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With the rapid development of artificial intelligence technology and increasing material data, machine learning- and artificial intelligence-assisted design of high-performance steel materials is becoming a mainstream paradigm in materials science. Machine learning methods, based on an interdisciplinary discipline between computer science, statistics and material science, are good at discovering correlations between numerous data points. Compared with the traditional physical modeling method in material science, the main advantage of machine learning is that it overcomes the complex physical mechanisms of the material itself and provides a new perspective for the research and development of novel materials. This review starts with data preprocessing and the introduction of different machine learning models, including algorithm selection and model evaluation. Then, some successful cases of applying machine learning methods in the field of steel research are reviewed based on the main theme of optimizing composition, structure, processing, and performance. The application of machine learning methods to the performance-oriented inverse design of material composition and detection of steel defects is also reviewed. Finally, the applicability and limitations of machine learning in the material field are summarized, and future directions and prospects are discussed. [ABSTRACT FROM AUTHOR]

The modern economy with all the variety of its structural elements, which every year is increasingly immersed in a hyper-connected digital space, new conditions of institutional functioning caused by both a change in technological patterns and innovative forms of thinking, needs to adjust the basic, established principles and models of economic growth. If earlier the material productive factors was played a key role, today their importance is to some extent offset by the increasing role of non-material factors of production, the most important of which should include reputation capital. The purpose of the article is to comprehend and theoretically support this scientific problem. The need to revise some principles of building models of economic dynamics and strategic management of the region based on the use and revision of structural, logical and evolutionary views on the construction of this process is substantiated in the article. Based on the results of systematization of the evolution of methodological approaches to assessing the effectiveness of regional socio-economic development of territories / regions, the position is substantiated, according to which, in modern economic conditions, the effectiveness of territorial development should be based on research and strengthening of reputation capital.