Stochastic Modeling: A Thorough Guide to Evaluate, Pre-Process, Model and Compare Time Series with MATLAB Software allows for new avenues in time series analysis and predictive modeling which summarize more than ten years of experience in the application of stochastic models in environmental problems. The book introduces a variety of different topics in time series in the modeling and prediction of complex environmental systems. Most importantly, all codes are user-friendly and readers will be able to use them for their cases. Users who may not be familiar with MATLAB software can also refer to the appendix. This book also guides the reader step-by-step to learn developed codes for time series modeling, provides required toolboxes, explains concepts, and applies different tools for different types of environmental time series problems. - Provides video tutorials on the use of codes - Includes a companion site with 3,000 lines of programming, 70 principal codes and 100 pseudo codes - Highlights multiple methods to Illustrate each problem
Machine Learning in Earth, Environmental and Planetary Sciences: Theoretical and Practical Applications is a practical guide on implementing different variety of extreme learning machine algorithms to Earth and environmental data. The book provides guided examples using real-world data for numerous novel and mathematically detailed machine learning techniques that can be applied in Earth, environmental, and planetary sciences, including detailed MATLAB coding coupled with line-by-line descriptions of the advantages and limitations of each method. The book also presents common postprocessing techniques required for correct data interpretation. This book provides students, academics, and researchers with detailed understanding of how machine learning algorithms can be applied to solve real case problems, how to prepare data, and how to interpret the results. - Describes how to develop different schemes of machine learning techniques and apply to Earth, environmental and planetary data - Provides detailed, guided line-by-line examples using real-world data, including the appropriate MATLAB codes - Includes numerous figures, illustrations and tables to help readers better understand the concepts covered
Decision-making is a key factor to achieve success in any discipline, especially in a field like civil engineering, which is based on calculations and requires large amounts of information being taken into account. Most processes and procedures are a compendium of many different tasks and requirements specific to each project under development, and making decisions in such environments can often be an arduous endeavor. That is why the need for analytical criteria capable of assisting with untangling complex scenarios has arisen preponderantly. As an all-encompassing resource, Multicriteria Decision-Making Analysis for Civil Engineering Applications facilitates civil engineers by outlining state-of-the-art techniques for quantitative decision-making to optimally select the appropriate approach when faced with operational issues or to prioritize among multiple options. Authored by recognized experts in the field, this book proves to be a balanced reference volume that is essential not just for civil engineers, but also for a wide variety of audiences in interconnected disciplines. - Presents a systematic framework of methodological solutions helping readers to make decisions quickly and accurately - Features several real-life case studies that support understanding and provide reliable actionable guidance - Includes the theoretical underpinnings of decision support tools and emphasizes multicriteria decision analysis techniques applied to civil engineering projects - Offers civil engineers a structured approach to tackle complex decisions and establish priorities in their projects - Is accompanied by an online companion site that includes Excel worksheets, demonstrating step-by-step processes, numerical simulations, and worked-out examples
Numerical Simulation of Effluent Discharges: Applications with OpenFOAM provides a resource for understanding the effluent discharge mechanisms and the approaches for modeling them. It bridges the gap between academia and industry with a focused approach in CFD modeling and providing practical examples and applications. With a detailed discussion on performing numerical modeling of effluent discharges in various ambient waters and with different discharge configurations, the book covers the application of OpenFOAM in effluent discharge modeling. Features: Discusses effluent discharges into various ambient waters with different discharge configurations. Focuses on numerical modeling of effluent discharges. Covers the fundamentals in predicting the mixing characteristics of effluents resulting from desalination plants. Reviews the past CFD studies on the effluent discharge modeling thoroughly. Provides guidance to researchers and engineers on the future steps in modeling of effluent discharges. Includes an introduction to OpenFOAM and its application in effluent discharge modeling. The book will benefit both academics and professional engineers practicing in the area of environmental fluid mechanics and working on the effluent discharge modeling. Chapter 3 of this book is available for free in PDF format as Open Access from the individual product page at www.routledge.com. It has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.
Machine Learning in Earth, Environmental and Planetary Sciences: Theoretical and Practical Applications is a practical guide on implementing different variety of extreme learning machine algorithms to Earth and environmental data. The book provides guided examples using real-world data for numerous novel and mathematically detailed machine learning techniques that can be applied in Earth, environmental, and planetary sciences, including detailed MATLAB coding coupled with line-by-line descriptions of the advantages and limitations of each method. The book also presents common postprocessing techniques required for correct data interpretation. This book provides students, academics, and researchers with detailed understanding of how machine learning algorithms can be applied to solve real case problems, how to prepare data, and how to interpret the results. - Describes how to develop different schemes of machine learning techniques and apply to Earth, environmental and planetary data - Provides detailed, guided line-by-line examples using real-world data, including the appropriate MATLAB codes - Includes numerous figures, illustrations and tables to help readers better understand the concepts covered
Stochastic Modeling: A Thorough Guide to Evaluate, Pre-Process, Model and Compare Time Series with MATLAB Software allows for new avenues in time series analysis and predictive modeling which summarize more than ten years of experience in the application of stochastic models in environmental problems. The book introduces a variety of different topics in time series in the modeling and prediction of complex environmental systems. Most importantly, all codes are user-friendly and readers will be able to use them for their cases. Users who may not be familiar with MATLAB software can also refer to the appendix. This book also guides the reader step-by-step to learn developed codes for time series modeling, provides required toolboxes, explains concepts, and applies different tools for different types of environmental time series problems. - Provides video tutorials on the use of codes - Includes a companion site with 3,000 lines of programming, 70 principal codes and 100 pseudo codes - Highlights multiple methods to Illustrate each problem
Decision-making is a key factor to achieve success in any discipline, especially in a field like civil engineering, which is based on calculations and requires large amounts of information being taken into account. Most processes and procedures are a compendium of many different tasks and requirements specific to each project under development, and making decisions in such environments can often be an arduous endeavor. That is why the need for analytical criteria capable of assisting with untangling complex scenarios has arisen preponderantly. As an all-encompassing resource, Multicriteria Decision-Making Analysis for Civil Engineering Applications facilitates civil engineers by outlining state-of-the-art techniques for quantitative decision-making to optimally select the appropriate approach when faced with operational issues or to prioritize among multiple options. Authored by recognized experts in the field, this book proves to be a balanced reference volume that is essential not just for civil engineers, but also for a wide variety of audiences in interconnected disciplines. - Presents a systematic framework of methodological solutions helping readers to make decisions quickly and accurately - Features several real-life case studies that support understanding and provide reliable actionable guidance - Includes the theoretical underpinnings of decision support tools and emphasizes multicriteria decision analysis techniques applied to civil engineering projects - Offers civil engineers a structured approach to tackle complex decisions and establish priorities in their projects - Is accompanied by an online companion site that includes Excel worksheets, demonstrating step-by-step processes, numerical simulations, and worked-out examples
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.