Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 12 hours.
Version: PDF/EPUB. If you need EPUB and MOBI Version, please contact us.
Compatible Devices: Can be read on any devices.
Bankruptcy Prediction through Soft Computing based Deep Learning Technique
This book proposes complex hierarchical deep architectures (HDA) for predicting bankruptcy, a topical issue for business and corporate institutions that in the past has been tackled using statistical, market-based and machine-intelligence prediction models. The HDA are formed through fuzzy rough tensor deep staking networks (FRTDSN) with structured, hierarchical rough Bayesian (HRB) models. FRTDSN is formalized through TDSN and fuzzy rough sets, and HRB is formed by incorporating probabilistic rough sets in structured hierarchical Bayesian model. Then FRTDSN is integrated with HRB to form the compound FRTDSN-HRB model. HRB enhances the prediction accuracy of FRTDSN-HRB model. The experimental datasets are adopted from Korean construction companies and American and European non-financial companies, and the research presented focuses on the impact of choice of cut-off points, sampling procedures and business cycle on the accuracy of bankruptcy prediction models. The book also highlights the fact that misclassification can result in erroneous predictions leading to prohibitive costs to investors and the economy, and shows that choice of cut-off point and sampling procedures affect rankings of various models. It also suggests that empirical cut-off points estimated from training samples result in the lowest misclassification costs for all the models. The book confirms that FRTDSN-HRB achieves superior performance compared to other statistical and soft-computing models. The experimental results are given in terms of several important statistical parameters revolving different business cycles and sub-cycles for the datasets considered and are of immense benefit to researchers working in this area.
This is a digital product.
Bankruptcy Prediction through Soft Computing based Deep Learning Technique is written by Arindam Chaudhuri; Soumya K Ghosh and published by Springer. The Digital and eTextbook ISBNs for Bankruptcy Prediction through Soft Computing based Deep Learning Technique are 9789811066832, 9811066833 and the print ISBNs are 9789811066825, 9811066825.

Gardner's Art through the Ages: A Global History, Volume I eBook
MGMT eBook
Advances in Data-driven Computing and Intelligent Systems: Selected Papers from ADCIS 2022, Volume 2 eBook
Healing Foods eBook
Molecular Gastronomy: Scientific Cuisine Demystified eBook
STAT2: Modeling with Regression and ANOVA eBook
Advances in Imaging and Electron Physics eBook
Fundamentals of Python: Data Structures, 2nd Edition eBook
Microsoft Office Excel 2007 Step by Step eBook
Mastering Risk and Procurement in Project Management eBook
Competition Law for the Digital Economy eBook
Murach's SQL Server 2016 for Developers eBook
ggplot2 eBook
The Good Gut eBook
PFIN eBook
Microsoft Office Publisher 2007 Step by Step eBook
New Perspectives Microsoft Office 365 & Access 2016: Comprehensive eBook
Rig it Right! Maya Animation Rigging Concepts, 2nd edition eBook
Excel 2007 eBook
Air Fryer Perfection eBook
Microsoft Office Excel 2007 Visual Basic for Applications Step by Step eBook
Piano for the Developing Musician, Media Update eBook
70-740 Installation, Storage, and Compute with Windows Server 2016 eBook
Handbook of Scheduling eBook
Word 2007 eBook
Elementary and Middle School Mathematics eBook
Data Abstraction & Problem Solving with C++: Walls and Mirrors, 7th Edition eBook
Cengage Advantage Books: The American Pageant, Volume 2: Since 1865 eBook
Bring Your Own Devices (BYOD) Survival Guide eBook
Visible Learning for Mathematics, Grades K-12: What Works Best to Optimize Student Learning eBook
Above the Fold, Revised Edition eBook
JMP Essentials eBook
She Has Her Mother's Laugh eBook
The Foundations of Mathematics eBook
Invitation to Public Speaking Handbook eBook
The Age of Surveillance Capitalism eBook
Transnational Management eBook
Businesss Intelligence and Analytics eBook
Interactive: Entrepreneurship: The Practice and Mindset Interactive eBook
Microsoft Office - Integration eBook
Smart Design: First International Conference Proceedings eBook
Access 2007 eBook
Microsoft Office Access 2007 Step by Step eBook
An Introduction to Stochastic Modeling, Student Solutions Manual (e-only) eBook
Governing Cross-Sector Collaboration, 1st Edition eBook
Practice Makes Perfect Mastering Writing eBook
The Complete Project Management Office Handbook eBook
The Discovery of the Tomb of Tutankhamen eBook
The Skew-Normal and Related Families eBook
Graph Theory with Applications to Engineering and Computer Science eBook
Using QuickBooks for Online for Accounting 2023, 6th Edition eBook
Validation of Score Meaning for the Next Generation of Assessments: The Use of Response Processes eBook
Powerpoint 2007 eBook
Cracking the AP Calculus AB Exam, 2019 Edition eBook
Network Security Essentials eBook
World Architecture: A Cross-Cultural History eBook
Information Technology for Management: On Demand Strategies for Performance, Growth and Sustainability, Enhanced eText eBook
Encyclopedia of Knot Theory eBook
Brown Trout: Biology, Ecology and Management eBook 


Reviews
There are no reviews yet.