Cost–volume–profit analysis under uncertainty: a model with fuzzy estimators based on confidence intervals

Chrysafis, Konstantinos A.; Papadopoulos, Basil K.

doi:10.1080/00207540802112660

Cited by 23 publications

(15 citation statements)

References 19 publications

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“…We obtained similar results to those we obtained in previous papers [12,22] investigating another Mediterranean lake-Lake Karla in Thessaly, which also has a hypertrophic character [16]. We used fuzzy linear regression for the construction of the parameters' fuzzy numbers [21][22][23][24] and compared the results with the method of fuzzy estimators. Similarly, we considered that the dependent variable was chlorophyll and all the others were independent.…”

Section: Discussionsupporting

confidence: 77%

The Use of Fuzzy Estimators for the Construction of a Prediction Model Concerning an Environmental Ecosystem

2019

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As a variable system, the Lake of Kastoria is a good example regarding the pattern of the Mediterranean shallow lakes. The focus of this study is on the investigation of this lake’s eutrophication, analyzing the relation of the basic factors that affect this phenomenon using fuzzy logic. In the method we suggest, while there are many fuzzy implications that can be used since the proposition can take values in the close interval [0,1], we investigate the most appropriate implication for the studied water body. We propose a method evaluating fuzzy implications by constructing triangular non-asymptotic fuzzy numbers for each of the studied parameters coming from experimental data. This is achieved with the use of fuzzy estimators and fuzzy linear regression. In this way, we achieve a better understanding of the mechanisms and functions that regulate this ecosystem.

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Section: Discussionsupporting

confidence: 77%

The Use of Fuzzy Estimators for the Construction of a Prediction Model Concerning an Environmental Ecosystem

2019

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“…In general, the methodology of fuzzy sets comprises a mapping from a general set X to the closed interval [0,1], which is described by its membership function [16]. Therefore, the above constraint can be easily achieved since the membership function takes values between zero and one.…”

Section: Topsis Methods Based On a Fuzzy Pattern Recognitionmentioning

confidence: 99%

Enhancement of Socioeconomic Criteria for the Assessment of the Vulnerability to Flood Events with the Use of Multicriteria Analysis

Skoulikaris

Papadopoulos

Spiliotis

et al. 2020

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

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The aim of the research is the re-assessment of the flood risk when the sensitivity criteria used to evaluate the vulnerability are enhanced with adaptive-recovery capacity criteria and the exposure. Hence, in the proposed methodology, the vulnerability to flooding is addressed as a synthesis between the adaptive-recovery capacity, the exposure, and the sensitivity. To do so, a multicriteria ranking is proposed. The multicriteria ranking is based on the fuzziness in order to interpret the multicriteria synthesis of the widely-used multicriteria technique for order preference by similarity to ideal solution (TOPSIS) method. The case study areas are the Greek parts of the Nestos and Strymonas transboundary river basins.

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“…In this paper this is achieved by the introduction of fuzzy estimators and more specifically with the so called a-cuts which are formally described in the next section. The method adopted in this research was originally developed and published in recent work by Tsironis et al (2010) and Chrysafis and Papadopoulos (2009). Upon detection of a DDoS attack, the next step would be to identify the offending hosts.…”

Section: Description Of the Proposed Methodsmentioning

confidence: 99%

Real time DDoS detection using fuzzy estimators

Shiaeles

Katos

Καράκος

et al. 2012

Computers & Security

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We propose a method for DDoS detection by constructing a fuzzy estimator on the mean packet inter arrival times. We divided the problem into two challenges, the first being the actual detection of the DDoS event taking place and the second being the identification of the offending IP addresses. We have imposed strict real time constraints for the first challenge and more relaxed constraints for the identification of addresses. Through empirical evaluation we confirmed that the detection can be completed within improved real time limits and that by using fuzzy estimators instead of crisp statistical descriptors we can avoid the shortcomings posed by assumptions on the model distribution of the traffic. In addition we managed to obtain results under a 3 sec detection window.

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Cost–volume–profit analysis under uncertainty: a model with fuzzy estimators based on confidence intervals

Cited by 23 publications

References 19 publications

The Use of Fuzzy Estimators for the Construction of a Prediction Model Concerning an Environmental Ecosystem

The Use of Fuzzy Estimators for the Construction of a Prediction Model Concerning an Environmental Ecosystem

Enhancement of Socioeconomic Criteria for the Assessment of the Vulnerability to Flood Events with the Use of Multicriteria Analysis

Real time DDoS detection using fuzzy estimators

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