Applying ER-MCDA and BF-TOPSIS to Decide on Effectiveness of Torrent Protection

Carladous, Simon; Tacnet, Jean‐Marc; Dezert, Jean; Han, Deqiang; Batton‐Hubert, Mireille

doi:10.1007/978-3-319-45559-4_6

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…The analysis of each decision-making problem depends on the analysis of several criteria of which the assessment is imperfect and performed in an uncertain environment. Decision-aiding methods grounded on Evidential Reasoning as previously introduced are used to answer each of these problems (Carladous et al, 2015(Carladous et al, , 2016c, as shown in Fig. 9.…”

Section: Stage 3: Decision-aiding Methods For Each Problemmentioning

confidence: 99%

“…The objective of this article is to show how the use of new decisionaiding methods may be integrated into a formalised framework of analysis through the conceptual description of this analytical framework. This article does not aim at detailing mathematical aspects of such methods or at showing the real application of these individual methods on different sub-problems as already done elsewhere (Carladous et al, 2015(Carladous et al, , 2016c. Under this assumption, the Section 2 introduces the methods, didactically, without detailing calculation-intensive aspects but by justifying choices made.…”

Section: A Multi-scale Multi-component Decision-making Problem Based ...mentioning

confidence: 99%

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Managing protection in torrential mountain watersheds: A new conceptual integrated decision-aiding framework

Carladous

Tacnet²,

Batton‐Hubert

et al. 2019

Land Use Policy

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Section: Stage 3: Decision-aiding Methods For Each Problemmentioning

confidence: 99%

Section: A Multi-scale Multi-component Decision-making Problem Based ...mentioning

confidence: 99%

Managing protection in torrential mountain watersheds: A new conceptual integrated decision-aiding framework

Carladous

Tacnet²,

Batton‐Hubert

et al. 2019

Land Use Policy

View full text Add to dashboard Cite

“…As shown in this application example, our proposed distance measure can be well used in the multiple criterion decision making. d E BI has also been used successfully in other kind of applications related to risk management and for protecting housing areas against torrential floods in France [46], [47].…”

Section: K Application Of D E Bi In Multiple Criteria Decision Makingmentioning

confidence: 99%

Belief Interval-Based Distance Measures in the Theory of Belief Functions

Han

Dezert

Yang

2018

IEEE Trans. Syst. Man Cybern, Syst.

Self Cite

102

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In belief functions related fields, the distance measure is an important concept, which represents the degree of dissimilarity between bodies of evidence. Various distance measures of evidence have been proposed and widely used in diverse belief function related applications, especially in performance evaluation. Existing definitions of strict and nonstrict distance measures of evidence have their own pros and cons. In this paper, we propose two new strict distance measures of evidence (Euclidean and Chebyshev forms) between two basic belief assignments based on the Wasserstein distance between belief intervals of focal elements. Illustrative examples, simulations, applications, and related analyses are provided to show the rationality and efficiency of our proposed measures for distance of evidence. Index Terms-Belief interval, dissimilarity, distance of evidence, evidence theory, the theory of belief functions. I. INTRODUCTION T HE theory of belief functions, also called Dempster-Shafer evidence theory (DST) [1], is an important mathematical framework for uncertainty modeling and reasoning. It has been applied to information fusion [2], pattern recognition [3], [4], multiple-attribute decision making [5], fault diagnosis [6], etc. DST has some limitations (see [7]-[9] for discussions). Generalized or refined theories were proposed including transferable belief model [10] and Dezert-Smarandache theory [7], [11], etc. In DST, the basic belief assignment (BBA) is a common way for modeling (epistemic) uncertainty. The distance of evidence is a crucial metric for measuring the distance between Manuscript

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Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index

Abdullah

Zainol

Thian

et al. 2022

BDCC

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The impact of Big Data (BD) creates challenges in selecting relevant and significant data to be used as criteria to facilitate flood management plans. Studies on macro domain criteria expand the criteria selection, which is important for assessment in allowing a comprehensive understanding of the current situation, readiness, preparation, resources, and others for decision assessment and disaster events planning. This study aims to facilitate the criteria identification and selection from a macro domain perspective in improving flood management planning. The objectives of this study are (a) to explore and identify potential and possible criteria to be incorporated in the current flood management plan in the macro domain perspective; (b) to understand the type of flood measures and decision goals implemented to facilitate flood management planning decisions; and (c) to examine the possible structured mechanism for criteria selection based on the decision analysis technique. Based on a systematic literature review and thematic analysis using the PESTEL framework, the findings have identified and clustered domains and their criteria to be considered and applied in future flood management plans. The critical review on flood measures and decision goals would potentially equip stakeholders and policy makers for better decision making based on a disaster management plan. The decision analysis technique as a structured mechanism would significantly improve criteria identification and selection for comprehensive and collective decisions. The findings from this study could further improve Malaysia Adaptation Index (MAIN) criteria identification and selection, which could be the complementary and supporting reference in managing flood disaster management. A proposed framework from this study can be used as guidance in dealing with and optimising the criteria based on challenges and the current application of Big Data and criteria in managing disaster events.

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Applying ER-MCDA and BF-TOPSIS to Decide on Effectiveness of Torrent Protection

Cited by 3 publications

References 15 publications

Managing protection in torrential mountain watersheds: A new conceptual integrated decision-aiding framework

Managing protection in torrential mountain watersheds: A new conceptual integrated decision-aiding framework

Belief Interval-Based Distance Measures in the Theory of Belief Functions

Big Data in Criteria Selection and Identification in Managing Flood Disaster Events Based on Macro Domain PESTEL Analysis: Case Study of Malaysia Adaptation Index

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