perceptron

The role of functional activation in neural networks in the context of financial time series analysis

Nowadays, neural networks are among the most popular analysis tools.  They are effective in solving classification, pattern recognition, and clustering problems.  This paper provides a detailed description and analysis of the operational principles of two neural networks, namely a Siamese network and a multilayer perceptron.  A model for using these neural networks in time series forecasting is proposed.  As an example, a web application was created in which the described neural networks were used to analyze the correlation between pairs of financial assets and assess t

Evaluation of transport system configuration by efficiency indicators

The study is devoted to the process of evaluating the efficiency of the transport system in terms of urban mobility. The approach is based on the use of a system of performance indicators using neurocomputer technologies. Generalized models for obtaining a vector of performance indicators and an integral performance indicator in the form of computer neural networks are proposed. It is shown that to record the fact that the indicator values fall to the threshold and below, it is enough to use a neural network built on perceptron neurons.