Buch, Englisch, 238 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 529 g
Reihe: Mathematical Engineering, Manufacturing, and Management Sciences
Buch, Englisch, 238 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 529 g
Reihe: Mathematical Engineering, Manufacturing, and Management Sciences
ISBN: 978-0-367-60775-3
Verlag: CRC Press
The book includes theoretical as well as recent applications of time series analysis. It focuses on the recent techniques used, discusses a combination of methodology and applications, presents traditional and advanced tools, new applications, and identifies the gaps in knowledge in engineering applications.
This book is aimed at scientists, researchers, postgraduate students and engineers in the areas of supply chain management, production, inventory planning, and statistical quality control.
Zielgruppe
Academic, Professional, and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
- Mathematik | Informatik Mathematik Stochastik
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Technische Wissenschaften Technik Allgemein Industrial Engineering
- Mathematik | Informatik Mathematik Operations Research
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie
- Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Einkauf, Logistik, Supply-Chain-Management
Weitere Infos & Material
Chapter 1.Time Series Econometrics: Some Initial Understanding
Chapter 2.Time Series Analysis for Modeling the Transmission of Dengue Disease
Chapter 3.Time-Series Analysis of COVID-19 Confirmed Cases in Select Countries
Chapter 4.Bayesian Estimation of Bonferroni Curve And Zenga Curve in Case of Dagum Distribution
Chapter 5.Band Pass Filters and their Applications in Time Series Analyses
Chapter 6.Deep learning approaches to time-series forecasting
Chapter 7.ARFIMA and ARTFIMA Processes in Time Series with Applications
Chapter 8.Comparative Study of Time series Forecasting Models for COVID-19 Cases in India
Chapter 9.Time Series Forecasting Using Support Vector Machines
Chapter 10.A Comprehensive Review on Urban Floods and it's Modeling Techniques
Chapter 11.Fuzzy Time Series Techniques for Forecasting
Chapter 12.(Artificial Neural Networks (ANNs) and their Application in Soil and Water Resources Engineering)