Author:
Song Runze,Wang Zeyu,Guo Lingfeng,Zhao Fanyi,Xu Zeqiu
Abstract
Deep Belief Networks (DBNs) represent a transformative approach in financial time series analysis, addressing the complexities of market dynamics through advanced deep learning techniques. By leveraging hierarchical layers of unsupervised Restricted Boltzmann Machines (RBMs), DBNs excel in extracting intricate patterns from vast datasets, enabling accurate prediction of market trends and fluctuations. This capability not only enhances traditional financial analysis methods but also facilitates informed decision-making in dynamic and uncertain financial environments.
Publisher
Century Science Publishing Co
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