))
The Future of Crypto Transactions? AI That Predicts Network Congestion
Manage episode 515253286 series 3474385
A tartalmat a HackerNoon biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a HackerNoon vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
This story was originally published on HackerNoon at: https://hackernoon.com/the-future-of-crypto-transactions-ai-that-predicts-network-congestion.
FENN uses deep learning to predict blockchain transaction fees by modeling mempool states, network speed, and transaction data.
Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #bitcoin-transaction-fees, #mempool-management, #fee-rate-analysis, #bitcoin-fee-estimation, #blockchain-ai, #mempool-analysis, #btcflow, #bitcoin-transaction-feerate, and more.
This story was written by: @blockchainize. Learn more about this writer by checking @blockchainize's about page, and for more stories, please visit hackernoon.com.
Blockchain transaction fees fluctuate due to limited block capacity and network congestion. The Fee Estimation based on Neural Network (FENN) framework tackles this challenge by combining three data sources—transaction features, mempool states, and network characteristics. Using deep learning methods like LSTM and attention mechanisms, FENN predicts future block behaviors and network trends to estimate optimal transaction fees. This dual-layer model—feature extraction and prediction—helps improve accuracy and efficiency in confirming blockchain transactions.
343 epizódok
Megosztás
