Probabilistic Forecasts And Optimal Decisions

DOWNLOAD

Download Probabilistic Forecasts And Optimal Decisions PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Probabilistic Forecasts And Optimal Decisions book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Probabilistic Forecasts And Optimal Decisions

DOWNLOAD
Author : Roman Krzysztofowicz
language : en
Publisher: John Wiley & Sons
Release Date : 2025-02-03

Probabilistic Forecasts And Optimal Decisions written by Roman Krzysztofowicz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-03 with Technology & Engineering categories.

Account for uncertainties and optimize decision-making with this thorough exposition Decision theory is a body of thought and research seeking to apply a mathematical-logical framework to assessing probability and optimizing decision-making. It has developed robust tools for addressing all major challenges to decision making. Yet the number of variables and uncertainties affecting each decision outcome, many of them beyond the decider's control, mean that decision-making is far from a “solved problem”. The tools created by decision theory remain to be refined and applied to decisions in which uncertainties are prominent. Probabilistic Forecasts and Optimal Decisions introduces a theoretically-grounded methodology for optimizing decision-making under conditions of uncertainty. Beginning with an overview of the basic elements of probability theory and methods for modeling continuous variates, it proceeds to survey the mathematics of both continuous and discrete models, supporting each with key examples. The result is a crucial window into the complex but enormously rewarding world of decision theory. Probabilistic Forecasts and Optimal Decisions readers will also find: Extended case studies supported with real-world data Mini-projects running through multiple chapters to illustrate different stages of the decision-making process End of chapter exercises designed to facilitate student learning Probabilistic Forecasts and Optimal Decisions is ideal for advanced undergraduate and graduate students in the sciences and engineering, as well as predictive analytics and decision analytics professionals.

Probabilistic Forecasts And Optimal Decisions

DOWNLOAD
Author : Roman Krzysztofowicz
language : en
Publisher: John Wiley & Sons
Release Date : 2024-11-20

Probabilistic Forecasts And Optimal Decisions written by Roman Krzysztofowicz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-20 with Technology & Engineering categories.

Account for uncertainties and optimize decision-making with this thorough exposition Decision theory is a body of thought and research seeking to apply a mathematical-logical framework to assessing probability and optimizing decision-making. It has developed robust tools for addressing all major challenges to decision making. Yet the number of variables and uncertainties affecting each decision outcome, many of them beyond the decider’s control, mean that decision-making is far from a ‘solved problem’. The tools created by decision theory remain to be refined and applied to decisions in which uncertainties are prominent. Probabilistic Forecasts and Optimal Decisions introduces a theoretically-grounded methodology for optimizing decision-making under conditions of uncertainty. Beginning with an overview of the basic elements of probability theory and methods for modeling continuous variates, it proceeds to survey the mathematics of both continuous and discrete models, supporting each with key examples. The result is a crucial window into the complex but enormously rewarding world of decision theory. Readers of Probablistic Forecasts and Optimal Decisions will also find: Extended case studies supported with real-world data Mini-projects running through multiple chapters to illustrate different stages of the decision-making process End of chapter exercises designed to facilitate student learning Probabilistic Forecasts and Optimal Decisions is ideal for advanced undergraduate and graduate students in the sciences and engineering, as well as predictive analytics and decision analytics professionals.

Statistical Learning Tools For Electricity Load Forecasting

DOWNLOAD
Author : Anestis Antoniadis
language : en
Publisher: Springer Nature
Release Date : 2024-08-14

Statistical Learning Tools For Electricity Load Forecasting written by Anestis Antoniadis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-14 with Mathematics categories.

This monograph explores a set of statistical and machine learning tools that can be effectively utilized for applied data analysis in the context of electricity load forecasting. Drawing on their substantial research and experience with forecasting electricity demand in industrial settings, the authors guide readers through several modern forecasting methods and tools from both industrial and applied perspectives – generalized additive models (GAMs), probabilistic GAMs, functional time series and wavelets, random forests, aggregation of experts, and mixed effects models. A collection of case studies based on sizable high-resolution datasets, together with relevant R packages, then illustrate the implementation of these techniques. Five real datasets at three different levels of aggregation (nation-wide, region-wide, or individual) from four different countries (UK, France, Ireland, and the USA) are utilized to study five problems: short-term point-wise forecasting, selection of relevant variables for prediction, construction of prediction bands, peak demand prediction, and use of individual consumer data. This text is intended for practitioners, researchers, and post-graduate students working on electricity load forecasting; it may also be of interest to applied academics or scientists wanting to learn about cutting-edge forecasting tools for application in other areas. Readers are assumed to be familiar with standard statistical concepts such as random variables, probability density functions, and expected values, and to possess some minimal modeling experience.

Probability Statistics And Decision Making In The Atmospheric Sciences

DOWNLOAD
Author : Allan Murphy
language : en
Publisher: CRC Press
Release Date : 2019-07-11

Probability Statistics And Decision Making In The Atmospheric Sciences written by Allan Murphy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-11 with Mathematics categories.

Methodology drawn from the fields of probability. statistics and decision making plays an increasingly important role in the atmosphericsciences. both in basic and applied research and in experimental and operational studies. Applications of such methodology can be found in almost every facet of the discipline. from the most theoretical and global (e.g., atmospheric predictability. global climate modeling) to the most practical and local (e.g., crop-weather modeling forecast evaluation). Almost every issue of the multitude of journals published by the atmospheric sciences community now contain some or more papers involving applications of concepts and/or methodology from the fields of probability and statistics. Despite the increasingly pervasive nature of such applications. very few book length treatments of probabilistic and statistical topics of particular interest to atmospheric scientists have appeared (especially inEnglish) since the publication of the pioneering works of Brooks andCarruthers (Handbook of Statistical Methods in Meteorology) in 1953 and Panofsky and Brier-(some Applications of)statistics to Meteor) in 1958. As a result. many relatively recent developments in probability and statistics are not well known to atmospheric scientists and recent work in active areas of meteorological research involving significant applications of probabilistic and statistical methods are not familiar to the meteorological community as a whole.

Seasonal Climate Forecasting And Managing Risk

DOWNLOAD
Author : Alberto Troccoli
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-02-22

Seasonal Climate Forecasting And Managing Risk written by Alberto Troccoli and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-22 with Science categories.

Originally formed around a set of lectures presented at a NATO Advanced Study Institute (ASI), this book has grown to become organised and presented rather more as a textbook than as a standard "collection of proceedings". This therefore is the first unified reference ‘textbook’ in seasonal to interannual climate predictions and their practical uses. Written by some of the world’s leading experts, the book covers a rapidly-developing science of prime social concern.

Intelligent Decision Technologies

DOWNLOAD
Author : Rui Neves-Silva
language : en
Publisher: Springer
Release Date : 2015-06-09

Intelligent Decision Technologies written by Rui Neves-Silva and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-09 with Technology & Engineering categories.

This book presents the 57 papers accepted for presentation at the Seventh KES International Conference on Intelligent Decision Technologies (KES-IDT 2015), held in Sorrento, Italy, in June 2015. The conference consists of keynote talks, oral and poster presentations, invited sessions and workshops on the applications and theory of intelligent decision systems and related areas. The conference provides an opportunity for the presentation and discussion of interesting new research results, promoting knowledge transfer and the generation of new ideas. The book will be of interest to all those whose work involves the development and application of intelligent decision systems.

Smart Meter Data Analytics

DOWNLOAD
Author : Yi Wang
language : en
Publisher: Springer Nature
Release Date : 2020-02-24

Smart Meter Data Analytics written by Yi Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-24 with Business & Economics categories.

This book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied. The following works try to model complex consumer behavior. Specific works include load profiling, pattern recognition, personalized price design, socio-demographic information identification, and household behavior coding. On this basis, the book extends consumer behavior in spatial and temporal scale. Works such as consumer aggregation, individual load forecasting, and aggregated load forecasting are introduced. We hope this book can inspire readers to define new problems, apply novel methods, and obtain interesting results with massive smart meter data or even other monitoring data in the power systems.

Integrating Renewables In Electricity Markets

DOWNLOAD
Author : Juan M. Morales
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-03

Integrating Renewables In Electricity Markets written by Juan M. Morales and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-03 with Business & Economics categories.

This addition to the ISOR series addresses the analytics of the operations of electric energy systems with increasing penetration of stochastic renewable production facilities, such as wind- and solar-based generation units. As stochastic renewable production units become ubiquitous throughout electric energy systems, an increasing level of flexible backup provided by non-stochastic units and other system agents is needed if supply security and quality are to be maintained. Within the context above, this book provides up-to-date analytical tools to address challenging operational problems such as: • The modeling and forecasting of stochastic renewable power production. • The characterization of the impact of renewable production on market outcomes. • The clearing of electricity markets with high penetration of stochastic renewable units. • The development of mechanisms to counteract the variability and unpredictability of stochastic renewable units so that supply security is not at risk. • The trading of the electric energy produced by stochastic renewable producers. • The association of a number of electricity production facilities, stochastic and others, to increase their competitive edge in the electricity market. • The development of procedures to enable demand response and to facilitate the integration of stochastic renewable units. This book is written in a modular and tutorial manner and includes many illustrative examples to facilitate its comprehension. It is intended for advanced undergraduate and graduate students in the fields of electric energy systems, applied mathematics and economics. Practitioners in the electric energy sector will benefit as well from the concepts and techniques explained in this book.

Statistical Postprocessing Of Ensemble Forecasts

DOWNLOAD
Author : Stéphane Vannitsem
language : en
Publisher: Elsevier
Release Date : 2018-05-17

Statistical Postprocessing Of Ensemble Forecasts written by Stéphane Vannitsem and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-17 with Science categories.

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

The Design Of Human Centered Artificial Intelligence For The Workplace

DOWNLOAD
Author : Constantinos K. Coursaris
language : en
Publisher: Springer Nature
Release Date : 2025-08-02

The Design Of Human Centered Artificial Intelligence For The Workplace written by Constantinos K. Coursaris and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-02 with Business & Economics categories.

Rapid advances in artificial intelligence (AI) are manifesting in increasingly sophisticated technologies and systems contributing to the digital transformation of organizations. These technological innovations involve the use of automation agents adding value through increased efficiency, effectiveness, service quality, and other performance-related dimensions. Motivated by the possibilities afforded by AI in organizational contexts of use, as well as by the challenges associated with AI, this book provides a comprehensive view of the considerations involved in designing AI-enabled systems, their application in the workplace, and the corresponding user experience. To this end, the book presents conceptual and empirical scientific perspectives on the design of human-centered AI, as well as case studies from multiple industries ranging from aerospace and automotive to retail, finance, and healthcare. These perspectives and evidence enable readers to consider and plan their own use cases for human-centered AI in the workplace. The book will be of interest to researchers and practitioners alike involved in the governance, design, development, implementation, and maintenance of human-AI-driven systems.