首页|Study Findings on Machine Learning Reported by a Researcher at South China Unive rsity of Technology (Application and Analysis of LSTM and GRU Models for Cryptoc urrency Return Prediction)
Study Findings on Machine Learning Reported by a Researcher at South China Unive rsity of Technology (Application and Analysis of LSTM and GRU Models for Cryptoc urrency Return Prediction)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in artificial intelligence. According to news originating from Guangzhou, People's Republic of China, by NewsRx correspondents, research stated, "Since the beginni ng of the 2010s, cryptocurrency has been gaining abundant attention and has beco me a worthy considered asset in individual investment portfolio arrangements." Our news journalists obtained a quote from the research from South China Univers ity of Technology: "In this way, research on its return prediction is needed to provide guidance for investors to realize their maximum interests. This research delves into the use of prominent machine learning methods for forecasting crypt ocurrency returns, with a particular emphasis on two advanced models: Long Short -Term Memory (LSTM) and Gated Recurrent Unit (GRU). By scrutinizing a range of a cademic studies, we identify the strengths and weaknesses of these models in ret urn prediction and offer a comparative analysis. Our findings reveal that the GR U model excels by achieving lower values in both Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE), highlighting its superior predictive accuracy. Meanwhile, LSTM presents plausible recAll rates, precision, accuracy, and lower cross-entropy losses."
South China University of TechnologyGu angzhouPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesInves tment and FinanceMachine Learning
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