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Authors:
Gene Oliver Cruz
Florencio Ballesteros, Jr.
Ariel Blanco
Keywords: artificial neural networks; genetic algorithms; land use; disaster preparedness
Abstract:
Cities are becoming more vulnerable to natural hazards due to increasing concentration of urban population and resources as well as to changing weather patterns caused by climate change. Adding to the aggravation of urban vulnerability is the socio-economic conditions of its population. More often, the poor are those who are severely affected and have no economic means to recover. Eventually, the local government takes the responsibility of providing services to restore and rehabilitate affected communities. This impacts the cities’ economic base by reducing their ability to grow and raise revenue. In order to minimize economic losses caused by a disaster, it is important to assess the communities’ vulnerabilities and plan ahead before a disaster strikes. This paper explores the use of neural networks and genetic algorithms as support tools for an integrated urban development and disaster risk reduction planning and decision making.
Pages: 79 to 82
Copyright: Copyright (c) IARIA, 2014
Publication date: March 23, 2014
Published in: conference
ISSN: 2308-4138
ISBN: 978-1-61208-325-4
Location: Barcelona, Spain
Dates: from March 23, 2014 to March 27, 2014