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AI and Analytics for Public Health: Proceedings of the 2020 Informs International Conference on Service Science

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AI and Analytics for Public Health: Proceedings of the 2020 Informs International Conference on Service Science AI and Analytics for Public Health: Proceedings of the 2020 Informs International Conference on Service Science

出版社:Springer
出版日期:2023-01-06
語言:英文   規格:平裝 / 477頁 / 普通級/ 初版
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圖書名稱:AI and Analytics for Public Health: Proceedings of the 2020 Informs International Conference on Service Science

內容簡介

Chapter 1. Private vs. Pooled Transportation: Customer Preference and Congestion Management.- Chapter 2. Optimal Dispatch in Emergency Service System via Reinforcement Learning.- Chapter 3. Towards Understanding the Dynamics of COVID-19: An Approach based on Polynomial Regression with Adaptive Sliding Windows.- Chapter 4. Capturing the Deep Trend of Stock Market for a Big Profit.- Chapter 5. Analysis on Competitiveness of Service Outsourcing Industry in Yangtze River Delta Region.- Chapter 6. OPBFT: Optimized Practical Byzantine Fault Tolerant Consensus Mechanism Model.- Chapter 7. Entropy Weight-TOPSIS Method Considered Text Information with An Application in E-commerce.- Chapter 8. Optimal Resource Allocation for Coverage Control of City Crimes.- Chapter 9. Application of Internet of Things (IoT) in Inventory Management for Perishable Produce.- Chapter 10. Enabling Smart Buildings with Reinforcement Learning Controllers to Reduce Energy Consumption.- Chapter 11. Modified Risk Parity Portfoliosto Limit Concentration on Low Risk Assets in Multi-Asset Portfolios.- Chapter 12. A Data Analysis Method for Estimating Balking Behavior in Bike-Sharing Systems.- Chapter 13. The Impact of Scalability on Advisory and Service Delivery Efforts of Nonprofits.- Chapter 14. Green Location-Routing Problem with Delivery Options.- Chapter 15. Molecular Bioactivity Prediction of HDAC1 Based on Deep Neural Nets.- Chapter 16. Risk assessment indicators for technology enterprises: From the perspective of complex networks.- Chapter 17. Risk assessment indicators for technology enterprises: From the perspective of complex networks.- Chapter 18. Early Detection of Rumors Based on BERT Model.

 

作者簡介

Hui Yang is a Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University, University Park, PA. Dr. Yang’s research interests focus on sensor-based modeling and analysis of complex systems for process monitoring, process control, system diagnostics, condition prognostics, quality improvement, and performance optimization.

Robin Qiu is Professor at Pennsylvania State University, USA. Dr. Qiu’s research interests include Big Data, Data/Business Analytics, Smart Service Systems, Service Science, Service Operations and Management, Information Systems, and Manufacturing and Supply Chain Management.

Weiwei Chen is an Associate Professor at Rutgers University, USA. His research interests lie in operations and finance interface, as well as supply chain operations planning and scheduling. He also works on simulation and randomized global optimization methodologies.

 

詳細資料

  • ISBN:9783030751685
  • 規格:平裝 / 477頁 / 普通級 / 初版
  • 出版地:美國
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