Rainfall threshold definition using an entropy decision approach and  radar data

Montesarchio, Valeria; Ridolfi, Elena; Russo, Fabio; Napolitano, Francesco

doi:10.5194/nhess-11-2061-2011

Cited by 44 publications

(31 citation statements)

References 30 publications

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“…In the field of rainfallrunoff analysis, Pechlivanidis et al (2010) proposed an entropy-based measure for the rainfall-runoff model diagnostic, and Pechlivanidis et al (2012) extended the work evaluating the non-dynamical information contained in streamflow analysis; Montesarchio et al (2011) and Ridolfi et al (2013) defined rainfall threshold values minimizing a risk function based on the entropy concept. Weijs et al (2010) proposed a theoretical framework based on relative entropy involving the analysis of a divergence score measure to evaluate the quality of hydrological forecasts.…”

Section: Introductionmentioning

confidence: 99%

An entropy approach for the optimization of cross-section spacing for river modelling

Ridolfi

Alfonso

Baldassarre

et al. 2013

Hydrological Sciences Journal

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An accurate definition of river geometry is essential to implement one-dimensional (1D) hydraulic models and, in particular, appropriate spacing between cross-sections is key for capturing a river's hydraulic behaviour. This work explores the potential of an entropy-based approach, as a complementary method to existing guidelines, to determine the optimal number of cross-sections to support 1D hydraulic modelling. To this end, given a redundant collection of existing cross-sections, a location subset is selected minimizing total correlation (as a measure of redundancy) and maximizing joint entropy (as a measure of information content). The problem is posed as a multiobjective optimization problem and solved using a genetic algorithm: the Non-dominated Sorting Genetic Algorithm (NSGA)-II. The proposed method is applied to a river reach of the Po River (Italy) and compared to standard guidelines for 1D hydraulic modelling. Cross-sections selected through the proposed methodology were found to provide an accurate description of the flood water profile, while optimizing computational efficiency.Key words cross-sections; heuristic entropy; hydraulic modelling; one-dimensional flow; network optimization; genetic algorithm; NGSA-II Une approche fondée sur l'entropie pour l'optimisation de l'espacement entre sections en travers pour la modélisation en riviére Résumé Une définition précise de la géométrie de la riviére est essentielle pour mettre en oeuvre des modéles hydrauliques unidimensionnels (1D). L'espacement approprié entre les sections en travers de la riviére est un élément clé pour reproduire son comportement hydraulique. Ce travail a pour objectif de fournir une méthode se basant sur l'entropie, complémentaire des guides existants et permettant de fournir des informations supplémentaires pour l'optimisation des modéles hydrauliques 1D et la gestion des jeux de données sur les sections en travers. Plus spécifiquement, sur la base d'une collecte redondante de sites de sections en travers existantes, un sous-ensemble de sites est sélectionné en minimisant la corrélation totale (comme mesure de redondance) et en maximisant l'entropie conjointe (comme mesure du contenu en information). Le probléme est posé sous la forme d'une optimisation multi-objectif, résolue en utilisant un algorithme génétique (NSGA-II). Nous appliquons la méthode proposée aux données de sections en travers sur le Po, en Italie, et nous la comparons aux méthodes existantes en utilisant un modéle hydraulique 1D. Les jeux de sections en travers sélectionnées par la méthodologie proposée fournissent une description précise du profil des eaux en crue, tout en optimisant l'efficacité de calcul.Mots clefs sections en travers ; entropie heuristique ; modélisation hydraulique ; flux unidimensionnel ; optimisation de réseau, algorithme génétique ; NGSA-II 126

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Section: Introductionmentioning

confidence: 99%

An entropy approach for the optimization of cross-section spacing for river modelling

Ridolfi

Alfonso

Baldassarre

et al. 2013

Hydrological Sciences Journal

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“…To solve the problems of multi-attribute decision making under uncertainty, Yang et al [37] first proposed their expected utility-entropy (EU-E) model. Although the EU-E model has been applied in different fields, such as a decision-making model for large consumers on a smart grid [38], rainfall threshold analysis [39], stock selection [40], etc., few people could question the rationality of the EU-E model itself. Fischera [41] commented on Yang's model and pointed out its deficiencies, such as the impact of consequences was not considered for uncertainty analysis, however, it does not propose a reasonable alternative framework or model, but simply thinks that the EU model is enough to solve decision-making problems under uncertainty.…”

Section: Scheme Selection Under Multi-source Attributesmentioning

confidence: 99%

Entropy-Based Risk Control of Geological Disasters in Mountain Tunnels Under Uncertain Environments

Xia¹,

Xiong²,

Hao³

et al. 2018

Preprint

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Uncertainty is the main source of risk of geological hazards in tunnel engineering. Uncertainty information not only affects the accuracy of evaluation results, but also affects the reliability of decision-making schemes. Therefore, it is necessary to evaluate and control the impact of uncertainty on risk. In this study, the problems in existing entropy-hazard model such as inefficient decision-making and failure of decision-making are analysed, and an improved uncertainty evaluation and control process are proposed. Then the tolerance cost, the key factor in the decision-making model, is also discussed. It is considered that the amount of change in risk value (R 1 ) can better reflect the psychological behaviour of decision-makers. Thirdly, common attribute decision models, such as the expected utility-entropy model, are analysed, and then the viewpoint of different types of decision-making issues that require different decision methods is proposed. The well-known Allais paradox is explained by the proposed methods. Finally, the engineering application results show that the uncertainty control idea proposed here is accurate and effective. This research indicates a direction for further research into uncertainty, and risk control, issues affecting underground engineering works.

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“…Allahverdyan et al [35] derived a measure of risk similar to the EU-E measure of risk and concluded that their risk measure has normative features. The EU-E model has also been applied in other fields, such as a decision-making model for large consumers on a smart grid [36] and in rainfall threshold analysis [37].…”

Section: Introductionmentioning

confidence: 99%

Performance of Portfolios Based on the Expected Utility-Entropy Fund Rating Approach

Chiew

Qiu

Treepongkaruna

et al. 2019

The 5th International Electronic Conference on Entropy and Its Applications

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Yang and Qiu proposed and reframed an expected utility-entropy (EU-E) based decision model; later on, similar numerical representation for a risky choice was axiomatically developed by Luce et al. under the condition of segregation.Recently, we established a fund rating approach based on the EU-E decision model and Morningstar ratings. In this paper, we apply the approach to US mutual funds and construct portfolios using the best rated funds. Furthermore, we evaluate the performance of the fund ratings based on EU-E decision model against Morningstar ratings by examining the performance of the three models in portfolio selection. The conclusions show that portfolios constructed using the ratings based on the EU-E models with moderate tradeoff coefficients perform better than those constructed using Morningstar. The conclusion is robust to different rebalancing intervals.

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Rainfall threshold definition using an entropy decision approach and radar data

Cited by 44 publications

References 30 publications

An entropy approach for the optimization of cross-section spacing for river modelling

An entropy approach for the optimization of cross-section spacing for river modelling

Entropy-Based Risk Control of Geological Disasters in Mountain Tunnels Under Uncertain Environments

Performance of Portfolios Based on the Expected Utility-Entropy Fund Rating Approach

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