Entropy Application for Forecasting
Entropy Application for Forecasting

Author: Ana Jesus Lopez-Menendez

Publisher: MDPI

Published: 2020-12-29

Total Pages: 200

ISBN-13: 3039364871

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This book shows the potential of entropy and information theory in forecasting, including both theoretical developments and empirical applications. The contents cover a great diversity of topics, such as the aggregation and combination of individual forecasts, the comparison of forecasting performance, and the debate concerning the tradeoff between complexity and accuracy. Analyses of forecasting uncertainty, robustness, and inconsistency are also included, as are proposals for new forecasting approaches. The proposed methods encompass a variety of time series techniques (e.g., ARIMA, VAR, state space models) as well as econometric methods and machine learning algorithms. The empirical contents include both simulated experiments and real-world applications focusing on GDP, M4-Competition series, confidence and industrial trend surveys, and stock exchange composite indices, among others. In summary, this collection provides an engaging insight into entropy applications for forecasting, offering an interesting overview of the current situation and suggesting possibilities for further research in this field.

Digital Enterprise Technology
Digital Enterprise Technology

Author: Pedro Filipe Cunha

Publisher: Springer Science & Business Media

Published: 2007-09-18

Total Pages: 599

ISBN-13: 0387498648

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The first Digital Enterprise Technology (DET) International Conference was held in Durham, UK in 2002 and the second DET Conference in Seattle, USA in 2004. Sponsored by CIRP (College International pour la Recherche en Productique), the third DET Conference took place in Setúbal, Portugal in 2006. Digital Enterprise Technology: Perspectives and Future Challenges is an edited volume based on this conference. Topics include: distributed and collaborative design, process modeling and process planning, advanced factory equipment and layout design and modeling, physical-to-digital environment integrators, enterprise integration technologies, and entrepreneurship in DET.

Entropy-Based Parameter Estimation in Hydrology
Entropy-Based Parameter Estimation in Hydrology

Author: Vijay Singh

Publisher: Springer Science & Business Media

Published: 1998-10-31

Total Pages: 400

ISBN-13: 9780792352242

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Since the pioneering work of Shannon in the late 1940's on the development of the theory of entropy and the landmark contributions of Jaynes a decade later leading to the development of the principle of maximum entropy (POME), the concept of entropy has been increasingly applied in a wide spectrum of areas, including chemistry, electronics and communications engineering, data acquisition and storage and retreival, data monitoring network design, ecology, economics, environmental engineering, earth sciences, fluid mechanics, genetics, geology, geomorphology, geophysics, geotechnical engineering, hydraulics, hydrology, image processing, management sciences, operations research, pattern recognition and identification, photogrammetry, psychology, physics and quantum mechanics, reliability analysis, reservoir engineering, statistical mechanics, thermodynamics, topology, transportation engineering, turbulence modeling, and so on. New areas finding application of entropy have since continued to unfold. The entropy concept is indeed versatile and its applicability widespread. In the area of hydrology and water resources, a range of applications of entropy have been reported during the past three decades or so. This book focuses on parameter estimation using entropy for a number of distributions frequently used in hydrology. In the entropy-based parameter estimation the distribution parameters are expressed in terms of the given information, called constraints. Thus, the method lends itself to a physical interpretation of the parameters. Because the information to be specified usually constitutes sufficient statistics for the distribution under consideration, the entropy method provides a quantitative way to express the information contained in the distribution.

Entropy Theory and its Application in Environmental and Water Engineering
Entropy Theory and its Application in Environmental and Water Engineering

Author: Vijay P. Singh

Publisher: Wiley-Blackwell

Published: 2013-02-18

Total Pages: 662

ISBN-13: 9781119976561

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Entropy Theory and its Application in Environmental and Water Engineering responds to the need for a book that deals with basic concepts of entropy theory from a hydrologic and water engineering perspective and then for a book that deals with applications of these concepts to a range of water engineering problems. The range of applications of entropy is constantly expanding and new areas finding a use for the theory are continually emerging. The applications of concepts and techniques vary across different subject areas and this book aims to relate them directly to practical problems of environmental and water engineering. The book presents and explains the Principle of Maximum Entropy (POME) and the Principle of Minimum Cross Entropy (POMCE) and their applications to different types of probability distributions. Spatial and inverse spatial entropy are important for urban planning and are presented with clarity. Maximum entropy spectral analysis and minimum cross entropy spectral analysis are powerful techniques for addressing a variety of problems faced by environmental and water scientists and engineers and are described here with illustrative examples. Giving a thorough introduction to the use of entropy to measure the unpredictability in environmental and water systems this book will add an essential statistical method to the toolkit of postgraduates, researchers and academic hydrologists, water resource managers, environmental scientists and engineers. It will also offer a valuable resource for professionals in the same areas, governmental organizations, private companies as well as students in earth sciences, civil and agricultural engineering, and agricultural and rangeland sciences. This book: Provides a thorough introduction to entropy for beginners and more experienced users Uses numerous examples to illustrate the applications of the theoretical principles Allows the reader to apply entropy theory to the solution of practical problems Assumes minimal existing mathematical knowledge Discusses the theory and its various aspects in both univariate and bivariate cases Covers newly expanding areas including neural networks from an entropy perspective and future developments.

Entropy Theory in Hydrologic Science and Engineering
Entropy Theory in Hydrologic Science and Engineering

Author: Vijay P. Singh

Publisher: McGraw Hill Professional

Published: 2014-09-22

Total Pages: 849

ISBN-13: 0071835474

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A THOROUGH INTRODUCTION TO ENTROPY THEORY AND ITS APPLICATIONS IN HYDROLOGIC SCIENCE AND ENGINEERING This comprehensive volume addresses basic concepts of entropy theory from a hydrologic engineering perspective. The application of these concepts to a wide range of hydrologic engineering problems is discussed in detail. The book is divided into sections--preliminaries, rainfall and evapotranspiration, subsurface flow, surface flow, and environmental considerations. Helpful equations, solutions, tables, and diagrams are included throughout this practical resource. Entropy Theory in Hydrologic Science and Engineering covers: Introduction to entropy theory Maximum entropy production principle Performance measures Morphological analysis Evaluation and design of sampling and measurement networks Precipitation variability Rainfall frequency distributions Evaluation of precipitation forecasting schemes Assessment of potential water resources availability Evaporation Infiltration Soil moisture Groundwater flow Rainfall-runoff modeling Streamflow simulation Hydrologic frequency analysis Streamflow forecasting River flow regime classification Sediment yield Eco-index

DAX Cookbook
DAX Cookbook

Author: Greg Deckler

Publisher: Packt Publishing Ltd

Published: 2020-03-18

Total Pages: 541

ISBN-13: 1839215224

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Solve real-world business problems by learning how to create common industry key performance indicators and other calculations using DAX within Microsoft products such as Power BI, SQL Server, and Excel. Key FeaturesLearn to write sophisticated DAX queries to solve business intelligence and data analytics challengesHandle performance issues and optimization within the data model, DAX calculations and moreSolve business issues with Microsoft Excel, Power BI, and SQL Server using DAX queriesBook Description DAX provides an extra edge by extracting key information from the data that is already present in your model. Filled with examples of practical, real-world calculations geared toward business metrics and key performance indicators, this cookbook features solutions that you can apply for your own business analysis needs. You'll learn to write various DAX expressions and functions to understand how DAX queries work. The book also covers sections on dates, time, and duration to help you deal with working days, time zones, and shifts. You'll then discover how to manipulate text and numbers to create dynamic titles and ranks, and deal with measure totals. Later, you'll explore common business metrics for finance, customers, employees, and projects. The book will also show you how to implement common industry metrics such as days of supply, mean time between failure, order cycle time and overall equipment effectiveness. In the concluding chapters, you'll learn to apply statistical formulas for covariance, kurtosis, and skewness. Finally, you'll explore advanced DAX patterns for interpolation, inverse aggregators, inverse slicers, and even forecasting with a deseasonalized correlation coefficient. By the end of this book, you'll have the skills you need to use DAX's functionality and flexibility in business intelligence and data analytics. What you will learnUnderstand how to create common calculations for dates, time, and durationCreate key performance indicators (KPIs) and other business calculationsDevelop general DAX calculations that deal with text and numbersDiscover new ideas and time-saving techniques for better calculations and modelsPerform advanced DAX calculations for solving statistical measures and other mathematical formulasHandle errors in DAX and learn how to debug DAX calculationsUnderstand how to optimize your data modelsWho this book is for Business users, BI developers, data analysts, and SQL users who are looking for solutions to the challenges faced while solving analytical operations using DAX techniques and patterns will find this book useful. Basic knowledge of the DAX language and Microsoft services is mandatory.

Artificial Intelligence and Technologies
Artificial Intelligence and Technologies

Author: Rajeev R. Raje

Publisher: Springer Nature

Published: 2021-12-16

Total Pages: 656

ISBN-13: 981166448X

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This book constitutes refereed proceedings of the 3rd International Conference on Recent Trends in Advanced Computing - Artificial Intelligence and Technologies. This book covers a wide range of topics—vision, analytics, robotics, networking, health care, current pandemic issues of COVID-19, and cutting-edge technologies connected to cybersecurity in digital manufacturing and Industry 4.0. The contents of this book will be useful to researchers from industry and academia. The volume includes novel contributions and the latest developments from researchers across industry and academia. The book will serve as a valuable reference resource for academics and researchers across the globe.

Entropy Applications in Environmental and Water Engineering
Entropy Applications in Environmental and Water Engineering

Author: Huijuan Cui

Publisher: MDPI

Published: 2019-03-07

Total Pages: 512

ISBN-13: 3038972223

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Entropy theory has wide applications to a range of problems in the fields of environmental and water engineering, including river hydraulic geometry, fluvial hydraulics, water monitoring network design, river flow forecasting, floods and droughts, river network analysis, infiltration, soil moisture, sediment transport, surface water and groundwater quality modeling, ecosystems modeling, water distribution networks, environmental and water resources management, and parameter estimation. Such applications have used several different entropy formulations, such as Shannon, Tsallis, Rényi, Burg, Kolmogorov, Kapur, configurational, and relative entropies, which can be derived in time, space, or frequency domains. More recently, entropy-based concepts have been coupled with other theories, including copula and wavelets, to study various issues associated with environmental and water resources systems. Recent studies indicate the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering, including establishing and explaining physical connections between theory and reality. The objective of this Special Issue is to provide a platform for compiling important recent and current research on the applications of entropy theory in environmental and water engineering. The contributions to this Special Issue have addressed many aspects associated with entropy theory applications and have shown the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering.

A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation
A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation

Author: Hongjun Guan

Publisher: Infinite Study

Published:

Total Pages: 18

ISBN-13:

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In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data.

Computational Intelligence: Theories, Applications and Future Directions - Volume II
Computational Intelligence: Theories, Applications and Future Directions - Volume II

Author: Nishchal K. Verma

Publisher: Springer

Published: 2018-09-01

Total Pages: 660

ISBN-13: 9811311358

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This book presents selected proceedings of ICCI-2017, discussing theories, applications and future directions in the field of computational intelligence (CI). ICCI-2017 brought together international researchers presenting innovative work on self-adaptive systems and methods. This volume covers the current state of the field and explores new, open research directions. The book serves as a guide for readers working to develop and validate real-time problems and related applications using computational intelligence. It focuses on systems that deal with raw data intelligently, generate qualitative information that improves decision-making, and behave as smart systems, making it a valuable resource for researchers and professionals alike.