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            <name>Title</name>
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                <text>Book Chapter</text>
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    <name>Book Chapter</name>
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          <name>Title</name>
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              <text>Predicting cryptocurrency prices model using a stacked sparse autoencoder and Bayesian optimization</text>
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          <name>Description</name>
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              <text>In recent years, digital currencies, also known as cybercash, digital money, and electronic money, have gained significant attention from researchers and investors alike. Cryptocurrency has emerged as a result of advancements in financial technology and has presented a unique opening for research in the field. However, predicting the prices of cryptocurrencies is a challenging task due to their dynamic and volatile nature. This study aims to address this challenge by introducing a new prediction model called Bayesian optimization with stacked sparse autoencoder-based cryptocurrency price prediction (BOSSAE-CPP). The main objective of this model is to effectively predict the prices of cryptocurrencies. To achieve this goal, the BOSSAE-CPP model employs a stacked sparse autoencoder (SSAE) for the prediction process and resulting in improved predictive outcomes. The results were compared to other models, and it was found that the BOSSAE-CPP model performed significantly better.  2023, IGI Global.</text>
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          <name>Creator</name>
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              <text>Baranidharan S.; Narayanan R.; Geetha V.</text>
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              <text>Revolutionizing Financial Services and Markets Through FinTech and Blockchain, pp. 60-77.</text>
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              <text>IGI Global</text>
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          <name>Date</name>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.4018/978-1-6684-8624-5.ch005" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/978-1-6684-8624-5.ch005&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168066754&amp;amp;doi=10.4018%2F978-1-6684-8624-5.ch005&amp;amp;partnerID=40&amp;amp;md5=43c51c753a15df029594b9e7cbd38ab5" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168066754&amp;amp;doi=10.4018%2f978-1-6684-8624-5.ch005&amp;amp;partnerID=40&amp;amp;md5=43c51c753a15df029594b9e7cbd38ab5&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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          <name>Relation</name>
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              <text>ISBN: 978-166848626-9; 1668486245; 978-166848624-5</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Baranidharan S., CHRIST University (Deemed), India; Narayanan R., Dayananda Sagar University, India; Geetha V., Seshadripuram Evening College, India</text>
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