.

The article focuses on developing a methodology to model the transshipment process in universal sea-ports. The proposed models have the form of a controlled queuing network, which receives multiple incoming flows of requests representing the arrival of goods via both land and sea transport. We employ different types of queueing systems, including controlled systems that adjust operational parameters based on predefined rules, to model the various subsystems of the port. This approach allows the model to account for the impact of random factors on port operations, as well as changes in transshipment technology across subsystems. To validate the methodology, we apply it to the universal seaport of Quang Ninh, Vietnam. A numerical analysis of the port’s model provides insights into its current throughput capacity and forecasts operational efficiency under increased cargo flows.