Titlebook: Artificial Intelligence and Soft Computing; 20th International C Leszek Rutkowski,Rafał Scherer,Jacek M. Zurada Conference proceedings 2021

Hazardous

书目名称Artificial Intelligence and Soft Computing影响因子(影响力)




书目名称Artificial Intelligence and Soft Computing影响因子(影响力)学科排名




书目名称Artificial Intelligence and Soft Computing网络公开度




书目名称Artificial Intelligence and Soft Computing网络公开度学科排名




书目名称Artificial Intelligence and Soft Computing被引频次




书目名称Artificial Intelligence and Soft Computing被引频次学科排名




书目名称Artificial Intelligence and Soft Computing年度引用




书目名称Artificial Intelligence and Soft Computing年度引用学科排名




书目名称Artificial Intelligence and Soft Computing读者反馈




书目名称Artificial Intelligence and Soft Computing读者反馈学科排名

Foam-Cells

Modification of Learning Feedforward Neural Networks with the BP Methodethod converges relatively slowly. In this paper a new approach to the backpropagation algorithm is presented. The proposed solution speeds up the BP method by using vector calculations. This modification of the BP algorithm was tested on a few standard examples. The obtained performance of both methods was compared.

发酵剂

https://doi.org/10.1007/978-3-030-87986-0artificial intelligence; classification; computer networks; computer science; computer systems; computer

Mettle

懒洋洋

Spirometry

Consensus

Durchleuchtung und Subtraktionsangiographieethod converges relatively slowly. In this paper a new approach to the backpropagation algorithm is presented. The proposed solution speeds up the BP method by using vector calculations. This modification of the BP algorithm was tested on a few standard examples. The obtained performance of both methods was compared.

组成

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162313.jpg

小口啜饮

Empirische und theoretische Ausgangspunkte,a (e.g.: investors required return, risk tolerance, goals, and time frame). The objective of this research is to present a two phase deep learning module to csonstruct a financial stocks portfolio that can be used repeatedly to select the most promising stocks and adjust stocks allocations (namely q

neolith

Methodologie und Design des Gesamtprojekts,ology of the Factor Augmented Artificial Neural Network Model is applied to improve the predictive capacity of liquidity models compared to traditional econometric methodologies. This hybrid methodology based on dynamic factor models and neural networks is compared with Deep Learning methodologies s