Maio 2014 vol. 1 num. 1 - 10th World Congress on Computational Mechanics
Full Article - Open Access.
A COMPARATIVE ASSESSMENT OF NEURAL NETWORK, FUZZY AND NEURO-FUZZY APPROACHES FOR LANDSLIDE SUSCEPTIBILITY ZONATION IN GARHWAL HIMALAYAS
Availability of accurate and objective landslide susceptibility maps depicting zones defined on the basis of probability of occurrence of landslides is one of the critical inputs in assessing risk to property and lives in any mountainous region, particularly in the Himalayas. The aim of this study is to assess the utility of soft computing tools, namely, neural network, fuzzy and neuro-fuzzy approaches for for landslide susceptibility zonation and risk assessment in a rigorous mountainous terrain in India.
Palavras-chave: Landslide Susceptibility Zonation, Artificial Neural Network, Fuzzy Set,
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Arora, M. K.; Chauhan, S.; Sharma, M.; "A COMPARATIVE ASSESSMENT OF NEURAL NETWORK, FUZZY AND NEURO-FUZZY APPROACHES FOR LANDSLIDE SUSCEPTIBILITY ZONATION IN GARHWAL HIMALAYAS", p. 4519-4536 . In: In Proceedings of the 10th World Congress on Computational Mechanics [= Blucher Mechanical Engineering Proceedings, v. 1, n. 1].
São Paulo: Blucher,
ISSN 2358-0828, DOI 10.5151/meceng-wccm2012-19943
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