Trend Identification Simulation and Application

By Zekâi Sen. 2014

300 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/9476d615e4bc5937587365fe0c7f0ea4a6d4a777

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Citations in the corpus

Innovative trend significance test and applications (2017, background): “…records (Hirsch et al. 1982; van Belle andHughes 1984; Hirsch and Slack 1984; Cailas et al. 1986; Hipel et al. 1988; Demaree and Nicolis 1990; Yu et al. 1993; Gan 1998; Taylor and Loftis 1989; Lins and Slack 1999; Douglas et al. 2000; Hamilton et al. 2001; Kalra et al. 2008).”
Innovative Trend Methodology Applications to Precipitation Records in Turkey (2017, methodology): “The main purpose of this paper is to apply asn innovative trend analysis methodology principles as suggested by Şen (2012, 2014) for identification not the monotonic and holistic trend but partial trend components in “low”, “medium” and “high” data values.”
Identification of sub-trends from hydro-meteorological series (2015, background): “For only the years 2013–2014, examples of studies related to the said changes include Lavender and Abbs (2013), Nyeko-Ogiramoi et al. (2013), Paruolo et al. (2014), Şen (2014), Tao et al. (2014).”
Trend Assessment by the Innovative-Şen Method (2016, background): “…and Shanley 2006; Feidas et al. 2007;Wu et al. 2008; Cong et al. 2009; Proutsos et al. 2010; Yin et al. 2010; Morin 2011; Kliment et al. 2011; Tabari et al. 2012; Yavuz and Erdoğan 2012; Shadmani et al. 2012; Çeribaşı et al. 2013; Gebremicael et al. 2013; Liu and Zhang 2013; Eregno et al.…”
An improved version of innovative trend analyses (2018, background): “On the other hand, Şen (2012, 2014, 2017b) proposed an ITA method, which does not need restrictive assumptions and ensures visual inspection possibility about trend existence.”
Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches (2020, methodology): “If the data is being plotted above the 1:1 line, it will state that the moment series shows an increasing trend, and if the data falls under the 1:1 line, it will indicate the negative trend 56,58 .”