Assessment of rainfall-induced sediment disasters due to sloping field development

Yie Ruey Chen; Shun Chieh Hsieh; Ying Shiu Chen; Jing Wen Chen; Yiwen Hui

Assessment of rainfall-induced sediment disasters due to sloping field development

Yie Ruey Chen, Shun Chieh Hsieh, Ying Shiu Chen, Jing Wen Chen, Yiwen Hui

Department of Civil Engineering

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

Abstract

In this research, artificial neural network and genetic algorithms are used to classify satellite images and evaluate influencing factors of slope l and development for sediment disasters due to heavy raining in eastern Taiwan. With the application of geographic information system as a working platform, potential map for sediment disaster with high success rate are made and can used in practice.

Original language	English
Title of host publication	The Proceedings of the 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE
Pages	85-89
Number of pages	5
Publication status	Published - 2009
Event	19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE - Osaka, Japan Duration: 2009 Jun 21 → 2009 Jun 26

Publication series

Name	Proceedings of the International Offshore and Polar Engineering Conference
ISSN (Print)	1098-6189
ISSN (Electronic)	1555-1792

Other

Other	19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE
Country/Territory	Japan
City	Osaka
Period	09-06-21 → 09-06-26

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Ocean Engineering
Mechanical Engineering

Cite this

@inproceedings{2e808ef5043244e2b441279746b4c8a4,

title = "Assessment of rainfall-induced sediment disasters due to sloping field development",

abstract = "In this research, artificial neural network and genetic algorithms are used to classify satellite images and evaluate influencing factors of slope l and development for sediment disasters due to heavy raining in eastern Taiwan. With the application of geographic information system as a working platform, potential map for sediment disaster with high success rate are made and can used in practice.",

author = "Chen, {Yie Ruey} and Hsieh, {Shun Chieh} and Chen, {Ying Shiu} and Chen, {Jing Wen} and Yiwen Hui",

year = "2009",

language = "English",

isbn = "9781880653531",

series = "Proceedings of the International Offshore and Polar Engineering Conference",

pages = "85--89",

booktitle = "The Proceedings of the 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE",

note = "19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE ; Conference date: 21-06-2009 Through 26-06-2009",

}

Chen, YR, Hsieh, SC, Chen, YS, Chen, JW & Hui, Y 2009, Assessment of rainfall-induced sediment disasters due to sloping field development. in The Proceedings of the 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE. Proceedings of the International Offshore and Polar Engineering Conference, pp. 85-89, 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE, Osaka, Japan, 09-06-21.

Assessment of rainfall-induced sediment disasters due to sloping field development. / Chen, Yie Ruey; Hsieh, Shun Chieh; Chen, Ying Shiu et al.

The Proceedings of the 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE. 2009. p. 85-89 (Proceedings of the International Offshore and Polar Engineering Conference).

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

TY - GEN

T1 - Assessment of rainfall-induced sediment disasters due to sloping field development

AU - Chen, Yie Ruey

AU - Hsieh, Shun Chieh

AU - Chen, Ying Shiu

AU - Chen, Jing Wen

AU - Hui, Yiwen

PY - 2009

Y1 - 2009

N2 - In this research, artificial neural network and genetic algorithms are used to classify satellite images and evaluate influencing factors of slope l and development for sediment disasters due to heavy raining in eastern Taiwan. With the application of geographic information system as a working platform, potential map for sediment disaster with high success rate are made and can used in practice.

AB - In this research, artificial neural network and genetic algorithms are used to classify satellite images and evaluate influencing factors of slope l and development for sediment disasters due to heavy raining in eastern Taiwan. With the application of geographic information system as a working platform, potential map for sediment disaster with high success rate are made and can used in practice.

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M3 - Conference contribution

AN - SCOPUS:74549203869

SN - 9781880653531

T3 - Proceedings of the International Offshore and Polar Engineering Conference

SP - 85

EP - 89

BT - The Proceedings of the 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE

T2 - 19th (2009) International OFFSHORE AND POLAR ENGINEERING CONFERENCE

Y2 - 21 June 2009 through 26 June 2009

ER -

Assessment of rainfall-induced sediment disasters due to sloping field development

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

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