TY - JOUR
T1 - Blockchain-Based IoFLT Federated Learning In A Fuzzy/Gan Environment For A Smart Trading Bot
AU - Aguilera, Ricardo Carreño
AU - Ortiz, Miguel Patiño
AU - Esteva, Verónica Aguilar
AU - Bautista, Daniel Acheco
N1 - Publisher Copyright:
© 2023 The Author(s).
PY - 2023/3/1
Y1 - 2023/3/1
N2 - 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.
AB - 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.
KW - Blockchain
KW - Generative Adversarial Network (GAN)
KW - IoT Federated Learning (IoFLT)
UR - http://www.scopus.com/inward/record.url?scp=85145594427&partnerID=8YFLogxK
U2 - 10.1142/S0218348X23500056
DO - 10.1142/S0218348X23500056
M3 - Artículo
AN - SCOPUS:85145594427
SN - 0218-348X
VL - 31
JO - Fractals
JF - Fractals
IS - 1
M1 - 2350005
ER -