Search: WFRF:(Torabi Haghighi A.) >
Development of a no...
Development of a novel hybrid multi-boosting neural network model for spatial prediction of urban flood
-
- Darabi, H. (author)
- University of Oulu
-
- Rahmati, O. (author)
- Agricultural Research Education And Extention Organization
-
- Naghibi, Seyed Amir (author)
- Lund University,Lunds universitet,Avdelningen för Teknisk vattenresurslära,Institutionen för bygg- och miljöteknologi,Institutioner vid LTH,Lunds Tekniska Högskola,Centrum för Mellanösternstudier (CMES),Samhällsvetenskapliga institutioner och centrumbildningar,Samhällsvetenskapliga fakulteten,LTH profilområde: Vatten,LTH profilområden,Division of Water Resources Engineering,Department of Building and Environmental Technology,Departments at LTH,Faculty of Engineering, LTH,Centre for Advanced Middle Eastern Studies (CMES),Departments of Administrative, Economic and Social Sciences,Faculty of Social Sciences,LTH Profile Area: Water,LTH Profile areas,Faculty of Engineering, LTH
-
show more...
-
- Mohammadi, F. (author)
- University of Tehran
-
- Ahmadisharaf, E. (author)
- DHI Denmark
-
- Kalantari, Zahra (author)
- Stockholm University,Stockholms universitet,KTH,Hållbar utveckling, miljövetenskap och teknik,Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden,Institutionen för naturgeografi,KTH Royal Institute of Technology, Sweden
-
Torabi Haghighi, A. (author)
-
- Soleimanpour, S. M. (author)
- Fars Agricultural and Natural Resources Research and Education Center
-
- Tiefenbacher, J. P. (author)
- Texas State University
-
- Tien Bui, D. (author)
- University of South-Eastern Norway
-
show less...
-
(creator_code:org_t)
- 2021-05-13
- 2021
- English.
-
In: Geocarto International. - : Taylor and Francis Ltd.. - 1010-6049 .- 1752-0762.
- Related links:
-
https://doi.org/10.1...
-
show more...
-
https://www.tandfonl...
-
http://dx.doi.org/10... (free)
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
https://urn.kb.se/re...
-
https://lup.lub.lu.s...
-
show less...
Abstract
Subject headings
Close
- In this study, a new hybridized machine learning algorithm for urban flood susceptibility mapping, named MultiB-MLPNN, was developed using a multi-boosting technique and MLPNN. The model was tested in Amol City, Iran, a data-scarce city in an ungauged area which is prone to severe flood inundation events and currently lacks flood prevention infrastructure. Performance of the hybridized model was compared with that of a standalone MLPNN model, random forest and boosted regression trees. Area under the curve, efficiency, true skill statistic, Matthews correlation coefficient, misclassification rate, sensitivity and specificity were used to evaluate model performance. In validation, the MultiB-MLPNN model showed the best predictive performance. The hybridized MultiB-MLPNN model is thus useful for generating realistic flood susceptibility maps for data-scarce urban areas. The maps can be used to develop risk-reduction measures to protect urban areas from devastating floods, particularly where available data are insufficient to support physically based hydrological or hydraulic models.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Vattenteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Water Engineering (hsv//eng)
- NATURVETENSKAP -- Geovetenskap och miljövetenskap -- Oceanografi, hydrologi och vattenresurser (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences -- Oceanography, Hydrology and Water Resources (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Geoteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Geotechnical Engineering (hsv//eng)
- NATURVETENSKAP -- Geovetenskap och miljövetenskap (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering (hsv//eng)
Keyword
- artificial intelligence
- boosting
- GIS
- neural networks
- Urban planning
Publication and Content Type
- ref (subject category)
- art (subject category)
Find in a library
To the university's database
- By the author/editor
-
Darabi, H.
-
Rahmati, O.
-
Naghibi, Seyed A ...
-
Mohammadi, F.
-
Ahmadisharaf, E.
-
Kalantari, Zahra
-
show more...
-
Torabi Haghighi, ...
-
Soleimanpour, S. ...
-
Tiefenbacher, J. ...
-
Tien Bui, D.
-
show less...
- About the subject
-
- ENGINEERING AND TECHNOLOGY
-
ENGINEERING AND ...
-
and Civil Engineerin ...
-
and Water Engineerin ...
-
- NATURAL SCIENCES
-
NATURAL SCIENCES
-
and Earth and Relate ...
-
and Oceanography Hyd ...
-
- ENGINEERING AND TECHNOLOGY
-
ENGINEERING AND ...
-
and Civil Engineerin ...
-
and Geotechnical Eng ...
-
- NATURAL SCIENCES
-
NATURAL SCIENCES
-
and Earth and Relate ...
-
- ENGINEERING AND TECHNOLOGY
-
ENGINEERING AND ...
-
and Civil Engineerin ...
- Articles in the publication
-
Geocarto Interna ...
- By the university
-
Royal Institute of Technology
-
Stockholm University
-
Lund University