Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)

Landslides are one of the most aggressive natural disasters that cause loss of lives and of billions dollars in damages annually worldwide. They pose a threat to the safety of human lives, the environment, resources and property. It is one of the natural disasters that occur quite often in Malays...

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Main Author:	Shabib Hussien Alkhasawneh, Mutasem
Format:	Thesis
Language:	English
Published:	2015
Subjects:	TK1-9971 Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.usm.my/46579/1/Pages%20from%20Improvement%20Of%20Landslide%20Prediction%20System%20Based%20On%20Hybrid%20Neural%20Networks%20%28Penang%20Island%2C%20Malaysia%29%2024%20PAGE.pdf
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id	my-usm-ep.46579
record_format	uketd_dc
spelling	my-usm-ep.465792020-06-19T02:05:03Z Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia) 2015-01 Shabib Hussien Alkhasawneh, Mutasem TK1-9971 Electrical engineering. Electronics. Nuclear engineering Landslides are one of the most aggressive natural disasters that cause loss of lives and of billions dollars in damages annually worldwide. They pose a threat to the safety of human lives, the environment, resources and property. It is one of the natural disasters that occur quite often in Malaysia and particularly in Penang Island during heavy rainy seasons. Numerous researches on landslides studies have been done based on Penang Island. However, many issues seriously related to landslides have not been solved yet. These issues include the extraction of new factors which cause landslides, investigation on the optimum factors which cause landslides and the generation of an accurate landslide hazard map for Penang island. In addition to that, the landslide hazard prediction intelligent system, either for Penang Island or for the entire world is still being investigated up to this date. For that reason, an intelligent landslide hazard mapping system is proposed. It consists of three stages: factor extraction, factor selection and Artificial Neural Network (ANNs) as an analysis tool. Twenty one factors are used in this study where nine factors were collected from different governmental agents. The rest of the factors (twelve) were extracted from the Digital Elevation Models (DEM), seven of these factors were extracted and used for the first time on Penang Island. In the factor selection phase. six factor selection techniques are employed to select the most important factors in the landslide prediction. 2015-01 Thesis http://eprints.usm.my/46579/ http://eprints.usm.my/46579/1/Pages%20from%20Improvement%20Of%20Landslide%20Prediction%20System%20Based%20On%20Hybrid%20Neural%20Networks%20%28Penang%20Island%2C%20Malaysia%29%2024%20PAGE.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik & Elektronik ( School of Electrical & Electronic Engineering)
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	TK1-9971 Electrical engineering Electronics Nuclear engineering
spellingShingle	TK1-9971 Electrical engineering Electronics Nuclear engineering Shabib Hussien Alkhasawneh, Mutasem Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)
description	Landslides are one of the most aggressive natural disasters that cause loss of lives and of billions dollars in damages annually worldwide. They pose a threat to the safety of human lives, the environment, resources and property. It is one of the natural disasters that occur quite often in Malaysia and particularly in Penang Island during heavy rainy seasons. Numerous researches on landslides studies have been done based on Penang Island. However, many issues seriously related to landslides have not been solved yet. These issues include the extraction of new factors which cause landslides, investigation on the optimum factors which cause landslides and the generation of an accurate landslide hazard map for Penang island. In addition to that, the landslide hazard prediction intelligent system, either for Penang Island or for the entire world is still being investigated up to this date. For that reason, an intelligent landslide hazard mapping system is proposed. It consists of three stages: factor extraction, factor selection and Artificial Neural Network (ANNs) as an analysis tool. Twenty one factors are used in this study where nine factors were collected from different governmental agents. The rest of the factors (twelve) were extracted from the Digital Elevation Models (DEM), seven of these factors were extracted and used for the first time on Penang Island. In the factor selection phase. six factor selection techniques are employed to select the most important factors in the landslide prediction.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Shabib Hussien Alkhasawneh, Mutasem
author_facet	Shabib Hussien Alkhasawneh, Mutasem
author_sort	Shabib Hussien Alkhasawneh, Mutasem
title	Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)
title_short	Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)
title_full	Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)
title_fullStr	Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)
title_full_unstemmed	Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)
title_sort	improvement of landslide prediction system based on hybrid neural networks (penang island, malaysia)
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Elektrik & Elektronik ( School of Electrical & Electronic Engineering)
publishDate	2015
url	http://eprints.usm.my/46579/1/Pages%20from%20Improvement%20Of%20Landslide%20Prediction%20System%20Based%20On%20Hybrid%20Neural%20Networks%20%28Penang%20Island%2C%20Malaysia%29%2024%20PAGE.pdf
_version_	1747821689601785856

Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)

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