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Deep Learning and Other Soft Computing Techniques: Biomedical and Related Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Bankruptcy Prediction through Soft Computing based Deep Learning Technique
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Bankruptcy Prediction Through Soft Computing Based Deep Learning Technique
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Bankruptcy Prediction Through Soft Computing Based Deep Learning Technique
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Bankruptcy Prediction Through Soft Computing Based Deep Learning Technique
Published by Springer Nature Singapore, 2017
ISBN 10: 9811066825 ISBN 13: 9789811066825
Language: English
US$ 65.89
Convert currencyUS$ 32.59 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 bookalso 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.
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Bankruptcy Prediction Through Soft Computing Based Deep Learning Technique
Published by Springer-Verlag New York Inc, 2017
ISBN 10: 9811066825 ISBN 13: 9789811066825
Language: English
US$ 87.24
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Add to basketPaperback. Condition: Brand New. 102 pages. 9.00x6.00x0.25 inches. In Stock.
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Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience
Published by Springer Nature Singapore, 2022
ISBN 10: 981166837X ISBN 13: 9789811668371
Language: English
US$ 120.04
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Add to basketCondition: Sehr gut. Zustand: Sehr gut - Gepflegter, sauberer Zustand. | Seiten: 152 | Sprache: Englisch | Produktart: Bücher.
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Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience
Published by Springer Nature Singapore, 2022
ISBN 10: 981166837X ISBN 13: 9789811668371
Language: English
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Add to basketCondition: Hervorragend. Zustand: Hervorragend | Seiten: 152 | Sprache: Englisch | Produktart: Bücher.
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Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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US$ 189.84
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Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Deep Learning and Other Soft Computing Techniques
Published by Springer, Berlin|Springer Nature Switzerland|Springer, 2023
ISBN 10: 3031294467 ISBN 13: 9783031294464
Language: English
US$ 167.60
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Deep Learning and Other Soft Computing Techniques (Hardcover)
Published by Springer International Publishing AG, Cham, 2023
ISBN 10: 3031294467 ISBN 13: 9783031294464
Language: English
Hardcover. Condition: new. Hardcover. This book focuses on the use of artificial intelligence (AI) and computational intelligence (CI) in medical and related applications. Applications include all aspects of medicine: from diagnostics (including analysis of medical images and medical data) to therapeutics (including drug design and radiotherapy) to epidemic- and pandemic-related public health policies.Corresponding techniques include machine learning (especially deep learning), techniques for processing expert knowledge (e.g., fuzzy techniques), and advanced techniques of applied mathematics (such as innovative probabilistic and graph-based techniques).The book also shows that these techniques can be used in many other applications areas, such as finance, transportation, physics. This book helps practitioners and researchers to learn more about AI and CI methods and their biomedical (and related) applicationsand to further develop thisimportant research direction. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Deep Learning and Other Soft Computing Techniques : Biomedical and Related Applications
Published by Springer Nature Switzerland, 2024
ISBN 10: 3031294491 ISBN 13: 9783031294495
Language: English
US$ 197.95
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on the use of artificial intelligence (AI) and computationalintelligence (CI) in medical and related applications. Applications includeall aspects of medicine: from diagnostics (including analysis of medicalimages and medical data) to therapeutics (including drug designand radiotherapy) to epidemic- and pandemic-related public health policies.Corresponding techniques include machine learning (especially deep learning),techniques for processing expert knowledge (e.g., fuzzy techniques), andadvanced techniques of applied mathematics (such as innovative probabilisticand graph-based techniques).The book also shows that these techniques can be used in many otherapplications areas, such as finance, transportation, physics. This book helps practitioners and researchers to learn more about AI andCI methods and their biomedical (and related) applications-and to furtherdevelop thisimportant research direction.
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Deep Learning and Other Soft Computing Techniques : Biomedical and Related Applications
Published by Springer Nature Switzerland, 2023
ISBN 10: 3031294467 ISBN 13: 9783031294464
Language: English
US$ 197.95
Convert currencyUS$ 35.23 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on the use of artificial intelligence (AI) and computationalintelligence (CI) in medical and related applications. Applications includeall aspects of medicine: from diagnostics (including analysis of medicalimages and medical data) to therapeutics (including drug designand radiotherapy) to epidemic- and pandemic-related public health policies.Corresponding techniques include machine learning (especially deep learning),techniques for processing expert knowledge (e.g., fuzzy techniques), andadvanced techniques of applied mathematics (such as innovative probabilisticand graph-based techniques).The book also shows that these techniques can be used in many otherapplications areas, such as finance, transportation, physics. This book helps practitioners and researchers to learn more about AI andCI methods and their biomedical (and related) applications-and to furtherdevelop thisimportant research direction.
-
Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience
Published by Springer Nature Singapore, Springer Nature Singapore, 2022
ISBN 10: 981166837X ISBN 13: 9789811668371
Language: English
US$ 200.62
Convert currencyUS$ 32.78 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book summarizes the application of soft computing techniques, machine learning approaches, deep learning algorithms and optimization techniques in geoengineering including tunnelling, excavation, pipelines, etc. and geoscience including the geohazards, rock and soil properties, etc. The book features state-of-the-art studies on use of SC,ML,DL and optimizations in Geoengineering and Geoscience.Considering these points and understanding, this book will be compiled with highly focussed chapters that will discuss the application of SC,ML,DL and optimizations in Geoengineering and Geoscience.Target audience: (1) Students of UG, PG, and Research Scholars: Several applications of SC,ML,DL and optimizations in Geoengineering and Geoscience can help students to enhance their knowledge in this domain. (2) Industry Personnel and Practitioner: Practitioners from different fields can be able to implement standard and advanced SC,ML,DL and optimizations for solvingcritical problems of civil engineering.
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Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience
Published by Springer Nature Singapore, Springer Nature Singapore, 2021
ISBN 10: 9811668345 ISBN 13: 9789811668340
Language: English
US$ 200.62
Convert currencyUS$ 33.68 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book summarizes the application of soft computing techniques, machine learning approaches, deep learning algorithms and optimization techniques in geoengineering including tunnelling, excavation, pipelines, etc. and geoscience including the geohazards, rock and soil properties, etc. The book features state-of-the-art studies on use of SC,ML,DL and optimizations in Geoengineering and Geoscience.Considering these points and understanding, this book will be compiled with highly focussed chapters that will discuss the application of SC,ML,DL and optimizations in Geoengineering and Geoscience.Target audience: (1) Students of UG, PG, and Research Scholars: Several applications of SC,ML,DL and optimizations in Geoengineering and Geoscience can help students to enhance their knowledge in this domain. (2) Industry Personnel and Practitioner: Practitioners from different fields can be able to implement standard and advanced SC,ML,DL and optimizations for solvingcritical problems of civil engineering.
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US$ 280.73
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Add to basketPaperback. Condition: Brand New. 152 pages. 9.25x6.10x0.47 inches. In Stock.
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US$ 283.72
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Add to basketHardcover. Condition: Brand New. 300 pages. 9.25x6.10x0.71 inches. In Stock.
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Proceedings of the 15th International Conference on Soft Computing and Pattern Recognition - Socpar 2023: Deep Learning and Large Language Models: Vol 2
Published by Springer-Nature New York Inc, 2025
ISBN 10: 3031810821 ISBN 13: 9783031810824
Language: English
US$ 396.21
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Add to basketPaperback. Condition: Brand New. 9.26x6.11 inches. In Stock.
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Proceedings of the 15th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2023) : Volume 2: Deep Learning and Large Language Models
Published by Springer, Berlin, Springer Nature Switzerland, Springer, 2025
ISBN 10: 3031810821 ISBN 13: 9783031810824
Language: English
US$ 369.66
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Add to basketTaschenbuch. Condition: Neu. Neuware - This book presents 55 selected papers focused on Deep Learning and Large Language Models from the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2023) and 14th World Congress on Nature and Biologically Inspired Computing (NaBIC 2023). SoCPaR - NaBIC 2023 was held in 5 different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India and in online mode. The conference had contributions by authors from 39 countries. This Volume offers a valuable reference guide for all scientists, academicians, researchers, students and practitioners focused on advanced machine learning including deep learning methods, large language models and its real-world applications.
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Bankruptcy Prediction Through Soft Computing Based Deep Learning Technique
Published by SPRINGER NATURE Dez 2017, 2017
ISBN 10: 9811066825 ISBN 13: 9789811066825
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
US$ 61.85
Convert currencyUS$ 25.82 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 102 pp. Englisch.
