Neural network technologies in economics study aid

Neural network technologies in economics study aid

The study aid covers the use in economics of a number of end-to-end technologies, such as “Artificial Intelligence” and “Neurotechnologies, Virtual and Augmented Reality Technologies”. The publication examines the use of neural network technologies in economic problems, such as assessing the financi...

Deskribapen osoa

Gorde:

Xehetasun bibliografikoak
Egile nagusia:	Kovalenko, A. V. (070)
Formatua:	Книга
Gaiak:	neural network technologies financial condition economic condition creditworthiness neural network
Sarrera elektronikoa:	Перейти к просмотру издания
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Antzeko izenburuak

Using neural network technologies to assess the quality characteristics of food
nork: Sadovoy, V. V., et al.
Argitaratua: (2021)

Neural Networks in Production
nork: Rudakova, T. A., et al.
Argitaratua: (2024)

Hamming neural network in discrete form
nork: Shaposhnikov, A. V., et al.
Argitaratua: (2022)

A method for predicting the evolvement of an emergency zone based on artificial neural networks
nork: Petrenko, V. I., et al.
Argitaratua: (2021)

Neural network analysis for image classification
nork: Vershkov, N. A., et al.
Argitaratua: (2022)

Neural network approach to prediction of the liquid petroleum products viscosity
nork: Koldaev, A. I., et al.
Argitaratua: (2021)

Optimization of Artificial Neural Networks using Wavelet Transforms
nork: Vershkov, N. A., et al.
Argitaratua: (2023)

Survey of Optimization Algorithms in Modern Neural Networks
nork: Abdulkadirov, R. I., et al.
Argitaratua: (2023)

Development of a convolution algorithm for the content of a Web resource for processing by a neural network
nork: Gorshkov, S. N., et al.
Argitaratua: (2020)

Hardware and software implementation of neural network control of power systems based on the system of residual classes
nork: Tikhonov, E. E., et al.
Argitaratua: (2020)

Transverse-layer partitioning of artificial neural networks for image classification
nork: Vershkov, N. A., et al.
Argitaratua: (2024)

Theoretical Analysis of the Convolutional Neural Networks Acceleration by Organizing Calculations According to the Winograd Method
nork: Abdulsalyamova, A. S., et al.
Argitaratua: (2023)

Adaptive finite ring neural network
nork: Evdokimov, A. A., et al.
Argitaratua: (2019)

Using neural networks in building a psychological typology
nork: Solomonov, V. A., et al.
Argitaratua: (2019)

Optimization of neural network training for image recognition based on trigonometric polynomial approximation
nork: Vershkov, N. A., et al.
Argitaratua: (2022)

Optimization of computational complexity of an artificial neural network
nork: Vershkov, N. A., et al.
Argitaratua: (2021)

Residue number system-based solution for reducing the hardware cost of a convolutional neural network
nork: Chervyakov, N. I., et al.
Argitaratua: (2020)

Development of the neural network method for analyzing the literary text from the point of view of genre identification
nork: Babenko, M. G., et al.
Argitaratua: (2018)

Improving the methodology for analyzing organizational creditworthiness based on the time factor
nork: Rusetskaya, E. A., et al.
Argitaratua: (2021)

Designing Computer Simulators in Support of a Propaedeutic Course on Neural Network Technologies
nork: Ionisyan, A. S., et al.
Argitaratua: (2023)

Method for Convolutional Neural Network Hardware Implementation Based on a Residue Number System
nork: Valueva, M. V., et al.
Argitaratua: (2023)

System for neural network recognition of malignant pigmented skin neoplasms with image pre-processing
nork: Lyakhova, U. A., et al.
Argitaratua: (2021)

Image recognition by a second-order convolutional neural network with dynamic receptive fields
nork: Nemkov, R. M., et al.
Argitaratua: (2018)

The wave model of artificial neural network
nork: Vershkov, N. A., et al.
Argitaratua: (2020)

Analysis of Neural Networks for Image Classification
nork: Vershkov, N. A., et al.
Argitaratua: (2023)

Development of prognostic neural network models based on non-positional coding for automatic control systems
nork: Tikhonov, E. E., et al.
Argitaratua: (2019)

Application of the residue number system to reduce hardware costs of the convolutional neural network implementation
nork: Valueva, M. V., et al.
Argitaratua: (2020)

Using of a convolutional neural network with changing receptive fields in the tasks of image recognition
nork: Nemkov, R. M., et al.
Argitaratua: (2018)

Discrete Neural Network of Bidirectional Associative Memory
nork: Shaposhnikov, A. V., et al.
Argitaratua: (2023)

Using virtual data for training deep model for hand gesture recognition
nork: Nikolaev, E. I., et al.
Argitaratua: (2018)

Privacy-preserving neural networks with Homomorphic encryption: Challenges and opportunities
nork: Babenko, M. G., et al.
Argitaratua: (2021)

Multimodal Neural Network for Recognition of Cardiac Arrhythmias Based on 12-Load Electrocardiogram Signals
nork: Kiladze, M. R., et al.
Argitaratua: (2023)

Adaptive system monitoring of the technical condition technological objects based on wireless sensor networks
nork: Fedorenko, V. V., et al.
Argitaratua: (2020)

Hardware implementation of a convolutional neural network using calculations in the residue number system
nork: Chervyakov, N. I., et al.
Argitaratua: (2019)

A robotic complex control method based on deep reinforcement learning of recurrent neural networks for automatic harvesting of greenhouse crops
nork: Petrenko, V. I., et al.
Argitaratua: (2021)

Analytical review of the methods of dynamic load balancing under conditions of uncertainty in the execution time of tasks
nork: Shiriaev, E. M., et al.
Argitaratua: (2021)

Neural Network System for Recognizing Images Affected by Random-Valued Impulse Noise
nork: Orazaev, A. R., et al.
Argitaratua: (2023)

System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network
nork: Lyakhov, P. A., et al.
Argitaratua: (2022)

An intelligent system for content generation
nork: Nikolaev, E. I., et al.
Argitaratua: (2018)

An intelligent system for content generation
nork: Nikolaev, E. I., et al.
Argitaratua: (2018)