Journal ArticleDOI
Spatial flood susceptibility prediction in Middle Ganga Plain: comparison of frequency ratio and Shannon’s entropy models
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In this article, the authors compared results of flood susceptibility modelling in the part of Middle Ganga Plain, Ganga foreland basin, and found that 12 major flood explanatory factors were included.Abstract:
This work focuses on comparing results of flood susceptibility modelling in the part of Middle Ganga Plain, Ganga foreland basin. Following inclusivity rule, 12 major flood explanatory factors incl...read more
Citations
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Flood susceptibility modelling using advanced ensemble machine learning models
Abu Reza Md. Towfiqul Islam,Swapan Talukdar,Susanta Mahato,Sonali Kundu,Kutub Uddin Eibek,Quoc Bao Pham,Alban Kuriqi,Nguyen Thi Thuy Linh +7 more
TL;DR: The methodology and solution-oriented results presented in this paper will assist the regional as well as local authorities and the policy-makers for mitigating the risks related to floods and also help in developing appropriate mitigation measures to avoid potential damages.
Journal ArticleDOI
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India.
Aman Arora,Alireza Arabameri,Manish Pandey,Masood Ahsan Siddiqui,Uma Kant Shukla,Dieu Tien Bui,Varun Narayan Mishra,Anshuman Bhardwaj +7 more
TL;DR: Better performance of ANIFS-GA than the individual models as well as some ensemble models suggests and warrants further study in this topoclimatic environment using other classes of susceptibility models.
Journal ArticleDOI
Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms
Swapan Talukdar,Bonosri Ghose,Shahfahad,Roquia Salam,Susanta Mahato,Quoc Bao Pham,Nguyen Thi Thuy Linh,Romulus Costache,Mohammadtaghi Avand +8 more
TL;DR: In this paper, the authors developed ensembles of bagging with REPtree, random forest (RF), M5P, and random tree (RT) algorithms for obtaining reliable and highly accurate results.
Journal ArticleDOI
Flood susceptibility mapping and assessment using a novel deep learning model combining multilayer perceptron and autoencoder neural networks
Mohammad Ahmadlou,A’kif Al-Fugara,Abdel Rahman Al-Shabeeb,Aman Arora,Rida Al-Adamat,Quoc Bao Pham,Nadhir Al-Ansari,Nguyen Thi Thuy Linh,Hedieh Sajedi +8 more
TL;DR: A novel hybrid model combining the multilayer perceptron (MLP) and autoencoder models to produce the susceptibility maps for two study areas located in Iran and India suggested that the hybrid autoen coder‐MLP model outperformed the MLP model and can be used as a powerful model in other studies for flood susceptibility mapping.
References
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Journal ArticleDOI
A mathematical theory of communication
TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
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Multivariate Data Analysis
TL;DR: This book deals with probability distributions, discrete and continuous densities, distribution functions, bivariate distributions, means, variances, covariance, correlation, and some random process material.
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The meaning and use of the area under a receiver operating characteristic (ROC) curve.
TL;DR: A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented and it is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a random chosen non-diseased subject.
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Measuring the accuracy of diagnostic systems
TL;DR: For diagnostic systems used to distinguish between two classes of events, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy.
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Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
Carsten F. Dormann,Jane Elith,Sven Bacher,Carsten M. Buchmann,Gudrun Carl,Gabriel Carré,Jaime Ricardo García Márquez,Bernd Gruber,Bruno Lafourcade,Pedro J. Leitão,Tamara Münkemüller,Colin J. McClean,Patrick E. Osborne,Björn Reineking,Boris Schröder,Andrew K. Skidmore,Damaris Zurell,Sven Lautenbach +17 more
TL;DR: It was found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection and the value of GLM in combination with penalised methods and thresholds when omitted variables are considered in the final interpretation.