BLOCKCHAIN-BASED IoFLT FEDERATED LEARNING IN A FUZZY/GAN ENVIRONMENT FOR A SMART TRADING BOT

被引：1

作者：

Aguilera, Ricardo Carreno ^{[1
]}

Ortiz, Miguel Patino ^{[2
]}

Esteva, Veronica Aguilar ^{[1
]}

Bautista, Daniel Pacheco ^{[1
]}

机构：

[1] Univ Istmo, Campus Tehuantepec Ciudad Universitaria S-N Barrio, Oaxaca 70760, OAX, Mexico

[2] Inst Politecn Nacl Escuela Super Ingenieria Mecan, Ave Luis Enr Erro S-N Un Profesional Adolfo Lopez, Gustavo A Madero 07738, Mexico

来源：

FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY | 2023年 / 31卷 / 01期

关键词：

Blockchain; IoT Federated Learning (IoFLT); Generative Adversarial Network (GAN); SYSTEM;

D O I：

10.1142/S0218348X23500056

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

A DAPP is performed with collaborative training, where "Federated Learning " uses each device client to work as a singular artificial intelligence model using machine learning. The purpose is to reduce the latency by using computing resources from all client devices and increase privacy since personal data does not leave the client's devices. Applying machine learning massively in decentralized trading bots using blockchain seems to be a great solution. This learning solution can be improved using a fuzzy generative adversarial network environment to help the training. In this case, the expert system has a Python bot to interact with the Binance API to place buy/sell orders for the BTC-USD pair.

引用

页数：10

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