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_id	315caadria2004
id	315caadria2004
authors	Kuo-Chung Wen, Wei-Lung Chen
year	2004
title	Application of Genetic Algorithms to Establish Flooding Evacuation Path Model in Metropolitan Area
doi	https://doi.org/10.52842/conf.caadria.2004.557
source	CAADRIA 2004 [Proceedings of the 9th International Conference on Computer Aided Architectural Design Research in Asia / ISBN 89-7141-648-3] Seoul Korea 28-30 April 2004, pp. 557-570
summary	This research has shown the difficulties associated with the GIS and the flooding evacuation path search through the huge searching space generated during the network analysis process. This research also presents an approach to these problems by utilizing a search process whose concept is derived from natural genetics. Genetic algorithms (GAs) have been introduced in the optimization problem solving area by Holland (1975) and Goldberg (1989) and have shown their usefulness through numerous applications. We apply GA and GIS to choice flooding evacuation path in metropolitan area in this study. We take the region of Shiji city in Taiwan for case. That could be divided into four parts. First, is to set the population of GA operation. Second, is to choose crossover and mutation. Third, is to calculate the fitness function of each generation and to select the better gene arrangement. Fourth, is to reproduce, after evolution, we can establish Flooding Evacuation Path that more reflect really human action and choice when flood takes place. However we can apply GA to calculate different evacuation path in different time series. Final, we compare and establish real model of evacuation path model to choosing flooding evacuation path.
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	7a2a
authors	Minsky, M.
year	1975
title	A framework for representing knowledge
source	P.H. Winston (ed.), The Psychology of Computer Vision, McGraw-Hill, New York, pp. 211-277
summary	Briefly describes frame systems as a formalism for representing knowledge and then concentrates on the issue of what the content of knowledge should be in specific domains. Argues that vision should be viewed symbolically with an emphasis on forming expectations and then using details to fill in slots in those expectations. Discusses the enormous problem of the volume of background common sense knowledge required to understand even very simple natural language texts and suggests that networks of frames are a reasonable approach to represent such knowledge. Discusses the concept of expectation further including ways to adapt to and understand expectation failures. Argues that numerical approaches to knowledge representation are inherently limited.
series	other
email
last changed	2003/04/23 15:14

_id	ddss2004_d-63
id	ddss2004_d-63
authors	Wen, K.-C. and W.-L. Chen
year	2004
title	Applying Genetic Algorithms to Establish Disaster Decision Support System for Flooding Evacuation Path of Hsichih Area in Taiwan
source	Van Leeuwen, J.P. and H.J.P. Timmermans (eds.) Developments in Design & Decision Support Systems in Architecture and Urban Planning, Eindhoven: Eindhoven University of Technology, ISBN 90-6814-155-4, p. 63-75
summary	Because of the special geography features and subtropics weather in Taiwan, we need to provide correct information to help people making decision when they are in disaster. So the disaster decision support system must offer proper information of evacuation path to people. This research has shown the difficulties associated with the GIS and the flooding evacuation path search through the huge searching space generated during the network analysis process. This research also presents an approach to these problems by utilizing a search process whose concept is derived from natural genetics. Genetic algorithms (GAs) have been introduced in the optimization problem solving area by Holland (1975) and Goldberg (1989) and have shown their usefulness through numerous applications. We apply GA and GIS to choice flooding evacuation path in metropolitan area in this study. We take the region of Shiji city in Taiwan for case. Firstly, we establish the node relationship of GA calculation, the level of the weight is the standard of the date that is exported by Disaster Database. Secondly, we apply GA to calculate different evacuation path in different time series. Finally, we build the model of choosing flooding evacuation path.
keywords	Genetic Algorithms, Decision Support System, GIS, Evacuation Path
series	DDSS
last changed	2004/07/03 22:13

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