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Título : Spatial Statistics and Modeling Tipo de documento: documento electrónico Autores: Gaetan, Carlo ; SpringerLink (Online service) ; Guyon, Xavier Editorial: New York, NY : Springer New York Fecha de publicación: 2010 Colección: Springer Series in Statistics, ISSN 0172-7397 Número de páginas: XIV, 302 p Il.: online resource ISBN/ISSN/DL: 978-0-387-92257-7 Idioma : Inglés (eng) Palabras clave: Mathematics Earth sciences Probabilities Statistics Environmental Econometrics Probability Theory and Stochastic Processes Statistical Methods Sciences, general Math. Appl. in Science Clasificación: 51 Matemáticas Resumen: Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete. The most important statistical methods and their asymptotic properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation). A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in probability and mathematical statistics is assumed, three appendices introduce some necessary background. The book is accessible to senior undergraduate students with a solid math background and Ph.D. students in statistics. Furthermore, experienced statisticians and researchers in the above-mentioned fields will find the book valuable as a mathematically sound reference. This book is the English translation of Modélisation et Statistique Spatiales published by Springer in the series Mathématiques & Applications, a series established by Société de Mathématiques Appliquées et Industrielles (SMAI). Carlo Gaetan is Associate Professor of Statistics in the Department of Statistics at the Ca' Foscari University of Venice. Xavier Guyon is Professor Emeritus at the University of Paris 1 Panthéon-Sorbonne. He is author of a Springer monograph on random fields Nota de contenido: Second-order spatial models and geostatistics -- Gibbs-Markov random fields on networks -- Spatial point processes -- Simulation of spatial models -- Statistics for spatial models En línea: http://dx.doi.org/10.1007/978-0-387-92257-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33524 Spatial Statistics and Modeling [documento electrónico] / Gaetan, Carlo ; SpringerLink (Online service) ; Guyon, Xavier . - New York, NY : Springer New York, 2010 . - XIV, 302 p : online resource. - (Springer Series in Statistics, ISSN 0172-7397) .
ISBN : 978-0-387-92257-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Earth sciences Probabilities Statistics Environmental Econometrics Probability Theory and Stochastic Processes Statistical Methods Sciences, general Math. Appl. in Science Clasificación: 51 Matemáticas Resumen: Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete. The most important statistical methods and their asymptotic properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation). A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in probability and mathematical statistics is assumed, three appendices introduce some necessary background. The book is accessible to senior undergraduate students with a solid math background and Ph.D. students in statistics. Furthermore, experienced statisticians and researchers in the above-mentioned fields will find the book valuable as a mathematically sound reference. This book is the English translation of Modélisation et Statistique Spatiales published by Springer in the series Mathématiques & Applications, a series established by Société de Mathématiques Appliquées et Industrielles (SMAI). Carlo Gaetan is Associate Professor of Statistics in the Department of Statistics at the Ca' Foscari University of Venice. Xavier Guyon is Professor Emeritus at the University of Paris 1 Panthéon-Sorbonne. He is author of a Springer monograph on random fields Nota de contenido: Second-order spatial models and geostatistics -- Gibbs-Markov random fields on networks -- Spatial point processes -- Simulation of spatial models -- Statistics for spatial models En línea: http://dx.doi.org/10.1007/978-0-387-92257-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33524 Ejemplares
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Título : An Intermediate Course in Probability Tipo de documento: documento electrónico Autores: Gut, Allan ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2009 Colección: Springer Texts in Statistics, ISSN 1431-875X Número de páginas: XV, 303 p Il.: online resource ISBN/ISSN/DL: 978-1-4419-0162-0 Idioma : Inglés (eng) Palabras clave: Mathematics Computers Mathematical statistics Life sciences Probabilities Statistics Environmental Probability Theory and Stochastic Processes Sciences, general of Computation Statistical Methods in Computer Science Math. Appl. Clasificación: 51 Matemáticas Resumen: The purpose of this book is to provide the reader with a solid background and understanding of the basic results and methods in probability theory before entering into more advanced courses. The first six chapters focus on some central areas of what might be called pure probability theory: multivariate random variables, conditioning, transforms, order variables, the multivariate normal distribution, and convergence. A final chapter is devoted to the Poisson process as a means both to introduce stochastic processes and to apply many of the techniques introduced earlier in the text. Students are assumed to have taken a first course in probability, though no knowledge of measure theory is assumed. Throughout, the presentation is thorough and includes many examples that are discussed in detail. Thus, students considering more advanced research in probability theory will benefit from this wide-ranging survey of the subject that provides them with a foretaste of the subject's many treasures. The present second edition offers updated content, one hundred additional problems for solution, and a new chapter that provides an outlook on further areas and topics, such as stable distributions and domains of attraction, extreme value theory and records, and martingales. The main idea is that this chapter may serve as an appetizer to the more advanced theory. Allan Gut is Professor of Mathematical Statistics at Uppsala University, Uppsala, Sweden. He is a member of the International Statistical Institute, the Bernoulli Society, the Institute of Mathematical Statistics, and the Swedish Statistical Society. He is an Associate Editor of the Journal of Statistical Planning and Inference and Sequential Analysis, a former Associate Editor of the Scandinavian Journal of Statistics, and the author of five other books including Probability: A Graduate Course (Springer, 2005) and Stopped Random Walks: Limit Theorems and Applications, Second Edition (Springer, 2009) Nota de contenido: Multivariate Random Variables -- Conditioning -- Transforms -- Order Statistics -- The Multivariate Normal Distribution -- Convergence -- An Outlook on Further Topics -- The Poisson Process En línea: http://dx.doi.org/10.1007/978-1-4419-0162-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33966 An Intermediate Course in Probability [documento electrónico] / Gut, Allan ; SpringerLink (Online service) . - New York, NY : Springer New York, 2009 . - XV, 303 p : online resource. - (Springer Texts in Statistics, ISSN 1431-875X) .
ISBN : 978-1-4419-0162-0
Idioma : Inglés (eng)
Palabras clave: Mathematics Computers Mathematical statistics Life sciences Probabilities Statistics Environmental Probability Theory and Stochastic Processes Sciences, general of Computation Statistical Methods in Computer Science Math. Appl. Clasificación: 51 Matemáticas Resumen: The purpose of this book is to provide the reader with a solid background and understanding of the basic results and methods in probability theory before entering into more advanced courses. The first six chapters focus on some central areas of what might be called pure probability theory: multivariate random variables, conditioning, transforms, order variables, the multivariate normal distribution, and convergence. A final chapter is devoted to the Poisson process as a means both to introduce stochastic processes and to apply many of the techniques introduced earlier in the text. Students are assumed to have taken a first course in probability, though no knowledge of measure theory is assumed. Throughout, the presentation is thorough and includes many examples that are discussed in detail. Thus, students considering more advanced research in probability theory will benefit from this wide-ranging survey of the subject that provides them with a foretaste of the subject's many treasures. The present second edition offers updated content, one hundred additional problems for solution, and a new chapter that provides an outlook on further areas and topics, such as stable distributions and domains of attraction, extreme value theory and records, and martingales. The main idea is that this chapter may serve as an appetizer to the more advanced theory. Allan Gut is Professor of Mathematical Statistics at Uppsala University, Uppsala, Sweden. He is a member of the International Statistical Institute, the Bernoulli Society, the Institute of Mathematical Statistics, and the Swedish Statistical Society. He is an Associate Editor of the Journal of Statistical Planning and Inference and Sequential Analysis, a former Associate Editor of the Scandinavian Journal of Statistics, and the author of five other books including Probability: A Graduate Course (Springer, 2005) and Stopped Random Walks: Limit Theorems and Applications, Second Edition (Springer, 2009) Nota de contenido: Multivariate Random Variables -- Conditioning -- Transforms -- Order Statistics -- The Multivariate Normal Distribution -- Convergence -- An Outlook on Further Topics -- The Poisson Process En línea: http://dx.doi.org/10.1007/978-1-4419-0162-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33966 Ejemplares
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Título : Applied Mathematical Demography Tipo de documento: documento electrónico Autores: Keyfitz, Nathan ; SpringerLink (Online service) ; Caswell, Hal Editorial: New York, NY : Springer New York Fecha de publicación: 2005 Colección: Statistics for Biology and Health, ISSN 1431-8776 Número de páginas: XXVI, 558 p. 74 illus Il.: online resource ISBN/ISSN/DL: 978-0-387-27409-6 Idioma : Inglés (eng) Palabras clave: Social sciences Ecology Biomathematics Statistics Environmental Demography Sciences Math. Appl. in Science for Life Sciences, Medicine, Health Science, Behavorial Education, Public Policy, and Law Mathematical Computational Biology Clasificación: 51 Matemáticas Resumen: The third edition of this classic text maintains its focus on applications of demographic models, while extending its scope to matrix models for stage-classified populations. The authors first introduce the life table to describe age-specific mortality, and then use it to develop theory for stable populations and the rate of population increase. This theory is then revisited in the context of matrix models, for stage-classified as well as age-classified populations. Reproductive value and the stable equivalent population are introduced in both contexts, and Markov chain methods are presented to describe the movement of individuals through the life cycle. Applications of mathematical demography to population projection and forecasting, kinship, microdemography, heterogeneity, and multi-state models are considered. The new edition maintains and extends the book’s focus on the consequences of changes in the vital rates. Methods are presented for calculating the sensitivity and elasticity of population growth rate, life expectancy, stable stage distribution, and reproductive value, and for applying those results in comparative studies. Stage-classified models are important in both human demography and population ecology, and this edition features examples from both human and non-human populations. In short, this third edition enlarges considerably the scope and power of demography. It will be an essential resource for students and researchers in demography and in animal and plant population ecology. Nathan Keyfitz is Professor Emeritus of Sociology at Harvard University. After holding positions at Canada’s Dominion Bureau of Statistics, the University of Chicago, and the University of California at Berkeley, he became Andelot Professor of Sociology and Demography at Harvard in 1972. After retiring from Harvard, he became Director of the Population Program at the International Institute for Applied Systems Analysis (IIASA) in Vienna from 1983 to 1993. Keyfitz is a member of the U.S. National Academy of Sciences and the Royal Society of Canada, and a Fellow of the American Academy of Arts and Sciences. He has received the Mindel Sheps Award of the Population Association of America and the Lazarsfeld Award of the American Sociological Association, and was the 1997 Laureate of the International Union for the Scientific Study of Population. He has written 12 books, including Introduction to the Mathematics of Population (1968) and, with Fr. Wilhelm Flieger, SVD, World Population Growth and Aging: Demographic Trends in the Late Twentieth Century (1990). Hal Caswell is a Senior Scientist in the Biology Department of the Woods Hole Oceanographic Institution, where he holds the Robert W. Morse Chair for Excellence in Oceanography. He is a Fellow of the American Academy of Arts and Sciences. He has held a Maclaurin Fellowship from the New Zealand Institute of Mathematics and its Applications and a John Simon Guggenheim Memorial Fellowship. His research focuses on mathematical population ecology with applications in conservation biology. He is the author of Matrix Population Models: Construction, Analysis, and Interpretation (2001). Nota de contenido: Introduction: Population Without Age -- The Life Table -- The Matrix Model Framework -- Mortality Comparisons; The Male-Female Ratio -- Fixed Regime of Mortality and Fertility: The Uses of Stable Theory -- Birth and Population Increase from the Life Table -- Birth and Population Increase from Matrix Population Models -- Reproductive Value from the Life Table -- Reproductive Value from Matrix Models -- Understanding Population Characteristics -- Markov Chains for Individual Life Histories -- Projection and Forecasting -- Perturbation Analysis of Matrix Models -- Some Types of Instability -- The Demographic Theory of Kinship -- Microdemography -- The Multi-State Model -- Family Demography -- Heterogeneity and Selection in Population Analysis -- Epilogue: How Do We Know the Facts of Demography? En línea: http://dx.doi.org/10.1007/b139042 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35118 Applied Mathematical Demography [documento electrónico] / Keyfitz, Nathan ; SpringerLink (Online service) ; Caswell, Hal . - New York, NY : Springer New York, 2005 . - XXVI, 558 p. 74 illus : online resource. - (Statistics for Biology and Health, ISSN 1431-8776) .
ISBN : 978-0-387-27409-6
Idioma : Inglés (eng)
Palabras clave: Social sciences Ecology Biomathematics Statistics Environmental Demography Sciences Math. Appl. in Science for Life Sciences, Medicine, Health Science, Behavorial Education, Public Policy, and Law Mathematical Computational Biology Clasificación: 51 Matemáticas Resumen: The third edition of this classic text maintains its focus on applications of demographic models, while extending its scope to matrix models for stage-classified populations. The authors first introduce the life table to describe age-specific mortality, and then use it to develop theory for stable populations and the rate of population increase. This theory is then revisited in the context of matrix models, for stage-classified as well as age-classified populations. Reproductive value and the stable equivalent population are introduced in both contexts, and Markov chain methods are presented to describe the movement of individuals through the life cycle. Applications of mathematical demography to population projection and forecasting, kinship, microdemography, heterogeneity, and multi-state models are considered. The new edition maintains and extends the book’s focus on the consequences of changes in the vital rates. Methods are presented for calculating the sensitivity and elasticity of population growth rate, life expectancy, stable stage distribution, and reproductive value, and for applying those results in comparative studies. Stage-classified models are important in both human demography and population ecology, and this edition features examples from both human and non-human populations. In short, this third edition enlarges considerably the scope and power of demography. It will be an essential resource for students and researchers in demography and in animal and plant population ecology. Nathan Keyfitz is Professor Emeritus of Sociology at Harvard University. After holding positions at Canada’s Dominion Bureau of Statistics, the University of Chicago, and the University of California at Berkeley, he became Andelot Professor of Sociology and Demography at Harvard in 1972. After retiring from Harvard, he became Director of the Population Program at the International Institute for Applied Systems Analysis (IIASA) in Vienna from 1983 to 1993. Keyfitz is a member of the U.S. National Academy of Sciences and the Royal Society of Canada, and a Fellow of the American Academy of Arts and Sciences. He has received the Mindel Sheps Award of the Population Association of America and the Lazarsfeld Award of the American Sociological Association, and was the 1997 Laureate of the International Union for the Scientific Study of Population. He has written 12 books, including Introduction to the Mathematics of Population (1968) and, with Fr. Wilhelm Flieger, SVD, World Population Growth and Aging: Demographic Trends in the Late Twentieth Century (1990). Hal Caswell is a Senior Scientist in the Biology Department of the Woods Hole Oceanographic Institution, where he holds the Robert W. Morse Chair for Excellence in Oceanography. He is a Fellow of the American Academy of Arts and Sciences. He has held a Maclaurin Fellowship from the New Zealand Institute of Mathematics and its Applications and a John Simon Guggenheim Memorial Fellowship. His research focuses on mathematical population ecology with applications in conservation biology. He is the author of Matrix Population Models: Construction, Analysis, and Interpretation (2001). Nota de contenido: Introduction: Population Without Age -- The Life Table -- The Matrix Model Framework -- Mortality Comparisons; The Male-Female Ratio -- Fixed Regime of Mortality and Fertility: The Uses of Stable Theory -- Birth and Population Increase from the Life Table -- Birth and Population Increase from Matrix Population Models -- Reproductive Value from the Life Table -- Reproductive Value from Matrix Models -- Understanding Population Characteristics -- Markov Chains for Individual Life Histories -- Projection and Forecasting -- Perturbation Analysis of Matrix Models -- Some Types of Instability -- The Demographic Theory of Kinship -- Microdemography -- The Multi-State Model -- Family Demography -- Heterogeneity and Selection in Population Analysis -- Epilogue: How Do We Know the Facts of Demography? En línea: http://dx.doi.org/10.1007/b139042 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35118 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar Aspects of Mathematical Modelling / SpringerLink (Online service) ; Hosking, Roger J ; Venturino, Ezio (2008)
Título : Aspects of Mathematical Modelling : Applications in Science, Medicine, Economics and Management Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Hosking, Roger J ; Venturino, Ezio Editorial: Basel : Birkhäuser Basel Fecha de publicación: 2008 Colección: Mathematics and Biosciences in Interaction Número de páginas: VIII, 375 p Il.: online resource ISBN/ISSN/DL: 978-3-7643-8591-0 Idioma : Inglés (eng) Palabras clave: Mathematics Computer simulation Biomathematics Environmental sciences Mathematical and Computational Biology Math. Appl. in Science Simulation Modeling Clasificación: 51 Matemáticas Resumen: The construction of mathematical models is an essential scientific activity. Mathematics has long been associated with developments in the exact sciences and engineering, but more recently mathematical modelling has been used to investigate complex systems that arise in many other fields. The contributors to this book demonstrate the application of mathematics to modern research topics in ecology and environmental science, health and medicine, phylogenetics and neural networks, theoretical chemistry, economics and management. The reader will find some review papers outlining current research directions in hot topics such as pattern formation and applications to medicine, and more targeted research papers on current developments in the various disciplines included. Both should provide insight and inspiration for further work on these subjects. The extensive relevant literature cited in some of the survey expository articles is another feature Nota de contenido: Mathematical Models of Pattern Formation in Planktonic Predation-Diffusion Systems: A Review -- Toward a General Theory of Ecosystem Stability: Plankton-Nutrient Interaction as a Paradigm -- Nutrient, Non-toxic Phytoplankton, Toxic Phytoplankton and Zooplankton Interaction in an Open Marine System -- Stability and Optimal Harvesting in a Stage Structure Predator-Prey Switching Strategy -- Insecticidal Bt Crops Under Massive Bt-resistant Pest Invasion: Mathematical Simulation -- Reducing the Emission of Pollutants in Industrial Wastewater through the Use of Membrane Bioreactors -- Model Hysteresis Dimer Molecule. I. Equilibrium Properties -- Model Hysteresis Dimer Molecule. II. Deductions from Probability Profiles -- Mathematical Modelling and Simulation of Coronary Blood Flow -- Modelling Vaccine Protocols -- Modelling the Response of Intracranial Pressure to Microgravity Environments -- “Noisy Oncology”: Some Caveats in using Gaussian Noise in Mathematical Models of Chemotherapy -- Phylogenetic Analysis, Split Systems and Boolean Functions -- Exponential Convergence Analysis of DCNNs having Unbounded Activations and Inhibitory Self-Connections -- The Single-Vendor Multi-Buyer Integrated Inventory Problem: an Heuristic Solution Technique -- A Term Structured Volatility Model of Poll Data and its Application to Election Timing -- Estimation for the Semiparametric Transformation Model under General Censorship -- Integer Programming Models of Bookmobile Routing -- Instability and Sustained Oscillations in Neo-Classical Growth Models with Unemployment -- A Bass-type Model for a Dynamic Market with Logistic Growth -- A Wavelet Neural Network applied to Textile Spinning En línea: http://dx.doi.org/10.1007/978-3-7643-8591-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34395 Aspects of Mathematical Modelling : Applications in Science, Medicine, Economics and Management [documento electrónico] / SpringerLink (Online service) ; Hosking, Roger J ; Venturino, Ezio . - Basel : Birkhäuser Basel, 2008 . - VIII, 375 p : online resource. - (Mathematics and Biosciences in Interaction) .
ISBN : 978-3-7643-8591-0
Idioma : Inglés (eng)
Palabras clave: Mathematics Computer simulation Biomathematics Environmental sciences Mathematical and Computational Biology Math. Appl. in Science Simulation Modeling Clasificación: 51 Matemáticas Resumen: The construction of mathematical models is an essential scientific activity. Mathematics has long been associated with developments in the exact sciences and engineering, but more recently mathematical modelling has been used to investigate complex systems that arise in many other fields. The contributors to this book demonstrate the application of mathematics to modern research topics in ecology and environmental science, health and medicine, phylogenetics and neural networks, theoretical chemistry, economics and management. The reader will find some review papers outlining current research directions in hot topics such as pattern formation and applications to medicine, and more targeted research papers on current developments in the various disciplines included. Both should provide insight and inspiration for further work on these subjects. The extensive relevant literature cited in some of the survey expository articles is another feature Nota de contenido: Mathematical Models of Pattern Formation in Planktonic Predation-Diffusion Systems: A Review -- Toward a General Theory of Ecosystem Stability: Plankton-Nutrient Interaction as a Paradigm -- Nutrient, Non-toxic Phytoplankton, Toxic Phytoplankton and Zooplankton Interaction in an Open Marine System -- Stability and Optimal Harvesting in a Stage Structure Predator-Prey Switching Strategy -- Insecticidal Bt Crops Under Massive Bt-resistant Pest Invasion: Mathematical Simulation -- Reducing the Emission of Pollutants in Industrial Wastewater through the Use of Membrane Bioreactors -- Model Hysteresis Dimer Molecule. I. Equilibrium Properties -- Model Hysteresis Dimer Molecule. II. Deductions from Probability Profiles -- Mathematical Modelling and Simulation of Coronary Blood Flow -- Modelling Vaccine Protocols -- Modelling the Response of Intracranial Pressure to Microgravity Environments -- “Noisy Oncology”: Some Caveats in using Gaussian Noise in Mathematical Models of Chemotherapy -- Phylogenetic Analysis, Split Systems and Boolean Functions -- Exponential Convergence Analysis of DCNNs having Unbounded Activations and Inhibitory Self-Connections -- The Single-Vendor Multi-Buyer Integrated Inventory Problem: an Heuristic Solution Technique -- A Term Structured Volatility Model of Poll Data and its Application to Election Timing -- Estimation for the Semiparametric Transformation Model under General Censorship -- Integer Programming Models of Bookmobile Routing -- Instability and Sustained Oscillations in Neo-Classical Growth Models with Unemployment -- A Bass-type Model for a Dynamic Market with Logistic Growth -- A Wavelet Neural Network applied to Textile Spinning En línea: http://dx.doi.org/10.1007/978-3-7643-8591-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34395 Ejemplares
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Título : Data Mining in Agriculture Tipo de documento: documento electrónico Autores: Mucherino, Antonio ; SpringerLink (Online service) ; Papajorgji, Petraq J ; Pardalos, Panos M Editorial: New York, NY : Springer New York Fecha de publicación: 2009 Colección: Springer Optimization and Its Applications, ISSN 1931-6828 num. 34 Número de páginas: XVIII, 274 p. 92 illus Il.: online resource ISBN/ISSN/DL: 978-0-387-88615-2 Idioma : Inglés (eng) Palabras clave: Mathematics Data mining Agriculture Mathematical models Operations research Management science Environmental sciences Modeling and Industrial Mining Knowledge Discovery Research, Science Math. Appl. in Clasificación: 51 Matemáticas Resumen: Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in MATLAB®. Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given. Also by P.J. Papajorgji and P.M. Pardalos: Advances in Modeling Agricultural Systems, 'Springer Optimization and its Applications' vol. 25, ©2009 Nota de contenido: to Data Mining -- Statistical Based Approaches -- Clustering by -means -- -Nearest Neighbor Classification -- Artificial Neural Networks -- Support Vector Machines -- Biclustering -- Validation -- Data Mining in a Parallel Environment -- Solutions to Exercises En línea: http://dx.doi.org/10.1007/978-0-387-88615-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33912 Data Mining in Agriculture [documento electrónico] / Mucherino, Antonio ; SpringerLink (Online service) ; Papajorgji, Petraq J ; Pardalos, Panos M . - New York, NY : Springer New York, 2009 . - XVIII, 274 p. 92 illus : online resource. - (Springer Optimization and Its Applications, ISSN 1931-6828; 34) .
ISBN : 978-0-387-88615-2
Idioma : Inglés (eng)
Palabras clave: Mathematics Data mining Agriculture Mathematical models Operations research Management science Environmental sciences Modeling and Industrial Mining Knowledge Discovery Research, Science Math. Appl. in Clasificación: 51 Matemáticas Resumen: Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in MATLAB®. Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given. Also by P.J. Papajorgji and P.M. Pardalos: Advances in Modeling Agricultural Systems, 'Springer Optimization and its Applications' vol. 25, ©2009 Nota de contenido: to Data Mining -- Statistical Based Approaches -- Clustering by -means -- -Nearest Neighbor Classification -- Artificial Neural Networks -- Support Vector Machines -- Biclustering -- Validation -- Data Mining in a Parallel Environment -- Solutions to Exercises En línea: http://dx.doi.org/10.1007/978-0-387-88615-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33912 Ejemplares
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