Intelligent control systems in urban planning conflicts: Social media users’ perception

The relevance of this study is determined by the need to develop technologies for effective urban systems management and resolution of urban planning conflicts. The paper presents an algorithm for analyzing urban planning conflicts. The material for the study was data from social networks, microblogging, blogs, instant messaging, forums, reviews, video hosting services, thematic portals, online media, print media and TV related to the construction of the North-Eastern Chord (NEC) in Moscow (RF). To analyze the content of social media, a multimodal approach was used. The paper presents the results of research on the development of methods and approaches for constructing mathematical and neural network models for analyzing the social media users’ perceptions based on their digital footprints. Artificial neural networks, differential equations, and mathematical statistics were involved in building the models. Differential equations of dynamic systems were based on observations enabled by machine learning. Mathematical models were developed to quickly detect, prevent, and address conflicts in urban planning in order to manage urban systems efficiently. In combination with mathematical and neural network model the developed approaches, made it possible to draw a conclusion about the tense situation around the construction of the NEC, identify complaints of residents to constructors and city authorities, and propose recommendations to resolve and prevent conflicts. Research data could be of use in solving similar problems in sociology, ecology, and economics. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Авторы
Gabdrakhmanova N. 1 , Pilgun M.2
Издательство
MDPI AG
Номер выпуска
14
Язык
Английский
Статус
Опубликовано
Номер
6579
Том
11
Год
2021
Организации
  • 1 S.M. Nikol’skii Mathematical Institute, Peoples Friendship University of Russia (RUDN University), Moscow, 117198, Russian Federation
  • 2 Institute of Linguistics, Russian Academy of Sciences, Moscow, 125009, Russian Federation
Ключевые слова
Differential equations; Neural networks; Perception cognitive systems; Social media; Speech
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