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Author: Shahab Araghinejad Publisher: Springer Science & Business Media ISBN: 9400775067 Category : Science Languages : en Pages : 292
Book Description
“Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important theories and applications of data-driven models and uses them to deal with a wide range of problems in the field of water resources and environmental engineering such as hydrological forecasting, flood analysis, water quality monitoring, regionalizing climatic data, and general function approximation. The book presents the statistical-based models including basic statistical analysis, nonparametric and logistic regression methods, time series analysis and modeling, and support vector machines. It also deals with the analysis and modeling based on artificial intelligence techniques including static and dynamic neural networks, statistical neural networks, fuzzy inference systems, and fuzzy regression. The book also discusses hybrid models as well as multi-model data fusion to wrap up the covered models and techniques. The source files of relatively simple and advanced programs demonstrating how to use the models are presented together with practical advice on how to best apply them. The programs, which have been developed using the MATLAB® unified platform, can be found on extras.springer.com. The main audience of this book includes graduate students in water resources engineering, environmental engineering, agricultural engineering, and natural resources engineering. This book may be adapted for use as a senior undergraduate and graduate textbook by focusing on selected topics. Alternatively, it may also be used as a valuable resource book for practicing engineers, consulting engineers, scientists and others involved in water resources and environmental engineering.
Author: Shahab Araghinejad Publisher: Springer Science & Business Media ISBN: 9400775067 Category : Science Languages : en Pages : 292
Book Description
“Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important theories and applications of data-driven models and uses them to deal with a wide range of problems in the field of water resources and environmental engineering such as hydrological forecasting, flood analysis, water quality monitoring, regionalizing climatic data, and general function approximation. The book presents the statistical-based models including basic statistical analysis, nonparametric and logistic regression methods, time series analysis and modeling, and support vector machines. It also deals with the analysis and modeling based on artificial intelligence techniques including static and dynamic neural networks, statistical neural networks, fuzzy inference systems, and fuzzy regression. The book also discusses hybrid models as well as multi-model data fusion to wrap up the covered models and techniques. The source files of relatively simple and advanced programs demonstrating how to use the models are presented together with practical advice on how to best apply them. The programs, which have been developed using the MATLAB® unified platform, can be found on extras.springer.com. The main audience of this book includes graduate students in water resources engineering, environmental engineering, agricultural engineering, and natural resources engineering. This book may be adapted for use as a senior undergraduate and graduate textbook by focusing on selected topics. Alternatively, it may also be used as a valuable resource book for practicing engineers, consulting engineers, scientists and others involved in water resources and environmental engineering.
Author: Saeid Eslamian Publisher: CRC Press ISBN: 1315404206 Category : Science Languages : en Pages : 800
Book Description
This volume include over 30 chapters, written by experts from around the world. It examines drought and all of the fundamental principles relating to drought and water scarcity. It includes coverage of the causes of drought, occurences, preparations, drought vulnerability assessments, societal implications, and more.
Author: Jiří Hřebíček Publisher: Springer ISBN: 331989935X Category : Computers Languages : en Pages : 486
Book Description
This book constitutes the refereed proceedings of the 12th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2017, held in Zadar, Croatia, in May 2017. The 35 revised full papers presented together with 4 keynote lectures were carefully reviewed and selected from 46 submissions. The papers deal with environmental challenges and try to provide solutions using forward-looking and leading-edge IT technology. They are organized in the following topical sections: air and climate; water and hydrosphere; health and biosphere; risk and disaster management; information systems; and modelling, visualization and decision support.
Author: Martin H. Trauth Publisher: Springer Nature ISBN: 3030384411 Category : Science Languages : en Pages : 526
Book Description
MATLAB® is used in a wide range of geoscientific applications, e.g. for image processing in remote sensing, for creating and processing digital elevation models, and for analyzing time series. This book introduces readers to MATLAB-based data analysis methods used in the geosciences, including basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data, and image analysis. The revised and updated Fifth Edition includes seven new sections, and the majority of the chapters have been rewritten and significantly expanded. New sections include error analysis, the problem of classical linear regression of log-transformed data, aligning stratigraphic sequences, the Normalized Difference Vegetation Index, Aitchison’s log-ratio transformation, graphical representation of spherical data, and statistics of spherical data. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.
Author: Dinesh G. Harkut Publisher: BoD – Books on Demand ISBN: 1839680830 Category : Computers Languages : en Pages : 120
Book Description
Data assimilation is a process of fusing data with a model for the singular purpose of estimating unknown variables. It can be used, for example, to predict the evolution of the atmosphere at a given point and time. This book examines data assimilation methods including Kalman filtering, artificial intelligence, neural networks, machine learning, and cognitive computing.
Author: Renji Remesan Publisher: Springer ISBN: 3319092359 Category : Science Languages : en Pages : 250
Book Description
This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.
Author: Jay Doorga Publisher: Springer Nature ISBN: 3030952134 Category : Technology & Engineering Languages : en Pages : 84
Book Description
This book provides a comprehensive guide on how geographic information systems (GIS) can be used to optimize solar energy resources. A collection of the latest cutting-edge research is presented which seeks to address the most pressing issues faced by policymakers regarding the planning and exploitation of solar energy. Scientifically robust models are developed to guide researchers on identifying optimum sites for the implementation of solar energy projects. Each methodology presented is accompanied by global case studies, ranging from the small islands of Hawaii and Mauritius to larger countries such as India and Spain. This book is primarily targeted to researchers aspiring to unveil and optimize the solar resource potential of their countries for the benefit of a wider audience, ranging from architects, agro-industrialists, climatologists, and energy experts.
Author: Borko Furht Publisher: Springer ISBN: 3319445502 Category : Computers Languages : en Pages : 400
Book Description
The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.
Author: K.W. Hipel Publisher: Elsevier ISBN: 0080870368 Category : Technology & Engineering Languages : en Pages : 1053
Book Description
This is a comprehensive presentation of the theory and practice of time series modelling of environmental systems. A variety of time series models are explained and illustrated, including ARMA (autoregressive-moving average), nonstationary, long memory, three families of seasonal, multiple input-single output, intervention and multivariate ARMA models. Other topics in environmetrics covered in this book include time series analysis in decision making, estimating missing observations, simulation, the Hurst phenomenon, forecasting experiments and causality. Professionals working in fields overlapping with environmetrics - such as water resources engineers, environmental scientists, hydrologists, geophysicists, geographers, earth scientists and planners - will find this book a valuable resource. Equally, environmetrics, systems scientists, economists, mechanical engineers, chemical engineers, and management scientists will find the time series methods presented in this book useful.
Author: Shahab Araghinejad
Author: Shahab Araghinejad
Author: Abedalrazq Fathy Khalil
Author: Saeid Eslamian
Author: Jiří Hřebíček
Author: Martin H. Trauth
Author: Dinesh G. Harkut
Author: Renji Remesan
Author: Jay Doorga
Author: Borko Furht
Author: K.W. Hipel