Mathematical Models of Time Series of Intensities of Network Traffic with Different Approaches to Their Creating autoregressive
models based on statistical analysis of time row measurements. Algorithm of
neural network model Economic and predictive modeling of company's development as major strategic planning prerequisites), correlation and regression analysis and
neural simulation. Results from the analysis, made in STATISTICA
Principles of decision-making systems building based on the integration of neural networks and semantic modelsGolovko, V. A.,
Kroshchanka, A.,
Ivashenko, V. P.,
Kovalev, M.,
Taberko, V.,
Ivaniuk, D. S. This article reviews the benefits of integration
neural network and semantic
models for building
Trees classification based on Fourier coefficients of the sapflow density fluxIn this paper we study the possibility to use the artificial
neural networks for trees
Cryptocurrencies chaotic co-movement forecasting with neural networks chaotic co-movement forecasting using non-linear
models like
Neural networks. The study finds that LSTM
Audio/Speech Coding Based on the Perceptual Sparse Representation of the Signal with DAE Neural Network Quantizer and Near-End Listening EnhancementHerasimovich, V.,
Petrovsky, Al. A.,
Avramov, V. V.,
Petrovsky, A.,
Герасимович, В. Ю.,
Петровский, Ал. А.,
Аврамов, В. В.,
Петровский, А. А. algorithm based on the artificial
neural networks with a deep autoencoder (DAE) architecture is presented
Detection of cardiac arrhythmia based on the analysis of electrocardiogram using deep learning models of convolutional (CNN) and recurrent deep
neural networks with LSTM unit. The results of performed computer
Spectrum Hole Prediction in LTE-Based Cognitive Radio System Using Kolmogorov-Arnold Network, the Kolmogorov-Arnold
network (KAN) architecture is used. A
model structure has been developed that collects data
Prototype of classifier for the decision support system of legal documents, an original
model based on an artificial
neural network was developed, which shows an unmistakable