S V Solodov’s scientific contributions

Distributed ledger technologies can support a rapid transition to smart cities and provide a high level of urban quality. Despite the large number of approaches to the problem of synthesizing smart city management systems, there is still no universal solution. One of the most promising areas is the construction of neural network control systems. The optimization module for a neurosimulator is developed that can operate in real time. The study of the neurosimulator on various data of anthropogenic load showed the possibility of obtaining high control accuracy.

The current state of social and economic development of regions requires new approaches to increasing the efficiency of their activities, and above all scientific approaches to forecasting, as one of the main components of the strategy of transformative changes. It is proposed to use an architecture based on neuro-fuzzy networks for forecasting regional development, which is characterized by a high learning rate due to the linear dependence of outputs on adjustable weights. Scientific and methodological approaches are developed to determine the global minimum of the learning criterion, taking into account the decision rules “if-then”.

The use of modern information and communication technologies is an essential condition for the formation of the transport infrastructure of a smart city. Scientific and methodological approaches are developed to effectively monitor the transport infrastructure of a smart city based on multi-channel metric learning in the Internet of Things. The proposed solutions provide invariance to the type and nature of the movement of objects. The principles of technical implementation of the proposed method are substantiated using the characteristics of unmanned aerial vehicles of a smart city. Adaptive automatic switching of transport infrastructure monitoring channels is implemented in the form of a neural network analyzer software.