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Full Description
Future predictions are always a topic of interest. Precise estimates are crucial in many activities as forecasting errors can lead to big financial loss. The sequential analysis of data and information gathered from past to present is call time series analysis. This book covers the recent advancements in time series forecasting.
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.
Contents
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)
