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1. |
Record Nr. |
UNINA9910150332503321 |
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Titolo |
Supply chain management in the big data era / / Hing Kai Chan, Nachiappan Subramanian, Muhammad Dan-Asabe Abdulrahman, editors |
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Pubbl/distr/stampa |
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Hershey, Pennsylvania : , : IGI Global, , 2017 |
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©2017 |
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ISBN |
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9781522509578 |
9781522509561 |
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Descrizione fisica |
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PDFs (298 pages) : illustrations |
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Collana |
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Advances in Logistics, Operations, and Management Science (ALOMS) Book Series, , 2327-3518 |
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Disciplina |
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Soggetti |
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Business logistics - Management |
Business logistics - Data processing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Big data analytics: academic perspectives / Muhammad D. Abdulrahman [and 3 others] -- Big data analytics: service and manufacturing industries perspectives / Nachiappan Subramanian [and 3 others] -- How smart operations help better planning and replenishment?: empirical study - supply chain collaboration for smart operations / Usha Ramanathan -- Big data analytics for predictive maintenance strategies / C. K. M. Lee, Yi Cao, Kam Hung Ng -- Data-driven inventory management in the healthcare supply chain / Shuojiang Xu, Kim Hua Tan -- Role of operations strategy and big data: a study of transport company / Arvind Upadhyay [and 3 others] -- Big data and RFID in supply chain and logistics management: a review of the literature and applications for data driven research / Thanos Papadopoulos [and 3 others] -- Developing an integration framework for crowdsourcing and internet of things with applications for disaster response / Rameshwar Dubey -- Supply chain coordination based on web service / Kamalendu Pal -- Exploring the hidden pattern from tweets: investigation into Volkswagen emissions scandal / Ying Kei Tse [and 4 others] -- Swift Guanxi data analysis and its application to e-commerce retail strategies improvement / Ewelina Lacka -- Applying |
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big data with fuzzy DEMATEL to discover the critical factors for employee engagement in developing sustainability for the hospitality industry under uncertainty / Kuo-Jui Wu [and 4 others]. |
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Sommario/riassunto |
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"This book is an authoritative reference source for the latest scholarly material on the implementation of big data analytics for improved operations and supply chain processes, highlighting emerging strategies from different industry perspectives"--Provided by publisher. |
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2. |
Record Nr. |
UNINA9910794380803321 |
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Autore |
Marston Daniel |
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Titolo |
Autism and independence : assessments and interventions to prepare teens for adult life / / Daniel Marston, PhD, ABPP |
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Pubbl/distr/stampa |
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Eau Claire, WI : , : PESI Publishing & Media, , [2019] |
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©2019 |
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ISBN |
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Descrizione fisica |
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1 online resource (206 pages) |
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Disciplina |
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Soggetti |
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Autistic youth - Behavior modification |
Autistic youth - Conduct of life |
Autistic youth |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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3. |
Record Nr. |
UNINA9910632470503321 |
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Autore |
Wüthrich Mario V. |
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Titolo |
Statistical Foundations of Actuarial Learning and its Applications / / by Mario V. Wüthrich, Michael Merz |
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Pubbl/distr/stampa |
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Cham, : Springer Nature, 2023 |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (XII, 605 p. 1 illus.) |
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Collana |
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Springer Actuarial, , 2523-3270 |
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Classificazione |
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BUS061000COM004000COM031000MAT003000 |
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Disciplina |
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Soggetti |
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Actuarial science |
Statistics |
Machine learning |
Artificial intelligence—Data processing |
Social sciences—Mathematics |
Actuarial Mathematics |
Statistics in Business, Management, Economics, Finance, Insurance |
Machine Learning |
Data Science |
Mathematics in Business, Economics and Finance |
Assegurances |
Estadística |
Llibres electrònics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be |
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weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus. |
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