Titlebook: Artificial Intelligence and Soft Computing; 19th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2020

judicial

Deep Recurrent Modelling of Stationary Bitcoin Price Formation Using the Order Flowd after the bubble. We show that without any retraining, the proposed model is temporally stable even as Bitcoin trading shifts into an extremely volatile “bubble trouble” period. The significance of the result is shown by benchmarking against existing state-of-the-art models in the literature for modelling price formation using deep learning.

lacrimal-gland

Application of Neural Networks and Graphical Representations for Musical Genre Classificationgnized by the networks. We show that the networks have learned to distinguish between genres upon features observable by a human listener and compare the metrics for the network models. Results of the conducted experiments are described and discussed, along with our conclusions and comparison with similar solutions.

COMA

0302-9743 nce and Soft Computing, ICAISC 2020, held in Zakopane, Poland*, in October 2020..The 112 revised full papers presented were carefully reviewed and selected from 265 submissions. The papers included in the first volume are organized in the following six parts:??neural networks and their applications;

accessory

改進(jìn)

Fundamental Theories of Physicswhich result in a significant reduction of the calculation time. This modification of the CG algorithm was tested on selected examples. The performance of our method and the classic CG method was compared.

發(fā)電機(jī)

Monoranjan Maiti,Samir Maity,Arindam Roy that scientists already exhibited that both systems exhibit almost the same behavior dynamics (chaotic regimes etc.), researchers still take both classes of algorithms as two different classes. We show in this paper, that there are some similarities, that can help to understand evolutionary algorithms as neural networks and vice versa.

黃瓜

流浪者

Fast Conjugate Gradient Algorithm for Feedforward Neural Networkswhich result in a significant reduction of the calculation time. This modification of the CG algorithm was tested on selected examples. The performance of our method and the classic CG method was compared.

淺灘

fatty-acids