Intra-Storm Pattern Recognition through Fuzzy Clustering

Autor: Konstantinos Vantas, Epaminondas Sidiropoulos

Publikováno v: Hydrology, Vol 8, Iss 2, p 57 (2021)

The identification and recognition of temporal rainfall patterns is important and useful not only for climatological studies, but mainly for supporting rainfall–runoff modeling and water resources management. Clustering techniques applied to rainfa

Externí odkaz: https://doaj.org/article/213d1734cb2e494d88686a3085d3291d

Soil erosion modelling: A global review and statistical analysis

Autor: Pasquale Borrelli, Christine Alewell, Pablo Alvarez, Jamil Alexandre Ayach Anache, Jantiene Baartman, Cristiano Ballabio, Nejc Bezak, Marcella Biddoccu, Artemi Cerdà, Devraj Chalise, Songchao Chen, Walter Chen, Anna Maria De Girolamo, Gizaw Desta Gessesse, Detlef Deumlich, Nazzareno Diodato, Nikolaos Efthimiou, Gunay Erpul, Peter Fiener, Michele Freppaz, Francesco Gentile, Andreas Gericke, Nigussie Haregeweyn, Bifeng Hu, Amelie Jeanneau, Konstantinos Kaffas, Mahboobeh Kiani-Harchegani, Ivan Lizaga Villuendas, Changjia Li, Luigi Lombardo, Manuel López-Vicente, Manuel Esteban Lucas-Borja, Michael Märker, Chiyuan Miao, Matjaž Mikoš, Sirio Modugno, Markus Möller, Victoria Naipal, Mark Nearing, Stephen Owusu, Dinesh Panday, Edouard Patault, Cristian Valeriu Patriche, Laura Poggio, Raquel Portes, Laura Quijano, Mohammad Reza Rahdari, Mohammed Renima, Giovanni Francesco Ricci, Jesús Rodrigo-Comino, Sergio Saia, Aliakbar Nazari Samani, Calogero Schillaci, Vasileios Syrris, Hyuck Soo Kim, Diogo Noses Spinola, Paulo Tarso Oliveira, Hongfen Teng, Resham Thapa, Konstantinos Vantas, Diana Vieira, Jae Yang, Shuiqing Yin, Demetrio Zema, Guangju Zhao, Panos Panagos

To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling 1994-2017. Our aim was to identify (i) processes and models m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c6ea75e3c5a9dc12a1b205b65462dec5
https://doi.org/10.31223/x5gs3t

Knowledge discovery using clustering analysis of rainfall timeseries

Autor: Konstantinos Vantas, Epaminondas Sidiropoulos

Rainfall time series analysis using clustering involves the identification of temporal patterns, with each data item representing an individual storm. This analysis results in clusters of data items that trend in a common way and can be utilized in s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b76d71269af5aca54f45f17482b9b0a4
https://doi.org/10.5194/egusphere-egu21-14758

Soil erosion modelling: a global review and statistical analysis

Autor: Marcella Biddoccu, Matjaž Mikoš, Stephen Owusu, Panos Panagos, Songchao Chen, Cristian Valeriu Patriche, Amelie Jeanneau, Aliakbar Nazari Samani, Manuel Esteban Lucas-Borja, Shuiqing Yin, Raquel de Castro Portes, Mahboobeh Kiani-Harchegani, Artemi Cerdà, Laura Poggio, Bifeng Hu, Peter Fiener, Mark A. Nearing, Diogo Noses Spinola, Michele Freppaz, Francis Matthews, Jantiene Baartman, Walter W. Chen, Pablo Alvarez, Konstantinos Kaffas, Nejc Bezak, Pasquale Borrelli, Anna Maria De Girolamo, Guangju Zhao, Andreas Gericke, Nikolaos Efthimiou, Changjia Li, Hyuck Soo Kim, Konstantinos Vantas, Paulo Tarso Sanches de Oliveira, Sergio Saia, Luigi Lombardo, Nazzareno Diodato, Nigussie Haregeweyn, Michael Märker, Gizaw Desta Gessesse, Jesús Rodrigo-Comino, Jae E. Yang, Victoria Naipal, Markus Möller, Cristiano Ballabio, Christine Alewell, Detlef Deumlich, Resham Thapa, Devraj Chalise, Vasileios Syrris, Chiyuan Miao, Manuel López-Vicente, Francesco Gentile, Laura Quijano, Diana Vieira, Sirio Modugno, Gunay Erpul, Calogero Schillaci, Mohammed Renima, Edouard Patault, Giovanni Francesco Ricci, Jamil Alexandre Ayach Anache, Demetrio Antonio Zema, Mohammad Reza Rahdari, Dinesh Panday, Hongfen Teng, Ivan Lizaga Villuendas

Publikováno v: Science of the Total Environment, 780, Art.-Nr.: 146494
Science of the Total Environment, 780
Science of the Total Environment
Science of the Total Environment, Elsevier, 2021, 780, pp.146494. ⟨10.1016/j.scitotenv.2021.146494⟩
Science of the total environment 780 (2021). doi:10.1016/j.scitotenv.2021.146494
info:cnr-pdr/source/autori:Borrelli P.; Alewell C.; Alvarez P.; Anache J.A.A.; Baartman J.; Ballabio C.; Bezak N.; Biddoccu M.; Cerda A.; Chalise D.; Chen S.; Chen W.; De Girolamo A.M.; Gessesse G.D.; Deumlich D.; Diodato N.; Efthimiou N.; Erpul G.; Fiener P.; Freppaz M.; Gentile F.; Gericke A.; Haregeweyn N.; Hu B.; Jeanneau A.; Kaffas K.; Kiani-Harchegani M.; Villuendas I.L.; Li C.; Lombardo L.; Lopez-Vicente M.; Lucas-Borja M.E.; Marker M.; Matthews F.; Miao C.; Mikos M.; Modugno S.; Moller M.; Naipal V.; Nearing M.; Owusu S.; Panday D.; Patault E.; Patriche C.V.; Poggio L.; Portes R.; Quijano L.; Rahdari M.R.; Renima M.; Ricci G.F.; Rodrigo-Comino J.; Saia S.; Samani A.N.; Schillaci C.; Syrris V.; Kim H.S.; Spinola D.N.; Oliveira P.T.; Teng H.; Thapa R.; Vantas K.; Vieira D.; Yang J.E.; Yin S.; Zema D.A.; Zhao G.; Panagos P./titolo:Soil erosion modelling: A global review and statistical analysis/doi:10.1016%2Fj.scitotenv.2021.146494/rivista:Science of the total environment/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume:780
Digital.CSIC. Repositorio Institucional del CSIC
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Digital.CSIC: Repositorio Institucional del CSIC
Consejo Superior de Investigaciones Científicas (CSIC)
The Science of the Total Environment
Science of the Total Environment 780 (2021)

40 Pags.- 10 Figs.- 2 Tabls.- Suppl. Informat. The definitive version is available at: https://www.sciencedirect.com/science/journal/00489697
To gain a better understanding of the global application of soil erosion prediction models, we comprehe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be04d5a0be5984db4d4c98016e8b2125
https://opus.bibliothek.uni-augsburg.de/opus4/files/84600/1-s2.0-S004896972101562X-main.pdf

Multiple statistical comparisons

Autor: Konstantinos Vantas

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ee46d03b773f67e501a305eb6a39e1ea
https://doi.org/10.5194/hess-2020-173-sc1