Artificial Intelligence and WebGIS for Disaster and Emergency Management

Rifaat Abdalla; Marwa Esmail

doi:10.1007/978-3-030-03828-1_6

Artificial Intelligence and WebGIS for Disaster and Emergency Management

Rifaat Abdalla^*, Marwa Esmail

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter

1 Citation (Scopus)

Abstract

GIS problems are often subject to what is known as curse of dimensionality, which means that the state space grows rapidly when the number of parameters increases. However, the use of intelligent algorithms reduces considerably the size of the state space and helps to quickly find the optimal configurations.

Original language	English
Title of host publication	Advances in Science, Technology and Innovation
Publisher	Springer Nature
Pages	57-62
Number of pages	6
DOIs	https://doi.org/10.1007/978-3-030-03828-1_6
Publication status	Published - 2019

Publication series

Name	Advances in Science, Technology and Innovation
ISSN (Print)	2522-8714
ISSN (Electronic)	2522-8722

Keywords

Artificial Neural Networks (ANNs)
Crisis Response Operations
Land Transformation Model (LTM)
Urban Search And Rescue (USAR)
Vast Datasets

ASJC Scopus subject areas

Architecture
Renewable Energy, Sustainability and the Environment
Environmental Chemistry

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-03828-1_6

Cite this

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title = "Artificial Intelligence and WebGIS for Disaster and Emergency Management",

abstract = "GIS problems are often subject to what is known as curse of dimensionality, which means that the state space grows rapidly when the number of parameters increases. However, the use of intelligent algorithms reduces considerably the size of the state space and helps to quickly find the optimal configurations.",

keywords = "Artificial Neural Networks (ANNs), Crisis Response Operations, Land Transformation Model (LTM), Urban Search And Rescue (USAR), Vast Datasets",

author = "Rifaat Abdalla and Marwa Esmail",

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T1 - Artificial Intelligence and WebGIS for Disaster and Emergency Management

AU - Abdalla, Rifaat

AU - Esmail, Marwa

PY - 2019

Y1 - 2019

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AB - GIS problems are often subject to what is known as curse of dimensionality, which means that the state space grows rapidly when the number of parameters increases. However, the use of intelligent algorithms reduces considerably the size of the state space and helps to quickly find the optimal configurations.

KW - Artificial Neural Networks (ANNs)

KW - Crisis Response Operations

KW - Land Transformation Model (LTM)

KW - Urban Search And Rescue (USAR)

KW - Vast Datasets

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M3 - Chapter

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T3 - Advances in Science, Technology and Innovation

SP - 57

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BT - Advances in Science, Technology and Innovation

PB - Springer Nature

ER -

Artificial Intelligence and WebGIS for Disaster and Emergency Management

Abstract

Publication series

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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