Intelligent optimization techniques for business analytics:
"Today, the convergence of cutting-edge algorithms and actionable insights in business is paramount for success. Scholars and practitioners grapple with the dilemma of optimizing data to drive efficiency, innovation, and competitiveness. The formidable challenge of effectively harnessing the im...
Gespeichert in:
| Weitere Verfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :
IGI Global,
c2024
|
| Schriftenreihe: | Advances in business information systems and analytics (ABISA) book series.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "Today, the convergence of cutting-edge algorithms and actionable insights in business is paramount for success. Scholars and practitioners grapple with the dilemma of optimizing data to drive efficiency, innovation, and competitiveness. The formidable challenge of effectively harnessing the immense power of intelligent optimization techniques and business analytics only increases as the volume of data grows exponentially, and the complexities of navigating the intricate landscape of business analytics becomes more daunting. This pressing issue underscores the critical need for a comprehensive solution, and Intelligent Optimization Techniques for Business Analytics is poised to provide much-needed answers.This groundbreaking book offers an all-encompassing solution to the challenges that academic scholars encounter in the pursuit of mastering the interplay between learning algorithms and intelligent optimization techniques for business analytics. Through a wealth of diverse perspectives and expert case studies, it illuminates the path to effectively implementing these advanced systems in real-world business scenarios. It caters not only to the scholarly community but also to industry professionals and policymakers, equipping them with the necessary tools and insights to excel in the realm of data-driven decision-making."-- |
| Beschreibung: | 20 PDFs (xx, 357 pages) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9798369315996 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
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| 245 | 0 | 0 | |a Intelligent optimization techniques for business analytics |c Sanjeev Bansal, Nitendra Kumar, Priyanka Agarwal, editors. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : |b IGI Global, |c c2024 | |
| 300 | |a 20 PDFs (xx, 357 pages) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 490 | 1 | |a Advances in business information systems and analytics (ABISA) book series | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Preface -- Chapter 1. Introduction to Intelligent Optimization Techniques in Business Analytics -- Chapter 2. Foundations of Machine Learning -- Chapter 3. Future Directions in the Application of Machine Learning and Intelligent Optimization in Business Analytics -- Chapter 4. Deciphering the Realities of Deep Learning in Business Analytics: A Bibliometric Analysis -- Chapter 5. Exploring the Impact of Deep Learning and Neural Networks on Business Analytics -- Chapter 6. AI-Driven Financial Forecasting: The Power of Soft Computing -- Chapter 7. An Analysis of Stock Price Prediction Techniques -- Chapter 8. Credit Card Fraud Detection and Analysis With the Blend of Machine Learning and Blockchain -- Chapter 9. Genetic Crossover Operator in Local Search of the Assembly Line Balancing Problem -- Chapter 10. Optimizing Customer Service With Chatbots -- Chapter 11. Tackling Customer Wait Times: Advanced Techniques for Call Centre Optimization -- Chapter 12. Fuzzy Logic Modelling-Based Measurement Approach for Mental Stress Measurement -- Chapter 13. Deep Learning, Neural Networks, and Their Applications in Business Analytics -- Compilation of References -- About the Contributors -- Index. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "Today, the convergence of cutting-edge algorithms and actionable insights in business is paramount for success. Scholars and practitioners grapple with the dilemma of optimizing data to drive efficiency, innovation, and competitiveness. The formidable challenge of effectively harnessing the immense power of intelligent optimization techniques and business analytics only increases as the volume of data grows exponentially, and the complexities of navigating the intricate landscape of business analytics becomes more daunting. This pressing issue underscores the critical need for a comprehensive solution, and Intelligent Optimization Techniques for Business Analytics is poised to provide much-needed answers.This groundbreaking book offers an all-encompassing solution to the challenges that academic scholars encounter in the pursuit of mastering the interplay between learning algorithms and intelligent optimization techniques for business analytics. Through a wealth of diverse perspectives and expert case studies, it illuminates the path to effectively implementing these advanced systems in real-world business scenarios. It caters not only to the scholarly community but also to industry professionals and policymakers, equipping them with the necessary tools and insights to excel in the realm of data-driven decision-making."-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 04/30/2024). | ||
| 650 | 0 | |a Business |x Data processing. | |
| 650 | 0 | |a Business |x Technological innovations. | |
| 650 | 0 | |a Mathematical optimization. | |
| 653 | |a Business Data Analytics. | ||
| 653 | |a Cutting-Edge Algorithms. | ||
| 653 | |a Data-Driven Decision-Making. | ||
| 653 | |a Efficiency-Driving Data Optimization. | ||
| 653 | |a Ethical Considerations. | ||
| 653 | |a Learning Algorithms. | ||
| 653 | |a Real-World Business Scenarios. | ||
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Agarwal, Priyanka, |e editor. | |
| 700 | 1 | |a Bansal, Sanjeev |d 1967- |e editor. | |
| 700 | 1 | |a Kumar, Nitendra |d 1989- |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 9798369315989 |
| 830 | 0 | |a Advances in business information systems and analytics (ABISA) book series. | |
| 856 | 4 | 0 | |l FWS01 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1598-9 |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-98-IGB-00329201 |
|---|---|
| _version_ | 1816797087873892352 |
| adam_text | |
| any_adam_object | |
| author2 | Agarwal, Priyanka Bansal, Sanjeev 1967- Kumar, Nitendra 1989- |
| author2_role | edt edt edt |
| author2_variant | p a pa s b sb n k nk |
| author_facet | Agarwal, Priyanka Bansal, Sanjeev 1967- Kumar, Nitendra 1989- |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | H - Social Science |
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| callnumber-raw | HD45 .I686 2024e |
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| contents | Preface -- Chapter 1. Introduction to Intelligent Optimization Techniques in Business Analytics -- Chapter 2. Foundations of Machine Learning -- Chapter 3. Future Directions in the Application of Machine Learning and Intelligent Optimization in Business Analytics -- Chapter 4. Deciphering the Realities of Deep Learning in Business Analytics: A Bibliometric Analysis -- Chapter 5. Exploring the Impact of Deep Learning and Neural Networks on Business Analytics -- Chapter 6. AI-Driven Financial Forecasting: The Power of Soft Computing -- Chapter 7. An Analysis of Stock Price Prediction Techniques -- Chapter 8. Credit Card Fraud Detection and Analysis With the Blend of Machine Learning and Blockchain -- Chapter 9. Genetic Crossover Operator in Local Search of the Assembly Line Balancing Problem -- Chapter 10. Optimizing Customer Service With Chatbots -- Chapter 11. Tackling Customer Wait Times: Advanced Techniques for Call Centre Optimization -- Chapter 12. Fuzzy Logic Modelling-Based Measurement Approach for Mental Stress Measurement -- Chapter 13. Deep Learning, Neural Networks, and Their Applications in Business Analytics -- Compilation of References -- About the Contributors -- Index. |
| ctrlnum | (CaBNVSL)slc00005838 (OCoLC)1432335683 |
| dewey-full | 658.4063 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.4063 |
| dewey-search | 658.4063 |
| dewey-sort | 3658.4063 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-98-IGB-00329201 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:52:00Z |
| institution | BVB |
| isbn | 9798369315996 |
| language | English |
| oclc_num | 1432335683 |
| open_access_boolean | |
| owner | DE-863 DE-BY-FWS |
| owner_facet | DE-863 DE-BY-FWS |
| physical | 20 PDFs (xx, 357 pages) Also available in print. |
| psigel | ZDB-98-IGB |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | IGI Global, |
| record_format | marc |
| series | Advances in business information systems and analytics (ABISA) book series. |
| series2 | Advances in business information systems and analytics (ABISA) book series |
| spelling | Intelligent optimization techniques for business analytics Sanjeev Bansal, Nitendra Kumar, Priyanka Agarwal, editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, c2024 20 PDFs (xx, 357 pages) text rdacontent electronic isbdmedia online resource rdacarrier Advances in business information systems and analytics (ABISA) book series Includes bibliographical references and index. Preface -- Chapter 1. Introduction to Intelligent Optimization Techniques in Business Analytics -- Chapter 2. Foundations of Machine Learning -- Chapter 3. Future Directions in the Application of Machine Learning and Intelligent Optimization in Business Analytics -- Chapter 4. Deciphering the Realities of Deep Learning in Business Analytics: A Bibliometric Analysis -- Chapter 5. Exploring the Impact of Deep Learning and Neural Networks on Business Analytics -- Chapter 6. AI-Driven Financial Forecasting: The Power of Soft Computing -- Chapter 7. An Analysis of Stock Price Prediction Techniques -- Chapter 8. Credit Card Fraud Detection and Analysis With the Blend of Machine Learning and Blockchain -- Chapter 9. Genetic Crossover Operator in Local Search of the Assembly Line Balancing Problem -- Chapter 10. Optimizing Customer Service With Chatbots -- Chapter 11. Tackling Customer Wait Times: Advanced Techniques for Call Centre Optimization -- Chapter 12. Fuzzy Logic Modelling-Based Measurement Approach for Mental Stress Measurement -- Chapter 13. Deep Learning, Neural Networks, and Their Applications in Business Analytics -- Compilation of References -- About the Contributors -- Index. Restricted to subscribers or individual electronic text purchasers. "Today, the convergence of cutting-edge algorithms and actionable insights in business is paramount for success. Scholars and practitioners grapple with the dilemma of optimizing data to drive efficiency, innovation, and competitiveness. The formidable challenge of effectively harnessing the immense power of intelligent optimization techniques and business analytics only increases as the volume of data grows exponentially, and the complexities of navigating the intricate landscape of business analytics becomes more daunting. This pressing issue underscores the critical need for a comprehensive solution, and Intelligent Optimization Techniques for Business Analytics is poised to provide much-needed answers.This groundbreaking book offers an all-encompassing solution to the challenges that academic scholars encounter in the pursuit of mastering the interplay between learning algorithms and intelligent optimization techniques for business analytics. Through a wealth of diverse perspectives and expert case studies, it illuminates the path to effectively implementing these advanced systems in real-world business scenarios. It caters not only to the scholarly community but also to industry professionals and policymakers, equipping them with the necessary tools and insights to excel in the realm of data-driven decision-making."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 04/30/2024). Business Data processing. Business Technological innovations. Mathematical optimization. Business Data Analytics. Cutting-Edge Algorithms. Data-Driven Decision-Making. Efficiency-Driving Data Optimization. Ethical Considerations. Learning Algorithms. Real-World Business Scenarios. Electronic books. Agarwal, Priyanka, editor. Bansal, Sanjeev 1967- editor. Kumar, Nitendra 1989- editor. IGI Global, publisher. Print version: 9798369315989 Advances in business information systems and analytics (ABISA) book series. FWS01 ZDB-98-IGB FWS_PDA_IGB http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1598-9 Volltext |
| spellingShingle | Intelligent optimization techniques for business analytics Advances in business information systems and analytics (ABISA) book series. Preface -- Chapter 1. Introduction to Intelligent Optimization Techniques in Business Analytics -- Chapter 2. Foundations of Machine Learning -- Chapter 3. Future Directions in the Application of Machine Learning and Intelligent Optimization in Business Analytics -- Chapter 4. Deciphering the Realities of Deep Learning in Business Analytics: A Bibliometric Analysis -- Chapter 5. Exploring the Impact of Deep Learning and Neural Networks on Business Analytics -- Chapter 6. AI-Driven Financial Forecasting: The Power of Soft Computing -- Chapter 7. An Analysis of Stock Price Prediction Techniques -- Chapter 8. Credit Card Fraud Detection and Analysis With the Blend of Machine Learning and Blockchain -- Chapter 9. Genetic Crossover Operator in Local Search of the Assembly Line Balancing Problem -- Chapter 10. Optimizing Customer Service With Chatbots -- Chapter 11. Tackling Customer Wait Times: Advanced Techniques for Call Centre Optimization -- Chapter 12. Fuzzy Logic Modelling-Based Measurement Approach for Mental Stress Measurement -- Chapter 13. Deep Learning, Neural Networks, and Their Applications in Business Analytics -- Compilation of References -- About the Contributors -- Index. Business Data processing. Business Technological innovations. Mathematical optimization. |
| title | Intelligent optimization techniques for business analytics |
| title_auth | Intelligent optimization techniques for business analytics |
| title_exact_search | Intelligent optimization techniques for business analytics |
| title_full | Intelligent optimization techniques for business analytics Sanjeev Bansal, Nitendra Kumar, Priyanka Agarwal, editors. |
| title_fullStr | Intelligent optimization techniques for business analytics Sanjeev Bansal, Nitendra Kumar, Priyanka Agarwal, editors. |
| title_full_unstemmed | Intelligent optimization techniques for business analytics Sanjeev Bansal, Nitendra Kumar, Priyanka Agarwal, editors. |
| title_short | Intelligent optimization techniques for business analytics |
| title_sort | intelligent optimization techniques for business analytics |
| topic | Business Data processing. Business Technological innovations. Mathematical optimization. |
| topic_facet | Business Data processing. Business Technological innovations. Mathematical optimization. Electronic books. |
| url | http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1598-9 |
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