Paper Info
Title
A Novel Swarm Intelligence-Harris Hawks Optimization for Spatial Assessment of Landslide Susceptibility.
Abstract
In this research, the novel metaheuristic algorithm Harris hawks optimization (HHO) is applied to landslide susceptibility analysis in Western Iran. To this end, the HHO is synthesized with an artificial neural network (ANN) to optimize its performance. A spatial database comprising 208 historical landslides, as well as 14 landslide conditioning factors-elevation, slope aspect, plan curvature, profile curvature, soil type, lithology, distance to the river, distance to the road, distance to the fault, land cover, slope degree, stream power index (SPI), topographic wetness index (TWI), and rainfall-is prepared to develop the ANN and HHO-ANN predictive tools. Mean square error and mean absolute error criteria are defined to measure the performance error of the models, and area under the receiving operating characteristic curve (AUROC) is used to evaluate the accuracy of the generated susceptibility maps. The findings showed that the HHO algorithm effectively improved the performance of ANN in both recognizing (AUROC(ANN) = 0.731 and AUROC(HHO-ANN) = 0.777) and predicting (AUROC(ANN) = 0.720 and AUROC(HHO-ANN) = 0.773) the landslide pattern.
Year
DOI
Venue
2019
10.3390/s19163590
SENSORS
Keywords
Field
DocType
landslide susceptibility mapping,GIS,artificial neural network,Harris hawks optimization
Topographic Wetness Index,Pattern recognition,Swarm intelligence,Mean squared error,Electronic engineering,Landslide,Artificial intelligence,Engineering,Artificial neural network,Land cover,Spatial database,Metaheuristic
Journal
Volume
Issue
ISSN
19
16
1424-8220
Citations 
PageRank 
References 
10
0.48
0
Authors
7
Name
Order
Citations
PageRank
Dieu Tien Bui114127.86
Hossein Moayedi217618.49
Bahareh Kalantar3217.16
Abdolreza Osouli4130.93
Biswajeet Pradhan532656.54
Hoang Nguyen6427.49
Ahmad Safuan A Rashid7110.85