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Entropy Measures for Environmental Data

Entropy Measures for Environmental Data
Author: Linda Altieri
Publisher: Springer
Total Pages: 0
Release: 2024-07-15
Genre: Science
ISBN: 9789819725458
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This book shows how to successfully adapt entropy measures to the complexity of environmental data. It also provides a unified framework that covers all main entropy and spatial entropy measures in the literature, with suggestions for their potential use in the analysis of environmental data such as biodiversity, land use and other phenomena occurring over space or time, or both. First, recent literature reviews about including spatial information in traditional entropy measures are presented, highlighting the advantages and disadvantages of past approaches and the difference in interpretation of their proposals. A consistent notation applicable to all approaches is introduced, and the authors’ own proposal is presented. Second, the use of entropy in spatial sampling is focused on, and a method with an outstanding performance when data show a negative or complex spatial correlation is proposed. The last part of the book covers estimating entropy and proposes a model-based approach that differs from all existing estimators, working with data presenting any departure from independence: presence of covariates, temporal or spatial correlation, or both. The theoretical parts are supported by environmental examples covering point data about biodiversity and lattice data about land use. Moreover, a practical section is provided for all parts of the book; in particular, the R package SpatEntropy covers not only the authors’ novel proposals, but also all the main entropy and spatial entropy indices available in the literature. R codes are supplemented to reproduce all the examples. This book is a valuable resource for students and researchers in applied sciences where the use of entropy measures is of interest and where data present dependence on space, time or covariates, such as geography, ecology, biology and landscape analysis.

Entropy Measures for Data Analysis

Entropy Measures for Data Analysis
Author: Karsten Keller
Publisher: MDPI
Total Pages: 260
Release: 2019-12-19
Genre: Science
ISBN: 3039280325
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Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.

Entropy Applications in Environmental and Water Engineering

Entropy Applications in Environmental and Water Engineering
Author: Huijuan Cui
Publisher: MDPI
Total Pages: 512
Release: 2019-03-07
Genre: Technology & Engineering
ISBN: 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.

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: John Wiley & Sons
Total Pages: 787
Release: 2013-01-10
Genre: Science
ISBN: 1118428609
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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 Measures for Data Analysis: Theory, Algorithms and Applications

Entropy Measures for Data Analysis: Theory, Algorithms and Applications
Author: Karsten Keller
Publisher:
Total Pages: 260
Release: 2019
Genre: Engineering (General). Civil engineering (General)
ISBN: 9783039280339
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Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.

Neutrosophic Entropy Measures For The Normal Distribution: Theory And Applications

Neutrosophic Entropy Measures For The Normal Distribution: Theory And Applications
Author: Rehan Ahmad Khan Sherwani
Publisher: Infinite Study
Total Pages: 16
Release:
Genre: Mathematics
ISBN:
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Entropy is a measure of uncertainty and often used in information theory to determine the precise testimonials about unclear situations. Different entropy measures available in the literature are based on the exact form of the observations and lacks in dealing with the interval-valued data. The interval-valued data often arises from the situations having ambiguity, imprecise, unclear, indefinite, or vague states of the experiment and is called neutrosophic data. In this research modified forms of different entropy measures for normal probability distribution have been proposed by considering the neutrosophic form data. The performance of the proposed neutrosophic entropies for normal distribution has been assessed via a simulation study. Moreover, the proposed measures are also applied to two real data sets for their wide applicability.

Entropy, Measures of Distance and Similarity of Q-Neutrosophic Soft Sets and Some Applications

Entropy, Measures of Distance and Similarity of Q-Neutrosophic Soft Sets and Some Applications
Author: Majdoleen Abu Qamar
Publisher: Infinite Study
Total Pages: 16
Release:
Genre: Mathematics
ISBN:
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The idea of the Q-neutrosophic soft set emerges from the neutrosophic soft set by upgrading the membership functions to a two-dimensional entity which indicate uncertainty, indeterminacy and falsity. Hence, it is able to deal with two-dimensional inconsistent, imprecise, and indeterminate information appearing in real life situations. In this study, the tools that measure the similarity, distance and the degree of fuzziness of Q-neutrosophic soft sets are presented. The definitions of distance, similarity and measures of entropy are introduced. Some formulas for Q-neutrosophic soft entropy were presented. The known Hamming, Euclidean and their normalized distances are generalized to make them well matched with the idea of Q-neutrosophic soft set. The distance measure is subsequently used to define the measure of similarity. Lastly, we expound three applications of the measures of Q-neutrosophic soft sets by applying entropy and the similarity measure to a medical diagnosis and decision making problems.

Spatial Point Patterns

Spatial Point Patterns
Author: Adrian Baddeley
Publisher: CRC Press
Total Pages: 830
Release: 2015-11-11
Genre: Mathematics
ISBN: 1482210215
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Modern Statistical Methodology and Software for Analyzing Spatial Point PatternsSpatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on th

The Entropy Effect

The Entropy Effect
Author: Paul E Triulzi
Publisher: iUniverse
Total Pages: 118
Release: 2018-04-06
Genre: Science
ISBN: 1532043120
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This book proposes conclusions and hypotheses derived from applying the concept of entropy to an analysis of physical and virtual systems. It is not a treatment of entropy as a thermodynamic measure, but rather a conceptual exploration of entropys role in systems. It presents a macroscopic level analysis of the effects of entropy in systems, and ties this analysis to discussions of energy, work, production, information, evolution, creation, society, health and the mind. It introduces the concept of Entropy Equilibrium as a way to quantify and define the exact nature of animate and inanimate objects. It introduces the concept of Virtual Entropy and its effect on physical systems. This book is intended to develop discussion and spur research into the concept of entropy as a way to better understand and relate with the physical world.