Recent Advances in Time Series Forecasting (eBook, PDF)
Redaktion: Bisht, Dinesh C. S.; Ram, Mangey
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Recent Advances in Time Series Forecasting (eBook, PDF)
Redaktion: Bisht, Dinesh C. S.; Ram, Mangey
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Future predictions are always a topic of interest. Precise estimates are crucial in many activities as forecasting errors can lead to significant financial loss. The sequential analysis of data and information gathered from past to present is called time series analysis. This book covers the recent advancements in time series forecasting.
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Future predictions are always a topic of interest. Precise estimates are crucial in many activities as forecasting errors can lead to significant financial loss. The sequential analysis of data and information gathered from past to present is called time series analysis. This book covers the recent advancements in time series forecasting.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 238
- Erscheinungstermin: 7. September 2021
- Englisch
- ISBN-13: 9781000433821
- Artikelnr.: 62321907
- Verlag: Taylor & Francis
- Seitenzahl: 238
- Erscheinungstermin: 7. September 2021
- Englisch
- ISBN-13: 9781000433821
- Artikelnr.: 62321907
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Dr. Dinesh C. S. Bisht received his Ph.D. with a major in Mathematics and a minor in Electronics and Communication Engineering from G. B. Pant University of Agri. & Technology, Uttarakhand. Before joining the Jaypee Institute of Information Technology he worked as an assistant professor at ITM University, Gurgaon, India. He has been a Faculty Member for around eleven years and has taught several core courses in applied mathematics and Soft computing at undergraduate and master levels. The major research interests of him include Soft Computing and Nature Inspired optimization. He has published more than 35 research papers in national and international journals of repute. He is the Associate Editor for International Journal of Mathematical, Engineering and Management Sciences, ESCI and SCOPUS indexed journal. He is the editor of the book "Computational Intelligence: Theoretical Advances and Advanced Applications" published by Walter de Gruyter GmbH & Co KG. He has also published seven book chapters in the reputed book series. Dr. Bisht is a member of International Association of Engineers in Hong Kong and Soft Computing Research Society, India. He has been awarded for outstanding contribution in reviewing, from the editors of Applied Soft Computing Journal, Elsevier. Prof. Dr. Mangey Ram received the Ph.D. degree major in Mathematics and minor in Computer Science from G. B. Pant University of Agriculture and Technology, Pantnagar, India. He has been a Faculty Member for around twelve years and has taught several core courses in pure and applied mathematics at undergraduate, postgraduate, and doctorate levels. He is currently the Research Professor at Graphic Era (Deemed to be University), Dehradun, India. Before joining the Graphic Era, he was a Deputy Manager (Probationary Officer) with Syndicate Bank for a short period. He is Editor-in-Chief of International Journal of Mathematical, Engineering and Management Sciences, Journal of Reliability and Statistical Studies, Editor-in-Chief of six Book Series with Elsevier, CRC Press-A Taylor and Frances Group, Walter De Gruyter Publisher Germany, River Publisher and the Guest Editor & Member of the editorial board of various journals. He has published 225 plus research publications (journal articles/books/book chapters/conference articles) in IEEE, Taylor & Francis, Springer, Elsevier, Emerald, World Scientific and many other national and international journals and conferences. Also, he has published more than 50 books (authored/edited) with international publishers like Elsevier, Springer Nature, CRC Press-A Taylor and Frances Group, Walter De Gruyter Publisher Germany, River Publisher. His fields of research are reliability theory and applied mathematics. Dr. Ram is a Senior Member of the IEEE, Senior Life Member of Operational Research Society of India, Society for Reliability Engineering, Quality and Operations Management in India, Indian Society of Industrial and Applied Mathematics, He has been a member of the organizing committee of a number of international and national conferences, seminars, and workshops. He has been conferred with "Young Scientist Award" by the Uttarakhand State Council for Science and Technology, Dehradun, in 2009. He has been awarded the "Best Faculty Award" in 2011; "Research Excellence Award" in 2015; and recently "Outstanding Researcher Award" in 2018 for his significant contribution in academics and research at Graphic Era Deemed to be University, Dehradun, India.
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)
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)
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)
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)