List of publications on a keyword: «machine learning»
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Using artificial intelligence to improve business efficiency
ProceedingInnovative approaches to management in economic, technical and legal systems- Author:
- Inna G. Iglinskaia
- Work direction:
- Информационные технологии в управлении бизнесом
- Abstract:
- The article examines the role of artificial intelligence (AI) in improving the efficiency of business processes. In the context of rapid technological progress, companies are faced with the need to adapt to new realities, and AI is becoming a key tool for achieving competitive advantages. The main areas of AI application are analyzed, including automation of routine tasks, improvement of customer service, forecasting consumer behavior and optimization of resource management. Special attention is paid to examples of successful AI implementation in various industries such as finance, retail and manufacturing. The challenges and risks associated with the integration of AI into business, including issues of ethics and data protection, are also discussed. The article emphasizes the importance of a strategic approach to the introduction of AI technologies, as well as the need to train personnel to work with new tools. In conclusion, conclusions are drawn about the prospects of using AI to in
- Keywords:
- competitive advantages, machine learning, digital transformation, data analysis, personnel training, forecasting, Artificial intelligence (AI), data protection, business efficiency, process automation, customer service, resource optimization, business innovation, AI ethics, strategic implementation
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INDUSTRY 4.0 TECHNOLOGIES: MACHINE LEARNING AND THE CUSTOMER RELATIONSHIPS MANAGEMENT
ProceedingThe Topical Issues of the Humanities and Social Sciences: from Theory to Practice- Author:
- Pavel V. Malyzhenkov
- Work direction:
- Содержание и технологии профессионального образования
- Abstract:
- The Fourth Industrial Revolution represents the latest transformation of means of production in the history of humanity. These innovations are built upon preceding technical progress, starting from the creation of the network itself, its evolution from static to social through the introduction of blogs, wikis, and web services, further enriching it with semantic data to facilitate inter-machine interaction, and culminating in its current state. This work provides an overview of the most interesting methods and approaches in applying artificial intelligence within Industry 4.0 to address the optimization of customer relationship management systems.
- Keywords:
- machine learning, CRM, Industry 4, enabling technologies
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Company’s value evaluation through modifying its capital structure with bonds and stocks issuance simulation using machine learning and statistical analysis approaches
ProceedingRelevant issues of management, economics and economic security- Authors:
- Daria I. Nazarova, Natalia S. Semina, Leonid R. Nikulin, Iuliia S. Tsertseil
- Work direction:
- Анализ и прогнозирование основных тенденций современной экономики на макро-, мезо- и микроуровне
- Abstract:
- The present financial landscape is complexly woven with the interplay of financial instruments and technologies, reshaping the way companies manage their value. Financial instruments act as the cornerstone of capital structure, influencing cash flows and overall valuation. Meanwhile, financial technologies introduce innovation and efficiency via presenting unprecedented capabilities in assessing and forecasting the impact of these instruments on a company's worth. The ability to make timely decisions on resource allocation and capital raising is a key determinant of success in a rapidly evolving business landscape. Thus, the financial sector undergoes transformative changes, reshaping how companies navigate complexities and make informed decisions in an increasingly dynamic environment. The symbiosis of these elements is reshaping the future of finance, offering new avenues for creating and managing value in an interconnected world.
- Keywords:
- machine learning, capital structure, securities, company value, simulation modeling, statistical analysis
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Bioheuristics: theory, algorithms and applications
Book ChapterBioheuristics: theory, algorithms and applications- Authors:
- Sergei I. Rodzin, Iurii A. Skobtsov, Samer A. El'-Khatib
- Work direction:
- Авторская монография
- Abstract:
- The book examines the current state and problems of bioheuristics development, biographical and memetic algorithms, the issues of finding optimal solutions by trajectory algorithms and bioheuristics of multicriteria optimization. Ant and swarm bioheuristics, their features and modifications are presented. Hybrid formic and hypeuruistic swarm segmentation algorithms of complexly structured images are considered as applications. The monograph is interdisciplinary, it is addressed to masters and graduate students studying the theory and practice of creating intelligent information systems and technologies, as well as specialists in the theoretical foundations of computer science, software engineering, system analysis, information management and processing, information systems and processes, bioinformatics.
- Keywords:
- experiment, modeling, optimization, machine learning, bioheuristics, drift analysis, ant system, particle swarm, image segmentation, fitness function, evolutionary computation, NFL theorem