چکیده مقاله
Cryptocurrency price prediction is a critical challenge in financial technology FinTech , with significant implications for eCommerce This study proposes a hybrid Temporal Convolutional Network TCN Transformer model to predict Ethereum prices, enhancing decision making in online transactions The model is trained on historical Ethereum price data and achieves high accuracy in forecasting future prices Its applications in eCommerce include risk management in cryptocurrency payment systems, optimized transaction timing, and intelligent customer support tools To validate its effectiveness, we simulate a real world eCommerce scenario where an online store leverages the model for cryptocurrency payments The results indicate that integrating AI driven price prediction can mitigate risks associated with price volatility and enhance business profitability This research contributes to the intersection of artificial intelligence and eCommerce by providing a practical framework for leveraging cryptocurrency forecasts in financial management and transaction optimization
کلیدواژهها
نویسندگان
Naser Abbasi
Islamic Azad University, Isfahan Khorasgan Branch
Zohreh Fotouhi
Islamic Azad University, Isfahan Khorasgan Branch
شیوه ارجاع
Abbasi, Naser and Fotouhi, Zohreh,1403,AI-Driven Cryptocurrency Price Prediction for Enhanced Decision-Making in E-Commerce,The 14th ECDC2025 international e-commerce conference with the approach of artificial intelligence, Internet of Things, business and metaverse,Shiraz
ارائهشده در
مجموعه مقالات چهاردهمین کنفرانس بین المللی تجارت الکترونیک ECDC۲۰۲۵ با رویکرد هوش مصنوعی، اینترنت اشیاء، کسب و کار و متاورس25 بهمن 1403 · شیراز