Cargando…
Comparing causal techniques for rainfall variability analysis using causality algorithms in Iran
Causal analysis (CA) is a strong quantitative approach whose mechanisms have climatic predictions. In this study, we studied the patterns of causality (PC) on the effect of rainfall (ER) using climatic series collected from 170 stations for the period 1975–2014 in Iran. Next, we predicted the causal...
Autor principal: | Javari, Majid |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138950/ https://www.ncbi.nlm.nih.gov/pubmed/30225376 http://dx.doi.org/10.1016/j.heliyon.2018.e00774 |
Ejemplares similares
-
Daily rainfall nearest neighbor pattern using point data series in Iran
por: Javari, Majid
Publicado: (2018) -
Free variables and local causality
por: Bell, John Stewart
Publicado: (1985) -
Free variables and local causality
por: Bell, J S
Publicado: (1977) -
Causal graph extraction from news: a comparative study of time-series causality learning techniques
por: Maisonnave, Mariano, et al.
Publicado: (2022) -
causalizeR: a text mining algorithm to identify causal relationships in scientific literature
por: Ancin-Murguzur, Francisco J., et al.
Publicado: (2021)