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Author: Katharine Anderson
Publisher: University of Chicago Press
ISBN: 0226019705
Category : Science
Languages : en
Pages : 342
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Book Description
Victorian Britain, with its maritime economy and strong links between government and scientific enterprises, founded an office to collect meteorological statistics in 1854 in an effort to foster a modern science of the weather. But as the office turned to prediction rather than data collection, the fragile science became a public spectacle, with its forecasts open to daily scrutiny in the newspapers. And meteorology came to assume a pivotal role in debates about the responsibility of scientists and the authority of science. Studying meteorology as a means to examine the historical identity of prediction, Katharine Anderson offers here an engrossing account of forecasting that analyzes scientific practice and ideas about evidence, the organization of science in public life, and the articulation of scientific values in Victorian culture. In Predicting the Weather, Anderson grapples with fundamental questions about the function, intelligibility, and boundaries of scientific work while exposing the public expectations that shaped the practice of science during this period. A cogent analysis of the remarkable history of weather forecasting in Victorian Britain, Predicting the Weather will be essential reading for scholars interested in the public dimensions of science.
Author: Katharine Anderson
Publisher: University of Chicago Press
ISBN: 0226019705
Category : Science
Languages : en
Pages : 342
Get Book
Book Description
Victorian Britain, with its maritime economy and strong links between government and scientific enterprises, founded an office to collect meteorological statistics in 1854 in an effort to foster a modern science of the weather. But as the office turned to prediction rather than data collection, the fragile science became a public spectacle, with its forecasts open to daily scrutiny in the newspapers. And meteorology came to assume a pivotal role in debates about the responsibility of scientists and the authority of science. Studying meteorology as a means to examine the historical identity of prediction, Katharine Anderson offers here an engrossing account of forecasting that analyzes scientific practice and ideas about evidence, the organization of science in public life, and the articulation of scientific values in Victorian culture. In Predicting the Weather, Anderson grapples with fundamental questions about the function, intelligibility, and boundaries of scientific work while exposing the public expectations that shaped the practice of science during this period. A cogent analysis of the remarkable history of weather forecasting in Victorian Britain, Predicting the Weather will be essential reading for scholars interested in the public dimensions of science.
Author: Nicolas Vandeput
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110671204
Category : Business & Economics
Languages : en
Pages : 338
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Book Description
Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method which includes experimentation, observation, and constant questioning must be applied to supply chains to achieve excellence in demand forecasting. This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value added framework. Part I focuses on statistical "traditional" models, Part II, on machine learning, and the all-new Part III discusses demand forecasting process management. The various chapters focus on both forecast models and new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. The book is replete with do-it-yourself sections with implementations provided in Python (and Excel for the statistical models) to show the readers how to apply these models themselves. This hands-on book, covering the entire range of forecasting—from the basics all the way to leading-edge models—will benefit supply chain practitioners, forecasters, and analysts looking to go the extra mile with demand forecasting. Events around the book Link to a De Gruyter Online Event in which the author Nicolas Vandeput together with Stefan de Kok, supply chain innovator and CEO of Wahupa; Spyros Makridakis, professor at the University of Nicosia and director of the Institute For the Future (IFF); and Edouard Thieuleux, founder of AbcSupplyChain, discuss the general issues and challenges of demand forecasting and provide insights into best practices (process, models) and discussing how data science and machine learning impact those forecasts. The event will be moderated by Michael Gilliland, marketing manager for SAS forecasting software: https://youtu.be/1rXjXcabW2s
Author: Rob J Hyndman
Publisher: OTexts
ISBN: 0987507117
Category : Business & Economics
Languages : en
Pages : 380
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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.
Author: Nicolas Vandeput
Publisher: Independently Published
ISBN: 9781730969430
Category :
Languages : en
Pages : 237
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Book Description
Data Science for Supply Chain Forecast Data Science for Supply Chain Forecast is a book for practitioners focusing on data science and machine learning; it demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. As one will discover in this book, artificial intelligence (AI) & machine learning (ML) are not simply a question of coding skills. Using data science in order to solve a problem requires a scientific mindset more than coding skills. The story behind these models is one of experimentation, of observation and of constant questioning; a true scientific method must be applied to supply chain. In the data science field as well as that of the supply chain, simple questions do not come with simple answers. In order to resolve these questions, one needs to be both a scientist as well as to use the correct tools. In this book, we will discuss both. Is this Book for me? This book has been written for supply chain practitioners, forecasters and analysts who are looking to go the extra mile. You do not need technical IT skills to start using the models of this book. You do not need a dedicated server or expensive software licenses: you solely need your own computer. You do not need a PhD in mathematics: mathematics will only be utilized as a tool to tweak and understand the models. In the majority of the cases - especially when it comes to machine learning - a deep understanding of the mathematical inner workings of a model will not be necessary in order to optimize it and understand its limitations. Reviews "In an age where analytics and machine learning are taking on larger roles in the business forecasting, Nicolas' book is perfect solution for professionals who need to combine practical supply chain experience with the mathematical and technological tools that can help us predict the future more reliably." Daniel Stanton - Author, Supply Chain Management For Dummies "Open source statistical toolkits have progressed tremendously over the last decade. Nicolas demonstrates that these toolkits are more than enough to start addressing real-world forecasting challenges as found in supply chains. Moreover, through its hands-on approach, this book is accessible to a large audience of supply chain practitioners. The supply chain of the 21st century will be data-driven and Nicolas gets it perfectly." Joannes Vermorel - CEO Lokad "This book is unique in its kind. It explains the basics of Python using basic traditional forecasting techniques and shows how machine learning is revolutionizing the forecasting domain. Nicolas has done an outstanding job explaining a technical subject in an easily accessible way. A must-read for any supply chain professional." Professor Bram Desmet - CEO Solventure "This book is before anything a practical and business-oriented "DIY" user manual to help planners move into 21st-century demand planning. The breakthrough comes from several tools and techniques available to all, and which thanks to Nicolas' precise and concrete explanations can now be implemented in real business environments by any "normal" planner. I can confirm that Nicolas' learnings are based on real-life experience and can tremendously help on improving top and bottom lines." Henri-Xavier Benoist - VP Supply Chain Bridegstone EMEA
Author: Fotini K. Chow
Publisher: Springer Science & Business Media
ISBN: 9400740980
Category : Science
Languages : en
Pages : 760
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Book Description
This book provides readers with a broad understanding of the fundamental principles driving atmospheric flow over complex terrain and provides historical context for recent developments and future direction for researchers and forecasters. The topics in this book are expanded from those presented at the Mountain Weather Workshop, which took place in Whistler, British Columbia, Canada, August 5-8, 2008. The inspiration for the workshop came from the American Meteorological Society (AMS) Mountain Meteorology Committee and was designed to bridge the gap between the research and forecasting communities by providing a forum for extended discussion and joint education. For academic researchers, this book provides some insight into issues important to the forecasting community. For the forecasting community, this book provides training on fundamentals of atmospheric processes over mountainous regions, which are notoriously difficult to predict. The book also helps to provide a better understanding of current research and forecast challenges, including the latest contributions and advancements to the field. The book begins with an overview of mountain weather and forecasting chal- lenges specific to complex terrain, followed by chapters that focus on diurnal mountain/valley flows that develop under calm conditions and dynamically-driven winds under strong forcing. The focus then shifts to other phenomena specific to mountain regions: Alpine foehn, boundary layer and air quality issues, orographic precipitation processes, and microphysics parameterizations. Having covered the major physical processes, the book shifts to observation and modelling techniques used in mountain regions, including model configuration and parameterizations such as turbulence, and model applications in operational forecasting. The book concludes with a discussion of the current state of research and forecasting in complex terrain, including a vision of how to bridge the gap in the future.
Author: Marina Astitha
Publisher: Elsevier
ISBN: 0128202432
Category : Science
Languages : en
Pages : 359
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Book Description
Extreme Weather Forecasting reviews current knowledge about extreme weather events, including key elements and less well-known variables to accurately forecast them. The book covers multiple temporal scales as well as components of current weather forecasting systems. Sections cover case studies on successful forecasting as well as the impacts of extreme weather predictability, presenting a comprehensive and model agnostic review of best practices for atmospheric scientists and others who utilize extreme weather forecasts. Reviews recent developments in numerical prediction for better forecasting of extreme weather events Covers causes and mechanisms of high impact extreme events and how to account for these variables when forecasting Includes numerous case studies on successful forecasting, outlining why they worked
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309069904
Category : Social Science
Languages : en
Pages : 369
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Book Description
Is rapid world population growth actually coming to an end? As population growth and its consequences have become front-page issues, projections of slowing growth from such institutions as the United Nations and the World Bank have been called into question. Beyond Six Billion asks what such projections really say, why they say it, whether they can be trusted, and whether they can be improved. The book includes analysis of how well past U.N. and World Bank projections have panned out, what errors have occurred, and why they have happened. Focusing on fertility as one key to accurate projections, the committee examines the transition from high, constant fertility to low fertility levels and discusses whether developing countries will eventually attain the very low levels of births now observed in the industrialized world. Other keys to accurate projections, predictions of lengthening life span and of the impact of international migration on specific countries, are also explored in detail. How good are our methods of population forecasting? How can we cope with the inevitable uncertainty? What population trends can we anticipate? Beyond Six Billion illuminates not only the forces that shape population growth but also the accuracy of the methods we use to quantify these forces and the uncertainty surrounding projections. The Committee on Population was established by the National Academy of Sciences (NAS) in 1983 to bring the knowledge and methods of the population sciences to bear on major issues of science and public policy. The committee's work includes both basic studies of fertility, health and mortality, and migration; and applied studies aimed at improving programs for the public health and welfare in the United States and in developing countries. The committee also fosters communication among researchers in different disciplines and countries and policy makers in government, international agencies, and private organizations. The work of the committee is made possible by funding from several government agencies and private foundations.
Author: Philip E. Tetlock
Publisher: Crown
ISBN: 080413670X
Category : Business & Economics
Languages : en
Pages : 352
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Book Description
NEW YORK TIMES BESTSELLER • NAMED ONE OF THE BEST BOOKS OF THE YEAR BY THE ECONOMIST “The most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow.”—Jason Zweig, The Wall Street Journal Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week’s meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught? In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters." In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.
Author: Steven S. Skiena
Publisher: Cambridge University Press
ISBN: 9780521009621
Category : Computers
Languages : en
Pages : 252
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Book Description
A story of using computer simulations and mathematical modeling techniques to predict the outcome of jai-alai matches and bet on them successfully.
Author: Michael C. Dietze
Publisher: Princeton University Press
ISBN: 1400885450
Category : Science
Languages : en
Pages : 285
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Book Description
An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online
