Yu Lei – författare

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14 produkter

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14 produkter

Introduction to Combinatorial Testing
AvYu Lei,Raghu N. Kackerm. fl.
E-bok
Engelska, 2016
1 291 kr
Läs direkt efter köp
Combinatorial testing of software analyzes interactions among variables using a very small number of tests. This advanced approach has demonstrated success in providing strong, low-cost testing in real-world situations. Introduction to Combinatorial Testing presents a complete self-contained tutorial on advanced combinatorial testing methods for re
Introduction to Combinatorial Testing
AvD. Richard Kuhn,Raghu N. Kackerm. fl.
Häftad, Engelska, 2013
1 120 kr
Skickas inom 10-15 vardagar
Combinatorial testing of software analyzes interactions among variables using a very small number of tests. This advanced approach has demonstrated success in providing strong, low-cost testing in real-world situations. Introduction to Combinatorial Testing presents a complete self-contained tutorial on advanced combinatorial testing methods for real-world software.The book introduces key concepts and procedures of combinatorial testing, explains how to use software tools for generating combinatorial tests, and shows how this approach can be integrated with existing practice. Detailed explanations and examples clarify how and why to use various techniques. Sections on cost and practical considerations describe tradeoffs and limitations that may impact resources or funding. While the authors introduce some of the theory and mathematics of combinatorial methods, readers can use the methods without in-depth knowledge of the underlying mathematics.Accessible to undergraduate students and researchers in computer science and engineering, this book illustrates the practical application of combinatorial methods in software testing. Giving pointers to freely available tools and offering resources on a supplementary website, the book encourages readers to apply these methods in their own testing projects.
Introduction to Combinatorial Testing
AvYu Lei,Raghu N. Kackerm. fl.
E-bok
PDF, Engelska, 2016
1 295 kr
Läs direkt efter köp
Combinatorial testing of software analyzes interactions among variables using a very small number of tests. This advanced approach has demonstrated success in providing strong, low-cost testing in real-world situations. Introduction to Combinatorial Testing presents a complete self-contained tutorial on advanced combinatorial testing methods for re
Statistical Analysis &quote;In Focus&quote;
Alternate Guides for R, SAS, and Stata for Statistics for the Behavioral Sciences
AvYu Lei,Kristin Lee Sotakm. fl.
E-bok
Engelska, 2017
646 kr
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Statistical Analysis "In Focus" supports users of Gregory J. Privitera’s Statistics for the Behavioral Sciences, Third Edition who work with a statistical program other than SPSS or Excel. Three standalone parts, each dedicated to R, SAS, and Stata, serve as step-by-step guides for completing the "In Focus" exercises in Privitera’s core text. A conversational writing style along with "To The Student" introductions allow students to familiarize themselves and become more comfortable with each program prior to making computations. Additionally, General Instruction Guidebook (GIG) sections for R, SAS, and Stata provide standardized how-to instructions for using each program, making the book a valuable reference for students beyond their studies.
Essential Statistical Analysis &quote;In Focus&quote;
Alternate Guides for R, SAS, and Stata for Essential Statistics for the Behavioral Sciences
AvYu Lei,Kristin Lee Sotakm. fl.
E-bok
Engelska, 2018
660 kr
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Essentials of Statistical Analysis "In Focus" supports users of Gregory J. Privitera’s Essential Statistics for the Behavioral Sciences, Second Edition who work with a statistical program other than SPSS® or Excel®. Three standalone parts, each dedicated to R, SAS®, and Stata®, serve as step-by-step guides for completing the "In Focus" exercises in Privitera’s core text. A conversational writing style along with "To The Student" introductions allow students to familiarize themselves and become more comfortable with each program prior to making computations. Additionally, General Instruction Guidebook (GIG) sections for R, SAS®, and Stata® provide standardized how-to instructions for using each program, making the book a valuable reference for students beyond their studies.
Computational Intelligence for Network Structure Analytics
AvMaoguo Gong,Qing Caim. fl.
Inbunden, Engelska, 2017
1 086 kr
Skickas inom 10-15 vardagar
This book presents the latest research advances in complex network structure analytics based on computational intelligence (CI) approaches, particularly evolutionary optimization. Most if not all network issues are actually optimization problems, which are mostly NP-hard and challenge conventional optimization techniques. To effectively and efficiently solve these hard optimization problems, CI based network structure analytics offer significant advantages over conventional network analytics techniques. Meanwhile, using CI techniques may facilitate smart decision making by providing multiple options to choose from, while conventional methods can only offer a decision maker a single suggestion. In addition, CI based network structure analytics can greatly facilitate network modeling and analysis. And employing CI techniques to resolve network issues is likely to inspire other fields of study such as recommender systems, system biology, etc., which will in turn expand CI’s scope and applications.As a comprehensive text, the book covers a range of key topics, including network community discovery, evolutionary optimization, network structure balance analytics, network robustness analytics, community-based personalized recommendation, influence maximization, and biological network alignment.Offering a rich blend of theory and practice, the book is suitable for students, researchers and practitioners interested in network analytics and computational intelligence, both as a textbook and as a reference work.
Computational Intelligence for Network Structure Analytics
AvYu Lei,Shanfeng Wangm. fl.
E-bok
Engelska, 2017
1 413 kr
Läs direkt efter köp
This book presents the latest research advances in complex network structure analytics based on computational intelligence (CI) approaches, particularly evolutionary optimization. Most if not all network issues are actually optimization problems, which are mostly NP-hard and challenge conventional optimization techniques. To effectively and efficiently solve these hard optimization problems, CI based network structure analytics offer significant advantages over conventional network analytics techniques. Meanwhile, using CI techniques may facilitate smart decision making by providing multiple options to choose from, while conventional methods can only offer a decision maker a single suggestion. In addition, CI based network structure analytics can greatly facilitate network modeling and analysis. And employing CI techniques to resolve network issues is likely to inspire other fields of study such as recommender systems, system biology, etc., which will in turn expand CI’s scope and applications.As a comprehensive text, the book covers a range of key topics, including network community discovery, evolutionary optimization, network structure balance analytics, network robustness analytics, community-based personalized recommendation, influence maximization, and biological network alignment.Offering a rich blend of theory and practice, the book is suitable for students, researchers and practitioners interested in network analytics and computational intelligence, both as a textbook and as a reference work.
Computational Intelligence for Network Structure Analytics
AvMaoguo Gong,Qing Caim. fl.
Häftad, Engelska, 2018
1 086 kr
Skickas inom 10-15 vardagar
This book presents the latest research advances in complex network structure analytics based on computational intelligence (CI) approaches, particularly evolutionary optimization. Most if not all network issues are actually optimization problems, which are mostly NP-hard and challenge conventional optimization techniques. To effectively and efficiently solve these hard optimization problems, CI based network structure analytics offer significant advantages over conventional network analytics techniques. Meanwhile, using CI techniques may facilitate smart decision making by providing multiple options to choose from, while conventional methods can only offer a decision maker a single suggestion. In addition, CI based network structure analytics can greatly facilitate network modeling and analysis. And employing CI techniques to resolve network issues is likely to inspire other fields of study such as recommender systems, system biology, etc., which will in turn expand CI’s scope and applications.As a comprehensive text, the book covers a range of key topics, including network community discovery, evolutionary optimization, network structure balance analytics, network robustness analytics, community-based personalized recommendation, influence maximization, and biological network alignment.Offering a rich blend of theory and practice, the book is suitable for students, researchers and practitioners interested in network analytics and computational intelligence, both as a textbook and as a reference work.
Glance at the Silk Road Disaster Risk
AvPeng Cui,Yu Lei
Inbunden, Engelska, 2022
1 626 kr
Skickas inom 10-15 vardagar
This book vividly shows the fostering environment, activity characteristics, distribution pattern, economic losses, casualties, disaster risks and management of earthquakes, mass movement, drought, floods, and marine disasters in the Silk Road region. It develops a multi-scale and multi-disaster risk assessment method to better assess and understand the Silk Road disaster risk. A multi-level collaborative risk management model has been proposed for transboundary disasters, and it also shares case studies on major disaster risk management. The book makes a major step forward to increase the understanding of the disaster risk of the Silk Road region. It presents a holistic understanding of the natural hazards and their induced disaster risks and is a valuable read for scholars, stakeholders and practitioners in the DRR community.
Glance at the Silk Road Disaster Risk
AvYu Lei,Peng Cui
E-bok
Engelska, 2022
2 044 kr
Läs direkt efter köp
This book vividly shows the fostering environment, activity characteristics, distribution pattern, economic losses, casualties, disaster risks and management of earthquakes, mass movement, drought, floods, and marine disasters in the Silk Road region. It develops a multi-scale and multi-disaster risk assessment method to better assess and understand the Silk Road disaster risk. A multi-level collaborative risk management model has been proposed for transboundary disasters, and it also shares case studies on major disaster risk management. The book makes a major step forward to increase the understanding of the disaster risk of the Silk Road region. It presents a holistic understanding of the natural hazards and their induced disaster risks and is a valuable read for scholars, stakeholders and practitioners in the DRR community.
Glance at the Silk Road Disaster Risk
AvPeng Cui,Yu Lei
Häftad, Engelska, 2023
1 626 kr
Skickas inom 10-15 vardagar
This book vividly shows the fostering environment, activity characteristics, distribution pattern, economic losses, casualties, disaster risks and management of earthquakes, mass movement, drought, floods, and marine disasters in the Silk Road region. It develops a multi-scale and multi-disaster risk assessment method to better assess and understand the Silk Road disaster risk. A multi-level collaborative risk management model has been proposed for transboundary disasters, and it also shares case studies on major disaster risk management. The book makes a major step forward to increase the understanding of the disaster risk of the Silk Road region. It presents a holistic understanding of the natural hazards and their induced disaster risks and is a valuable read for scholars, stakeholders and practitioners in the DRR community.
Nyhet
Computational Intelligence for Remote Sensing Image Change Detection
AvJiao Shi,Yu Leim. fl.
Häftad, Engelska, 2026
547 kr
Skickas inom 5-8 vardagar
Nowadays, remote sensing systems and technologies have been widely studied and applied in environmental monitoring, land survey, and disaster management. As a pivotal remote sensing task, change detection aims to identify and quantify spatio-temporal changes using multi-temporal imagery, supporting timely decision-making and sustainable resource planning. Nevertheless, conventional change detection approaches remain limited in addressing challenges including sensitivity to noise, discrepancies in spatial resolution, sensor misalignment, and the fusion of multi-source heterogeneous data. To address these issues, advanced computational intelligence (CI) techniques, particularly deep learning and evolutionary computation, are being increasingly adopted, offering improved robustness and adaptability for modern change detection tasks.This book establishes the first systematic framework of CI-driven methodologies in remote sensing change detection, providing a comprehensive exposition spanning theoretical foundations, algorithmic innovation, and empirical validation. Opening with the research principles of remote sensing change detection and core CI theories, it covers CI-driven methodologies tailored to homogeneous (e.g., single-sensor time series) and heterogeneous (e.g., cross-sensor) paradigms. These methodologies address domain-critical challenges such as noise robustness, feature space alignment, and multi-source fusion through rigorously designed technical workflows that cover data preprocessing, adaptive model learning, and task-specific network architecture. Extensive validation across diverse remote sensing data types—including synthetic aperture radar, optical, multispectral, and hyperspectral imagery—empirically confirms the operational efficacy of these methodologies in delivering accurate and robust change monitoring. By bridging theory and practice, this book empowers readers to formulate complex problems, develop robust models, and apply cutting-edge CI techniques to remote sensing change detection tasks. It is ideal for researchers and engineers working at the intersection of remote sensing, machine learning, and computational intelligence who seek practical and scalable solutions for change detection in evolving environments.
Nyhet
Computational Intelligence for Remote Sensing Image Change Detection
AvNan Zhang,Maoguo Gongm. fl.
E-bok
Engelska, 2026
710 kr
Läs direkt efter köp
Nowadays, remote sensing systems and technologies have been widely studied and applied in environmental monitoring, land survey, and disaster management. As a pivotal remote sensing task, change detection aims to identify and quantify spatio-temporal changes using multi-temporal imagery, supporting timely decision-making and sustainable resource planning. Nevertheless, conventional change detection approaches remain limited in addressing challenges including sensitivity to noise, discrepancies in spatial resolution, sensor misalignment, and the fusion of multi-source heterogeneous data. To address these issues, advanced computational intelligence (CI) techniques, particularly deep learning and evolutionary computation, are being increasingly adopted, offering improved robustness and adaptability for modern change detection tasks.This book establishes the first systematic framework of CI-driven methodologies in remote sensing change detection, providing a comprehensive exposition spanning theoretical foundations, algorithmic innovation, and empirical validation. Opening with the research principles of remote sensing change detection and core CI theories, it covers CI-driven methodologies tailored to homogeneous (e.g., single-sensor time series) and heterogeneous (e.g., cross-sensor) paradigms. These methodologies address domain-critical challenges such as noise robustness, feature space alignment, and multi-source fusion through rigorously designed technical workflows that cover data preprocessing, adaptive model learning, and task-specific network architecture. Extensive validation across diverse remote sensing data types—including synthetic aperture radar, optical, multispectral, and hyperspectral imagery—empirically confirms the operational efficacy of these methodologies in delivering accurate and robust change monitoring. By bridging theory and practice, this book empowers readers to formulate complex problems, develop robust models, and apply cutting-edge CI techniques to remote sensing change detection tasks. It is ideal for researchers and engineers working at the intersection of remote sensing, machine learning, and computational intelligence who seek practical and scalable solutions for change detection in evolving environments.
Purple Clay Teapot Art of Wang Yufang
AvConnie Yuanting Wu,Yu Lei
Inbunden, Engelska, 2011
268 kr
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Yu Lei – författare

Introduction to Combinatorial Testing

Introduction to Combinatorial Testing

Introduction to Combinatorial Testing

Statistical Analysis &quote;In Focus&quote;

Essential Statistical Analysis &quote;In Focus&quote;

Computational Intelligence for Network Structure Analytics

Computational Intelligence for Network Structure Analytics

Computational Intelligence for Network Structure Analytics

Glance at the Silk Road Disaster Risk

Glance at the Silk Road Disaster Risk

Glance at the Silk Road Disaster Risk

Computational Intelligence for Remote Sensing Image Change Detection

Computational Intelligence for Remote Sensing Image Change Detection

Purple Clay Teapot Art of Wang Yufang

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