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The Evaluation of Forecast Accuracy of a Non Statistical Method of Forecasting

The Evaluation of Forecast Accuracy of a Non Statistical Method of Forecasting PDF Author: Chee Choong Foong
Publisher:
ISBN: 9780867469578
Category : Business forecasting
Languages : en
Pages : 8

Book Description


The Evaluation of Forecast Accuracy of a Non Statistical Method of Forecasting

The Evaluation of Forecast Accuracy of a Non Statistical Method of Forecasting PDF Author: Chee Choong Foong
Publisher:
ISBN: 9780867469578
Category : Business forecasting
Languages : en
Pages : 8

Book Description


Forecasting: principles and practice

Forecasting: principles and practice PDF Author: Rob J Hyndman
Publisher: OTexts
ISBN: 0987507117
Category : Business & Economics
Languages : en
Pages : 380

Book Description
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Principles of Forecasting

Principles of Forecasting PDF Author: J.S. Armstrong
Publisher: Springer Science & Business Media
ISBN: 9780792374015
Category : Business & Economics
Languages : en
Pages : 880

Book Description
This handbook summarises knowledge from experts and empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. Includes a comprehensive forecasting dictionary.

Statistical Postprocessing of Ensemble Forecasts

Statistical Postprocessing of Ensemble Forecasts PDF Author: Stéphane Vannitsem
Publisher: Elsevier
ISBN: 012812248X
Category : Science
Languages : en
Pages : 364

Book Description
Statistical Postprocessing of Ensemble Forecasts brings together chapters contributed by international subject-matter experts describing the current state of the art in the statistical postprocessing of ensemble forecasts. The book illustrates the use of these methods in several important applications including weather, hydrological and climate forecasts, and renewable energy forecasting. After an introductory section on ensemble forecasts and prediction systems, the second section of the book is devoted to exposition of the methods available for statistical postprocessing of ensemble forecasts: univariate and multivariate ensemble postprocessing are first reviewed by Wilks (Chapters 3), then Schefzik and Möller (Chapter 4), and the more specialized perspective necessary for postprocessing forecasts for extremes is presented by Friederichs, Wahl, and Buschow (Chapter 5). The second section concludes with a discussion of forecast verification methods devised specifically for evaluation of ensemble forecasts (Chapter 6 by Thorarinsdottir and Schuhen). The third section of this book is devoted to applications of ensemble postprocessing. Practical aspects of ensemble postprocessing are first detailed in Chapter 7 (Hamill), including an extended and illustrative case study. Chapters 8 (Hemri), 9 (Pinson and Messner), and 10 (Van Schaeybroeck and Vannitsem) discuss ensemble postprocessing specifically for hydrological applications, postprocessing in support of renewable energy applications, and postprocessing of long-range forecasts from months to decades. Finally, Chapter 11 (Messner) provides a guide to the ensemble-postprocessing software available in the R programming language, which should greatly help readers implement many of the ideas presented in this book. Edited by three experts with strong and complementary expertise in statistical postprocessing of ensemble forecasts, this book assesses the new and rapidly developing field of ensemble forecast postprocessing as an extension of the use of statistical corrections to traditional deterministic forecasts. Statistical Postprocessing of Ensemble Forecasts is an essential resource for researchers, operational practitioners, and students in weather, seasonal, and climate forecasting, as well as users of such forecasts in fields involving renewable energy, conventional energy, hydrology, environmental engineering, and agriculture. - Consolidates, for the first time, the methodologies and applications of ensemble forecasts in one succinct place - Provides real-world examples of methods used to formulate forecasts - Presents the tools needed to make the best use of multiple model forecasts in a timely and efficient manner

Intermittent Demand Forecasting

Intermittent Demand Forecasting PDF Author: John E. Boylan
Publisher: John Wiley & Sons
ISBN: 1119135303
Category : Medical
Languages : en
Pages : 403

Book Description
INTERMITTENT DEMAND FORECASTING The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting Intermittent Demand Forecasting is for anyone who is interested in improving forecasts of intermittent demand products, and enhancing the management of inventories. Whether you are a practitioner, at the sharp end of demand planning, a software designer, a student, an academic teaching operational research or operations management courses, or a researcher in this field, we hope that the book will inspire you to rethink demand forecasting. If you do so, then you can contribute towards significant economic and environmental benefits. No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software. “Intermittent demand forecasting may seem like a specialized area but actually is at the center of sustainability efforts to consume less and to waste less. Boylan and Syntetos have done a superb job in showing how improvements in inventory management are pivotal in achieving this. Their book covers both the theory and practice of intermittent demand forecasting and my prediction is that it will fast become the bible of the field.” —Spyros Makridakis, Professor, University of Nicosia, and Director, Institute for the Future and the Makridakis Open Forecasting Center (MOFC). “We have been able to support our clients by adopting many of the ideas discussed in this excellent book, and implementing them in our software. I am sure that these ideas will be equally helpful for other supply chain software vendors and for companies wanting to update and upgrade their capabilities in forecasting and inventory management.” —Suresh Acharya, VP, Research and Development, Blue Yonder. “As product variants proliferate and the pace of business quickens, more and more items have intermittent demand. Boylan and Syntetos have long been leaders in extending forecasting and inventory methods to accommodate this new reality. Their book gathers and clarifies decades of research in this area, and explains how practitioners can exploit this knowledge to make their operations more efficient and effective.” —Thomas R. Willemain, Professor Emeritus, Rensselaer Polytechnic Institute.

Australian National Bibliography: 1992

Australian National Bibliography: 1992 PDF Author: National Library of Australia
Publisher: National Library Australia
ISBN:
Category : Australia
Languages : en
Pages : 1976

Book Description


Renewable Energy Forecasting

Renewable Energy Forecasting PDF Author: Georges Kariniotakis
Publisher: Woodhead Publishing
ISBN: 0081005059
Category : Technology & Engineering
Languages : en
Pages : 388

Book Description
Renewable Energy Forecasting: From Models to Applications provides an overview of the state-of-the-art of renewable energy forecasting technology and its applications. After an introduction to the principles of meteorology and renewable energy generation, groups of chapters address forecasting models, very short-term forecasting, forecasting of extremes, and longer term forecasting. The final part of the book focuses on important applications of forecasting for power system management and in energy markets. Due to shrinking fossil fuel reserves and concerns about climate change, renewable energy holds an increasing share of the energy mix. Solar, wind, wave, and hydro energy are dependent on highly variable weather conditions, so their increased penetration will lead to strong fluctuations in the power injected into the electricity grid, which needs to be managed. Reliable, high quality forecasts of renewable power generation are therefore essential for the smooth integration of large amounts of solar, wind, wave, and hydropower into the grid as well as for the profitability and effectiveness of such renewable energy projects. - Offers comprehensive coverage of wind, solar, wave, and hydropower forecasting in one convenient volume - Addresses a topic that is growing in importance, given the increasing penetration of renewable energy in many countries - Reviews state-of-the-science techniques for renewable energy forecasting - Contains chapters on operational applications

Business Forecasting

Business Forecasting PDF Author: Michael Gilliland
Publisher: John Wiley & Sons
ISBN: 1119782473
Category : Business & Economics
Languages : en
Pages : 435

Book Description
Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.

Statistical Methods for Forecasting

Statistical Methods for Forecasting PDF Author: Bovas Abraham
Publisher: John Wiley & Sons
ISBN: 0470317299
Category : Mathematics
Languages : en
Pages : 474

Book Description
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!" -Journal of the Royal Statistical Society "A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates." -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.

The Art of Forecasting Economic Growth

The Art of Forecasting Economic Growth PDF Author: Barrett Williams
Publisher: Barrett Williams
ISBN:
Category : Business & Economics
Languages : en
Pages : 163

Book Description
Unlock the Power of Predicting Tomorrow with "The Art of Forecasting Economic Growth"! Are you ready to delve into the intricate world of economic forecasting? Discover the strategies, methods, and tools that shape the way experts predict future economic trends. "The Art of Forecasting Economic Growth" is your comprehensive guide to mastering economic predictions and leveraging them for smarter decision-making. Start your journey with an essential introduction to economic forecasting, exploring its significance, history, and the key players that have set the stage. As you progress, get acquainted with the fundamentals of data analysis in economics – uncover the types of data, collection methods, and basic concepts in economic modeling. Dive deeper into statistical techniques with chapters dedicated to descriptive and inferential statistics, and regression analysis. Grasp the intricacies of time series analysis and learn how to utilize economic indicators for accurate predictions. Build your full understanding of constructing and validating predictive economic models. Venture into advanced econometric techniques and discover the cutting-edge role of machine learning in economic forecasting. Understand the impact of big data, and the nuanced field of behavioral economics, to enhance your forecasting accuracy even further. Explore the significance of economic policy analysis, scenario planning, and stress testing. Enhance your insight on forecasting financial markets and evaluate the accuracy of your predictions with clear, actionable metrics. Learn the best practices for communicating your forecasts, ensuring clarity and impact. Ethics play a critical role in economic forecasting. This eBook provides a mindful exploration of ethical considerations, dilemmas, and solutions, backed by real-world case studies. Utilize forecasts to shape business strategies and align them with market realities. As you reach the final chapters, look ahead to the future of economic forecasting, exploring emerging trends, the transformative influence of AI, and the dynamics of a globalized economy. "The Art of Forecasting Economic Growth" is a must-have for anyone seeking to understand and apply economic forecasting techniques. Equip yourself with the knowledge to predict, plan, and prosper in an ever-changing economic landscape. Your journey into the future of economics starts here!