The article examines corporate responsibility in the context of conflicting environmental and economic interests, which are exacerbated by the inadequacies of the legal framework. It emphasizes the importance of considering environmental factors in corporate decision-making and the necessity of developing a balanced legal framework that promotes sustainable development. The research also focuses on analyzing situations where legislative shortcomings lead to conflicts between environmental and economic interests. Based on comparative analysis, experience generalization, and the application of an eco-economic approach, the article provides recommendations for improving the legal framework to enhance corporate responsibility and ensure a balance between economic benefits and environmental preservation. This study specifically examines the situation in Azerbaijan, considering its status as an oil-producing country, and assesses the issues related to the environmental and ecological aspects of economic activities.

One of the most promising areas of scientific research in the field of analysis, forecasting and modelling of economic phenomena and processes is fuzzy logic. In the article with the use of the fuzzy logic apparatus (Fuzzy Logic toolkit of the MATLAB software package) a model for assessing the development of manufacturing indicators is developed. Key indicators for evaluating the activities of energy enterprises are analysed. The model is based on microeconomic indicators of the enterprises’ efficiency and development. The presented indexes pass through the stage of fuzzification, at which each measure is assigned the membership function; then comes the decision stage; finally, the task ends by the stage of defuzzification, i.e., bringing the resulting fuzzy value to precise ones. The application of the Mamdani fuzzy inference algorithm allows getting an exact value of the consolidated indicator of enterprise development. The resulting value allows making operational management decisions in the energy enterprises in real-time.

The article discusses the means and directions for improving the results of simulation modeling of suburban agriculture and, as a result, the creation of digital twins of farms. Most innovative technologies are still considered new areas for experimentation in agriculture. However, the digital twins being developed for agriculture implement many of the ideas that have already been tested in other industries. The article presents an optimization problem that allows the simulation of suburban agriculture to provide the city with fresh products. Particular attention is paid to modeling the sustainable development of suburban agriculture and the characterization of related data. At the same time, one of the biggest challenges is the need to constantly collect and update expanding data about the object in order to create digital twins. The result of the study is the construction of a simulation modeling system that forms digital twins of suburban crop and livestock production, and the determination of priorities for the selection of relevant data. In order to determine the conditions for realizing opportunities in the transition from suburban farming simulation to digital twins, a general modeling system is presented, consisting of simulation and optimization models, and a set of metrics is selected for the constant collection and updating of the digital twin. The created simulation model was previously worked out by running dozens of different options in the form of sets of initial data, and as a result of the model's operation, the article presents the best (optimal) responses. The necessary steps for the realization of this transition are defined. As a result of the activity of the proposed conceptual system, real-time information, and analytics allows to optimize the performance of the farm

The object of this research is integrating green infrastructure into sustainable urbanization zones within the context of digitalization. The problem addressed is the difficulty of ensuring urban sustainability without considering the green infrastructure in urban and suburban areas. The article argues that city sustainability cannot be effectively addressed without integrating green corridors that connect urban and suburban zones. The research proposes using optimization and simulation models to plan and manage the expansion of green corridors in sustainable urban areas. The results highlight the importance of a joint approach to green infrastructure development in urban and suburban areas, showing that interconnectivity is crucial for long-term environmental sustainability. Findings were interpreted by illustrating how simulation models can be used to assess the effectiveness of green infrastructure in real-time. The research demonstrates that the digital modeling of green corridors enhances planning precision, ensuring better connectivity between the city and surrounding areas. The key features that solved the problem include an optimization model, which enabled efficient planning for green corridor expansion, improving connectivity between urban and suburban areas. The paper uses digital simulation tools that allow for real-time assessment of green infrastructure's sustainability impact, leading to better-informed decision-making. The results are applicable in urban planning and sustainability management within rapidly urbanizing cities. The findings are most effective when cities have access to digital tools and aim to enhance green infrastructure's role in sustainability strategies

Research background:The study uses the key parameters of the spread of the epidemic, dividing the population into several groupsS- susceptible,E- exposed,I- infectious,R- recovered,D- dead. It is found that the model behaves differently depending on theR₀indicator - the average number of people that one infected manages to infect. Measures to suppress the epidemic undertaken by Azerbaijan and their effectiveness have been considered.Purpose of the article:The aim of the article is to model the current dynamics of the disease for future forecasting. The model takes into account all the main parameters of the epidemic: the proportion of severe patients and the mortality rate depending on the age of the patients, the duration of the incubation period and the infectious phase of the disease; incomplete registration of infected people due to the high prevalence of asymptomatic disease and insufficient testing; possible measures to contain and suppress the epidemic and their impact onR₀.Methods:The article uses the linear regression method, which consists in finding estimates of unknown parameters and the formation of a functional relationship between the sickness rate and the factors determining it.Findings & Value added:The constructed model analyzes the growth of patients in the country after removing the restrictive measures taken in early May on the basis of real statistics.

In the modern world, where efficiency, stability, and precision play a crucial role, the development and application of optimal control strategies in oscillatory systems hold significant importance. The issues related to the numerical solution of control problems associated with damping oscillatory systems consisting of two objects are considered. To numerically solve the discussed problem, the gradient projection method, based on the formula for the first variation of the functional, and the method of successive approximations, associated with the linearity of boundary problems describing oscillatory processes, are applied. The oscillations of one object are described by a wave equation with first-order boundary conditions, while a second-order ordinary differential equation models the oscillations of the other object. Furthermore, the original and the adjoint boundary value problems are solved using direct methods at each iteration step. An algorithm for the numerical solution of the problem is proposed, and based on this algorithm, a software code for implementation is developed. The numerical results obtained in the study demonstrate that there is convergence in terms of functionality, and the approximately optimal controls found in this process are minimizing sequences in the control space. The mechanism of controlling and regulating the operation of the system according to its input constraints is provided by observed feedback, allowing systems with limited excitation to maintain stability and optimal functioning in conditions of changing external or internal circumstances. The obtained results can also be used to forecast the system's behavior in the future, resource planning, prevention of emergencies, or optimization of production processes