The paper investigates the use of architectural combinatorics to solve the problems of multifunctional residential complexes in the conditions of digital transformation. The main methods of combinatorics, including conceptual and formal approaches, are considered. The main stages of evolution of the method, starting from constructivism, and the role of modern digital technologies such as BIM, parametric modeling, machine learning and artificial intelligence in the implementation of combinatorial approaches are described. Attention is given to sustainable architecture and optimization of spatial solutions. Successful and problematic project examples are analyzed. Limitations of the application of the technologies are analyzed, as well as ethical and social aspects of their use. The conclusions substantiate the significance of the method in the context of contemporary challenges.

Keywords: architectural combinatorics, combinatorial methods, multifunctional residential complex, sustainable development, sustainable architecture, adaptive architecture, digital technologies, BIM, parametric modeling, machine learning, artificial intelligence

This paper presents the results of a study aimed at developing a method for semantic segmentation of thermal images using a modified neural network algorithm that differs from the original neural network algorithm by a higher speed or processing graphic information. As part of the study, a modification of the DeepLabv3+ semantic segmentation neural network algorithm was carried out by reducing the number of parameters of the neural network model, which made it possible to increase the speed of processing graphic information by 48% – from 27 to 40 frames per second. A training method is also presented that allows to increase the accuracy of the modified neural network algorithm; the accuracy value obtained was 5% lower than the accuracy of the original neural network algorithm.

Keywords: neural network algorithms, semantic segmentation, machine learning, data augmentation

The article offers examples of simulated processes for creating a digital twin, a monitoring process, and a cargo transportation process. A theory is proposed for calculating a mathematical model based on Petri nets. Models for placing an order and its delivery are proposed, as well as a model of information flows using the example of developing models for the processes of transporting perishable products in a refrigerated container.

Keywords: Business process, modeling, BPMN, IDEF1, DFD, Petri nets, mathematical model, intelligent 3D model

The paper presents the results of calculating reliability indicators and analyzing the fault tolerance of the subsystem for monitoring and controlling steam pressure in the steam curtain of a tubular furnace of a diesel fuel hydrotreating technological unit. The effectiveness of reserving critical elements to improve functional safety is substantiated.

Keywords: reliability, fault tolerance, steam curtain, tubular furnace, hydrotreating, diesel fuel, redundancy, functional safety

The article examines the optimization of processes for receiving and transferring design and working documentation in contracting construction organizations using Building Information Modeling (BIM) technologies. The current state of document management in construction is analyzed, and problem areas of traditional approaches are identified. A concept for implementing BIM in document management processes is proposed, along with an algorithm for documentation transfer and regulations for interaction between construction process participants. The results of testing the developed solutions on a pilot project are presented, confirming their effectiveness. Promising directions for further research in this field are determined.

Keywords: building information modeling, design documentation, working documentation, construction production, common data environment

The article is devoted to the development of a tool for automated generation of time constraints in the context of circuit development in the basis of programmable logic integrated circuits (FPGAs). The paper analyzes current solutions in the field of interface tools for generating design constraints. The data structure for the means of generating design constraints and algorithms for reading and writing Synopsys Design Constraints format files have been developed. Based on the developed structures and algorithms, a software module was implemented, which was subsequently implemented into the circuit design flow in the FPGA basis - X-CAD.

Keywords: computer-aided design, field programmable gate array, automation, design constraints, development, design route, interface, algorithm, tool, static timing analysis

The article presents an analysis of the application of the Socratic method for selecting machine learning models in corporate information systems. The study aims to explore the potential of utilizing the modular architecture of Socratic Models for integrating pretrained models without the need for additional training. The methodology relies on linguistic interactions between modules, enabling the combination of data from various domains, including text, images, and audio, to address multimodal tasks. The results demonstrate that the proposed approach holds significant potential for optimizing model selection, accelerating decision-making processes, and reducing the costs associated with implementing artificial intelligence in corporate environments.

Keywords: Socratic method, machine learning, corporate information systems, multimodal data, linguistic interaction, business process optimization, artificial intelligence

The article examines the modular structure of interactions between various models based on the Socratic dialogue. The research aims to explore the possibilities of synthesizing neural networks and system analysis using Socratic methods for managing corporate IT projects. The application of these methods enables the integration of knowledge stored in pre – trained models without additional training, facilitating the resolution of complex management tasks. The research methodology is based on analyzing the capabilities of multimodal models, their integration through linguistic interactions, and system analysis of key aspects of IT project management. The results include the development of a structured framework for selecting suitable models and generating recommendations, thereby improving the efficiency of project management in corporate environments. The scientific significance of the study lies in the integration of modern artificial intelligence approaches to implement system analysis using multi – agent solutions.

Keywords: neural networks, system analysis, Socratic method, corporate IT projects, multimodal models, project management

Monolithic reinforced concrete structures are widely used in construction practice. When concreting massive structures, technological and organizational difficulties may arise in ensuring the continuity of the concrete mix, which leads to the need to organize working joints. Studies conducted earlier show a decrease in strength characteristics in this area and the bearing capacity of the entire structure. Known and practical solutions to the problem cause additional labor, material and time costs. In this paper, we propose a method for installing a technological seam caused by unplanned interruptions in concreting for technological and organizational reasons, based on previously conducted experimental and pilot studies by the author of this article. The proposed method consists in the fact that, when a break occurs, subsequent concreting is carried out with a break from the previously concreted section, while a stepped profile is formed with the help of fasteners, as a result of which a space is organized bounded by the surface of the first and second concreted sections and a formwork of a shape close to pyramidal, similar to the run-in fines, during the construction of brickwork. After holding the concrete of both sections and dismantling the cut-offs, a concrete mixture of the same class on Portland cement is laid within the free space of the applied slag-alkali solution with the characteristics: slag with a basicity modulus of more than 1.0; an alkaline solution with a hydrogen index level above 12.0. The technological features of performing forced seam concreting according to the proposed method are given.

Keywords: concrete contact zone, technological concreting joint, unplanned concreting working joint, monolithic reinforced concrete structures

The reuse of ash and slag waste from coal combustion is of great economic and environmental importance. The most material-intensive area of their reuse is the stabilization of ash and slag mixtures with Portland cement for the construction of layers of highways. A technical understanding of the processes of structure formation in stabilized ash and slag mixtures makes it possible to regulate the final properties and quality of the layers of road clothing and the roadbed. Strengthening of ash and slag mixtures with Portland cement makes it possible to increase the physical and mechanical properties of ash and slag mixtures: strength, frost resistance, density, etc.

Keywords: ash and slag mixtures, stabilized ash and slag mixtures, structure formation of stabilized ash and slag mixtures, sportland cement, microstructure of the ash and slag mixture

The article presents the results of a numerical experiment comparing the accuracy of neural network recognition of objects in images using various types of data set extensions. It describes the need to expand data sets using adaptive approaches in order to minimize the use of image transformations that may reduce the accuracy of object recognition. The author considers such approaches to data set expansion as random and automatic augmentation, as they are common, as well as the developed method of adaptive data set expansion using a reinforcement learning algorithm. The algorithms of operation of each of the approaches, their advantages and disadvantages of the methods are given. The work and main parameters of the developed method of expanding the dataset using the Deep-Q-Network algorithm are described from the point of view of the algorithm and the main module of the software package. Attention is being paid to one of the machine learning approaches, namely reinforcement learning. The application of a neural network for approximating the Q-function and updating it in the learning process, which is based on the developed method, is described. The experimental results show the advantage of using data set expansion using a reinforcement learning algorithm using the example of the Squeezenet v1.1 classification model. The comparison of recognition accuracy using data set expansion methods was carried out using the same parameters of a neural network classifier with and without the use of pre-trained weights. Thus, the increase in accuracy in comparison with other methods varies from 2.91% to 6.635%.

Keywords: dataset, extension, neural network models, classification, image transformation, data replacement

The ecology of modern megacities is one of the most relevant and acute topics of our time. Rapid growth of cities, increase in the urban population and development of industry have led to significant changes in the environment. This article examines the main environmental problems of modern megacities, factors affecting the ecology of urban areas. An analysis of the influence of solar radiation on the formation of the microclimate and ecology of the air basin of cities is carried out. The conditions for the occurrence of air flows of thermal origin, which contribute to the improvement of the aeration regime of urban areas, are studied.

Keywords: ecology, urban area, air exchange, convective flows, insolation, aeration regime, dense development, solar radiation, air basin, microclimate, heat island

The analysis of the environmental impact of the largest enterprises located in the Southern and Northern industrial zones of the linear city of Volgograd has been carried out, and the need to change approaches to designing a comfortable urban environment, which currently take into account the average data for characterizing the ecological state of a particular territory, has been shown. The analysis confirmed the need to take into account the local impact of industrial enterprises on the components of the urban environment when justifying the selection and planning of appropriate modern spaces within the framework of the Federal Project "Creating a comfortable Urban environment".

Keywords: urban environment, comfort, urban environment quality index, modern spaces, environmental analysis, environmental friendliness, environmental safety

The article analyzes the design features in the conditions of the Far North. Attention is focused on the need to take into account climatic, geographical and socio-economic factors, as well as the use of innovative approaches to ensure economic development. The authors propose compensatory measures aimed at mitigating the negative conditions of the region, contributing to the successful implementation of projects in the Far North, as well as ensuring safety and reducing the duration of construction projects. The study of the most significant compensatory measures and their effective application is conducted.

Keywords: design, Far North, Arctic, regional features, unique factors, climatic conditions, geographical conditions, innovative approaches, development, compensatory measures

The transition from scheduled maintenance and repair of equipment to maintenance based on its actual technical state requires the use of new methods of data analysis based on machine learning. Modern data collection systems such as robotic unmanned complexes allow generating large volumes of graphic data in various spectra. The increase in data volume leads to the task of automating their processing and analysis to identify defects in high-voltage equipment. This article analyzes the features of using computer vision algorithms for images of high-voltage equipment of power plants and substations in the infrared spectrum and presents a method for their analysis, which can be used to create intelligent decision support systems in the field of technical diagnostics of equipment. The proposed method uses both deterministic algorithms and machine learning. Classical computer vision algorithms are applied for preliminary data processing in order to highlight significant features, and models based on unsupervised machine learning are applied to recognize graphic images of equipment in a feature space optimized for information space. Image segmentation using a spatial clustering algorithm based on the density distribution of values ​​taking into account outliers allows detecting and grouping image fragments with statistically close distributions of line orientations. Such fragments characterize certain structural elements of the equipment. The article describes an algorithm that implements the proposed method using the example of solving the problem of detecting defects in current transformers, and presents a visualization of its intermediate steps.

Keywords: diversification of management, production diversification, financial and economic purposes of a diversification, technological purposes of ensuring flexibility of production