Economics digitalization as a base for changing the globalization model: trends and challenges

В статье говорится, что глобализация является продуктом эволюции государственных рыночных систем. Разрешаются противоречия, возникающие на стадии зрелости рыночной системы. Глобализация, возникающая в результате эволюции рыночных систем, трансформирует международную экономику. Конечной точкой глобализации является формирование единой сети мировой экономики - геоэкономику. Основой этой трансформации является цифровая экономика, которая в корне меняет не только тенденции глобализации, но и создает новые вызовы для человечества

Artificial neural network-based decision support system for development of an energy-efficient built environment

Implementing energy-efficient solutions in a built environment is important for reaching international energy reduction targets. For advanced energy efficiency-related solutions, computer-based decision support systems are proposed and rapidly used in a variety of spheres relevant to a built environment. Present research proposes a novel artificial neural network-based decision support system for development of an energy-efficient built environment. The system was developed by integrating methods of the multiple criteria evaluation and multivariant design, determination of project utility and market value, and visual data mining by artificial neural networks. It enables a user to compose up to 100,000,000 combinations of the energy-efficient solutions, analyze strengths and weaknesses of a built environment projects, provide advice for stakeholders, and calculate market value and utility degree of the projects. For visual data mining, self-organizing maps (type neural networks) are used, which may influence the choosing of the final set of alternatives and criteria in the decision-making problem, taking into account the discovered similarities of alternatives or criteria. A system was validated by the real case study on the design of an energy-efficient individual house. Keywords: energy-efficiency; built environment; solutions; artificial neural networks; decision support system; quantitative and qualitative analysi

Artificial Neural Network-Based Decision Support System for Development of an Energy-Efficient Built Environment

Настоящее исследование предлагает новую искусственную нейронную сеть на основе системы поддержки принятия решений для развития энергоэффективной искусственной среды. Система была разработана путем интеграции методов оценки нескольких критериев и многовариантного проектирования, определения полезности и рыночной стоимости проекта, а также извлечения визуальных данных с помощью искусственных нейроных сетей

Artificial Neural Network-Based Decision Support System for Development of an Energy-Efficient Built Environment

Implementing energy-efficient solutions in a built environment is important for reaching international energy reduction targets. For advanced energy efficiency-related solutions, computer-based decision support systems are proposed and rapidly used in a variety of spheres relevant to a built environment. Present research proposes a novel artificial neural network-based decision support system for development of an energy-efficient built environment. The system was developed by integrating methods of the multiple criteria evaluation and multivariant design, determination of project utility and market value, and visual data mining by artificial neural networks. It enables a user to compose up to 100,000,000 combinations of the energy-efficient solutions, analyze strengths and weaknesses of a built environment projects, provide advice for stakeholders, and calculate market value and utility degree of the projects. For visual data mining, self-organizing maps (type neural networks) are used, which may influence the choosing of the final set of alternatives and criteria in the decision-making problem, taking into account the discovered similarities of alternatives or criteria. A system was validated by the real case study on the design of an energy-efficient individual house

Forest Carbon Resources of Belarus

The monograph outlines the views of Belarusian experts on the contribution of the forest sector of Belarus to mitigation of weather and climate impacts on the environment which is made through carbon dioxide absorption by foreste and partial sequestration of carbon in the forest and components. It touches upon the calculation of carbon dioxide emmissions and absorption, the carbon budget of the Belarusian forest fund, relationship between the age and species structure and the carbon dioxide absorption by forests, measures on increasung of carbon dioxide absorption by forests, etc