This article deals with the problem of determining the cost of renting real estate. The idea of minimizing the absolute error function using artificial neural networks is substantiated. Particular attention is paid to the process of determining the input data of the neural network. In particular, the problems of determining such parameters as the improvement of the region and premises. The article clarifies the features of determining the weight coefficients to determine the technical equipment of the room using a genetic algorithm. A model of neural network architecture is proposed. The model of change of weight coefficients is described. As a result, the model was tested on test data, and the model of data correction taking into account price dynamics was described.
Keywords: neural network, data mining, data analysis, real estate rental, regression, genetic algorithm, Informatics, machine learning, cost estimation, modeling, extrapolation
This article presents a mathematical model of the distributed registry as a Queuing network. The main components of this network, as well as their formal representation are considered. The model of the peer-to-peer network is visualized, the vector of the network state is defined, and the restrictions of the state space are defined. After that, the laws of distribution of individual flows and service time were presented. In addition, the design elements of the infinitesimal matrix were determined. Based on the data obtained, a simulation model of this process was produced. For simulation, the Anylogic package was used. The results of simulation were analyzed and the most optimal parameters were selected.
Keywords: Queuing network, information security, distributed registries, computer science and engineering, mathematical modeling information system, corda