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Using artificial intelligence techni...

O'Connell, David John.

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Using artificial intelligence techniques to automate sewer system planning.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Using artificial intelligence techniques to automate sewer system planning./
Author:	O'Connell, David John.
Description:	112 p.
Notes:	Source: Masters Abstracts International, Volume: 46-03, page: 1582.
Contained By:	Masters Abstracts International46-03.
Subject:	Artificial Intelligence. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR33318
ISBN:	9780494333181

Using artificial intelligence techniques to automate sewer system planning.
O'Connell, David John.

Using artificial intelligence techniques to automate sewer system planning. - 112 p.

Source: Masters Abstracts International, Volume: 46-03, page: 1582.

Thesis (M.Sc.)--University of Alberta (Canada), 2007.

This thesis explores the use of computing science algorithms in sewer system automation. Related research can be separated into two subproblems; design and layout. Design determines pipe properties such as size, depth and slope. Sewer system layout specifies the topology of the pipe network. Many layout techniques consider only high-level connectivity between key neighborhood points. This thesis improves the automated layout process by finding detailed pipe and manhole positions. A set of primitive algorithms for placing a pipeline between two fixed points is developed. These primitive algorithms are used to develop two algorithms to minimize the entire neighborhood cost. The first uses a local greedy optimization heuristic to quickly generate high quality solutions. A second algorithm implements a branch-and-bound search to generate the best layout based on a set of fixed points. These algorithms are validated within a complete sewer planning prototype using a third party design module.

ISBN: 9780494333181Subjects--Topical Terms:

769149
Artificial Intelligence.

Using artificial intelligence techniques to automate sewer system planning.
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245 1 0 $a Using artificial intelligence techniques to automate sewer system planning.
300 $a 112 p.
500 $a Source: Masters Abstracts International, Volume: 46-03, page: 1582.
502 $a Thesis (M.Sc.)--University of Alberta (Canada), 2007.
520 $a This thesis explores the use of computing science algorithms in sewer system automation. Related research can be separated into two subproblems; design and layout. Design determines pipe properties such as size, depth and slope. Sewer system layout specifies the topology of the pipe network. Many layout techniques consider only high-level connectivity between key neighborhood points. This thesis improves the automated layout process by finding detailed pipe and manhole positions. A set of primitive algorithms for placing a pipeline between two fixed points is developed. These primitive algorithms are used to develop two algorithms to minimize the entire neighborhood cost. The first uses a local greedy optimization heuristic to quickly generate high quality solutions. A second algorithm implements a branch-and-bound search to generate the best layout based on a set of fixed points. These algorithms are validated within a complete sewer planning prototype using a third party design module.
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650 4 $a Engineering, Sanitary and Municipal. $3 1018731
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