Transportation Planning: State of the Art

Springer Science & Business Media
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This book collects selected presentations of the Meeting of the EURO Working Group on Transportation, which took place at the Department of Ma- ematics at Chalmers University of Technology, Göteborg (or, Gothenburg), Sweden, September 9–11, 1998. [The EURO Working Group on Transpor- tion was founded at the end of the 7th EURO Summer Institute on Urban Traffic Management, which took place in Cetraro, Italy, June 21–July, 1991. There were around 30 founding members of the Working Group, a number which now has grown to around 150. Meetings since then include Paris (1993), Barcelona (1994), and Newcastle (1996). ] About 100 participants were present, enjoying healthy rain and a memorable conference dinner in the Feskekôrka. The total number of presentations at the conference was about 60, coming from quite diverse areas within the field of operations research in transportation, and covering all modes of transport: Deterministic traffic equilibrium models (6 papers) Stochastic traffic equilibrium models (5 papers) Combined traffic models (3 papers) Dynamic traffic models (7 papers) Simulation models (4 papers) Origin–destination matrix estimation (2 papers) Urban public transport models (8 papers) Aircraft scheduling (1 paper) Ship routing (2 papers) Railway planning and scheduling (6 papers) Vehicle routing (3 papers) Traffic management (3 papers) Signal control models (3 papers) Transportation systems analysis (5 papers) ix x TRANSPORTATION PLANNING Among these papers, 14 were eventually selected to be included in this volume.
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Additional Information

Publisher
Springer Science & Business Media
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Published on
Apr 18, 2006
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Pages
252
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ISBN
9780306482205
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Best For
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Language
English
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Genres
Business & Economics / Economics / General
Business & Economics / Operations Research
Business & Economics / Urban & Regional
Mathematics / Applied
Mathematics / Optimization
Political Science / Public Policy / Economic Policy
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Content Protection
This content is DRM protected.
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Michael Patriksson
John W. Foreman
Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.

But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.

Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. 

Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. 

But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.

 Each chapter will cover a different technique in a spreadsheet so you can follow along:

Mathematical optimization, including non-linear programming and genetic algorithms Clustering via k-means, spherical k-means, and graph modularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, and bag-of-words models Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation Moving from spreadsheets into the R programming language

You get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

Michael Patriksson
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