A hybrid fuzzy frequency factor based methodology for analyzing the hydrological drought

Papadopoulos, Christopher; Spiliotis, Mike; Angelidis, Panagiotis; Papadopoulos, Basil K.

doi:10.5004/dwt.2019.24549

Cited by 7 publications

(9 citation statements)

References 13 publications

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“…When h ¼ 0, the total fuzziness is taken into account. It is proved (Ubale & Sananse 2016;Papadopoulos et al 2019) that the above measure G takes into account both the Euclidean distance between the central value and the left-right boundaries, and the (double) Euclidean distance between the central value and the observation for all points in time. It is highlighted that in the fuzzy least-squares model suggested by Diamond (1988), the measure G is used as a function which is minimized.…”

Section: Fuzzy Linear Regression Based On Tanaka's Modelmentioning

confidence: 99%

“…It is mentioned that in all cases, the output of the fuzzy linear regression models is a fuzzy number. Papadopoulos et al (2019) use the G as an objective function into the fuzzy linear regression model of Tanaka (1987) thus taking additionally into account the inclusion constraints.…”

Section: Fuzzy Linear Regression Based On Tanaka's Modelmentioning

confidence: 99%

“…The maximum value of Equation ( 19) is the unit, since g WT i $ WT obs i , which is always possible for α h, as aforementioned, according to the inclusion constraints of the Tanaka model. It is noted that Papadopoulos et al (2019) use a similar suitability measure by taking into account the Euclidean distance between the observed value and the values of the produced fuzzy output (left-right boundaries and central value) in the case of strong zero-cut, and thus, the measure is a crisp number.…”

Section: Fuzzy Linear Regression Based On Tanaka's Modelmentioning

confidence: 99%

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Fuzzy linear regression analysis for groundwater response to meteorological drought in the aquifer system of Xanthi plain, NE Greece

Papadopoulos

Spiliotis

Gkiougkis

et al. 2021

Journal of Hydroinformatics

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This paper studies, through the principles of fuzzy set theory, groundwater response to meteorological drought in the case of an aquifer system located in the plains at the southeast of Xanthi, NE Greece. Meteorological drought is expressed through standardized Reconnaissance Drought Index (RDISt) and Standardized Precipitation Index (SPI), which are calculated for various reference periods. These drought indices are considered as independent variables in multiple fuzzy linear regression based on Tanaka's model, while the observed water table regarding two areas is used as a dependent variable. The fuzzy linear regression of Tanaka is characterized by the inclusion constraints where all the observed data must be included in the produced fuzzy band. Hence, each fuzzy output can get an interval of values where a membership degree corresponds to each of them. A modification of the Tanaka model by adding constraints is proposed in order to avoid irrational behavior. The results show that there was a significant influence of the meteorological drought of the previous hydrological year, while geology plays an important role. Furthermore, the use of RDISt improves the results of fuzzy linear regressions in all cases. Two suitability measures and a measure of comparison between fuzzy numbers are used.

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Section: Fuzzy Linear Regression Based On Tanaka's Modelmentioning

confidence: 99%

Section: Fuzzy Linear Regression Based On Tanaka's Modelmentioning

confidence: 99%

Section: Fuzzy Linear Regression Based On Tanaka's Modelmentioning

confidence: 99%

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Fuzzy linear regression analysis for groundwater response to meteorological drought in the aquifer system of Xanthi plain, NE Greece

Papadopoulos

Spiliotis

Gkiougkis

et al. 2021

Journal of Hydroinformatics

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“…In general, the fuzzy regression analysis gives a fuzzy functional relationship between the dependent and independent variables [2,3]. In contrast to the statistical regression, the fuzzy regression model of Tanaka [1] has no error term, while the uncertainty is incorporated into the model with the use of fuzzy numbers [4,5]. The data of the fuzzy regression can be either fuzzy or crisp.…”

Section: Introductionmentioning

confidence: 99%

“…Papadopoulos et al and Spiliotis et al [5,6] proposed a fuzzy hybrid frequency factor-based method, with the use of fuzzy regression, in order to improve the couple between the theoretical and the observed probability distributions. These articles deal with either annual cumulative streamflow or precipitation.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Couple between the Historical Sample and the Theoretical Probability Distributions for Maximum flow Values Based on a Fuzzy Methodology

Saridakis

Spiliotis

Angelidis

et al. 2020

The 4th EWaS International Conference: Valuing the Water, Carbon, Ecological Footprints of Human Activities

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In this article, an adjustment of the extreme theoretical probability distributions upon the sample is proposed, based on the conventional fuzzy linear regression model of Tanaka [1], where all the data must be included within the produced fuzzy band. This is achieved by using the quintile approach, which relates the observed return period with the theoretical cumulative probability. A new contribution of this work is the use of the fuzzified maximum likelihood, as a measure of goodness of fit. The model is applied for real data from the Strymonas River, regarding the annual maximum flow, and finally, useful conclusions are made.

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Regional classification of extreme droughts across Iran

Fathian,

Dehghan,

Alee

et al. 2023

Acta Geophys.

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A hybrid fuzzy frequency factor based methodology for analyzing the hydrological drought

Cited by 7 publications

References 13 publications

Fuzzy linear regression analysis for groundwater response to meteorological drought in the aquifer system of Xanthi plain, NE Greece

Fuzzy linear regression analysis for groundwater response to meteorological drought in the aquifer system of Xanthi plain, NE Greece

Assessment of the Couple between the Historical Sample and the Theoretical Probability Distributions for Maximum flow Values Based on a Fuzzy Methodology

Regional classification of extreme droughts across Iran

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