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Novel Financial Applications of Machine Learning and Deep Learning

Overview of attention for book
Cover of 'Novel Financial Applications of Machine Learning and Deep Learning'

Table of Contents

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    Book Overview
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    Chapter 1 FinTech Risk Management and Monitoring
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    Chapter 2 Digital Transformation of Supply Chain with Supportive Culture in Blockchain Environment
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    Chapter 3 Integration of Artificial Intelligence Technology in Management Accounting Information System: An Empirical Study
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    Chapter 4 The Impact of Big Data on Accounting Practices: Empirical Evidence from Africa
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    Chapter 5 Using Outlier Modification Rule for Improvement of the Performance of Classification Algorithms in the Case of Financial Data
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    Chapter 6 Default Risk Prediction Based on Support Vector Machine and Logit Support Vector Machine
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    Chapter 7 Predicting Corporate Failure Using Ensemble Extreme Learning Machine
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    Chapter 8 Assessing and Predicting Small Enterprises’ Credit Ratings: A Multicriteria Approach
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    Chapter 9 An Ensemble LGBM (Light Gradient Boosting Machine) Approach for Crude Oil Price Prediction
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    Chapter 10 Model Development for Predicting the Crude Oil Price: Comparative Evaluation of Ensemble and Machine Learning Methods
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    Chapter 11 Discovering the Role of M-Learning Among Finance Students: The Future of Online Education
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    Chapter 12 Exploring the Role of Mobile Technologies in Higher Education: The Impact of Online Teaching on Traditional Learning
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    Chapter 13 Knowledge Mining from Health Data: Application of Feature Selection Approaches
Attention for Chapter 2: Digital Transformation of Supply Chain with Supportive Culture in Blockchain Environment
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Citations

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Chapter title
Digital Transformation of Supply Chain with Supportive Culture in Blockchain Environment
Chapter number 2
Book title
Novel Financial Applications of Machine Learning and Deep Learning
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-18552-6_2
Book ISBNs
978-3-03-118551-9, 978-3-03-118552-6
Authors

Akter, Shakila, Haque, Mohammad Samiul, Sohag, Ashrafuzzaman, Siddikee, Md. Jahangir Alam, Abedin, Mohammad Zoynul

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 33%
Unknown 2 67%
Readers by discipline Count As %
Business, Management and Accounting 1 33%
Unknown 2 67%

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