Social Science

    

An Introduction to the Relearning Cycle Index $i_{rel}$ and the Average Split Function $\bar{f}_{rel}$ of the Source Energy Exploitation by and for the Neural Networks.

Authors: Alexis Zaganidis

We define the relearning cycle index $i_{ReL}$ and the average split function $\bar{f}_{ReL}$ of the source energy exploitation by and for the neural networks. We propose an optimized learning strategy which depend on a fixed relearning cycle index $i_{ReL}$ and a fixed average split function $\bar{f}_{ReL}$. In practice, this theory may explain why the communist politics in Russia and in China faced strong difficulties at the 20th century and why the private companies politics in Western countries faced critical difficulties at the beginning of the 21th century. We conclude with some critical hints for the future relearning cycles of the source energy exploitation by and for the neural networks.

Comments: 3 Pages.

Download: PDF

Submission history

[v1] 2021-01-21 15:00:38
[v2] 2021-04-08 20:56:01

Unique-IP document downloads: 369 times

Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.

Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.

comments powered by Disqus