東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Using artificial intelligence techni...

O'Connell, David John.

FindBook

Google Book

Amazon

博客來

Using artificial intelligence techniques to automate sewer system planning.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Using artificial intelligence techniques to automate sewer system planning./
作者:	O'Connell, David John.
面頁冊數:	112 p.
附註:	Source: Masters Abstracts International, Volume: 46-03, page: 1582.
Contained By:	Masters Abstracts International46-03.
標題:	Artificial Intelligence. -
電子資源:	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.
LDR:01802nam 2200265 a 45 001 959039
005 20110704
008 110704s2007 ||||||||||||||||| ||eng d
020 $a 9780494333181
035 $a (UMI)AAIMR33318
035 $a AAIMR33318
040 $a UMI $c UMI
100 1 $a O'Connell, David John. $3 1282507
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.
590 $a School code: 0351.
650 4 $a Artificial Intelligence. $3 769149
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, Sanitary and Municipal. $3 1018731
690 $a 0554
690 $a 0800
690 $a 0984
710 2 $a University of Alberta (Canada). $3 626651
773 0 $t Masters Abstracts International $g 46-03.
790 $a 0351
791 $a M.Sc.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR33318