Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Transportation engineering. --- Civil engineering --- Engineering --- Transportation engineering

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Transportation Engineering: Theory, Practice and Modeling is a guide for integrating multi-modal transportation networks and assessing their potential cost and impact on society and the environment. Clear and rigorous in its coverage, the authors begin with an exposition of theory related to traffic engineering and control, transportation planning, and an evaluation of transportation alternatives that is followed by models and methods for predicting travel and freight transportation demand, analyzing existing and planning new transportation networks, and developing traffic control tactics and strategies. Written by an author team with over thirty years of experience in both research and teaching, the book incorporates both theory and practice to facilitate greener solutions. Contains worked out examples and end of the chapter questions Covers all forms of transportation engineering, including air, rail, and public transit modes Includes modeling and analytical procedures for supporting different aspects of traffic and transportation analyses Examines different transport mode sand how to make them sustainable Explains the economics of transport systems in terms of users' value of time.

Transportation engineering. --- Civil engineering.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Production engineering. --- Manufacturing engineering --- Process engineering --- Industrial engineering --- Mechanical engineering

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Civil engineering --- Civil engineering. --- Engineering --- Public works

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community’s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains

Software engineering. --- Computer software engineering --- Engineering