Predictive Analytics (eBook, PDF)

Modeling and Optimization
Redaktion: Kumar, Vijay; Ram, Mangey

• Format: PDF

Produktbeschreibung

Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligences. This book provides the most recent advances in the field along with case studies and real-world examples.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 288
• Erscheinungstermin: 13. Januar 2021
• Englisch
• ISBN-13: 9781000332865
• Artikelnr.: 60682272

Inhaltsangabe

Chapter 1 Role of MCDM in Software Reliability Engineering Chapter 2 Fault
Tree Analysis of a Computerized Numerical Control Turning Center Chapter 3
How to Schedule Elective Patients in Hospitals to Gain Full Utilization of
Resources and Eliminate Patient Overcrowding Chapter 4 Reducing the
Deterioration Rate of Inventory through Preservation Technology Investment
under Fuzzy and Cloud Fuzzy Environment Chapter 5 Image Formation Using
Deep Convolutional Generative Adversarial Networks Chapter 6 Optimal
Preservation Technology Investment and Price for the Deteriorating
Inventory Model with Price-Sensitivity Stock- Dependent Demand Chapter 7
EOQ with Shortages and Learning Effect Chapter 8 Optimal
Production-Inventory Policies for Processed Fruit Juices Manufacturer and
Multi-retailers with Trended Demand and Quality Degradation Chapter 9
Information Visualization: Perception and Limitations for Data-Driven
Designs Chapter 10 IoT, Big Data, and Analytics - Challenges and
Opportunities Chapter 11 Multiple-Criteria Decision Analysis Using VLSI
Global Routing Chapter 12 Application of IoT in Water Supply Management
Chapter 13 A Hybrid Approach for Video Indexing Using Computer Vision and
Speech Recognition Chapter 14 Statistical Methodology for Software
Reliability with Environmental Factors Chapter 15 Maintenance Data-Trends
Based Reliability Availability and Maintainability (RAM) Assessment of a
Steam Boiler