BeCoMe: Easy-to-implement optimized method for best-compromise group decision making: Flood-prevention and COVID-19 case studies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F21%3A83860" target="_blank" >RIV/60460709:41110/21:83860 - isvavai.cz</a>

Výsledek na webu

<a href="https://authors.elsevier.com/c/1cHxZ4sKhEP01K" target="_blank" >https://authors.elsevier.com/c/1cHxZ4sKhEP01K</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.envsoft.2020.104953" target="_blank" >10.1016/j.envsoft.2020.104953</a>

Jazyk výsledku

angličtina

Název v původním jazyce

BeCoMe: Easy-to-implement optimized method for best-compromise group decision making: Flood-prevention and COVID-19 case studies

Popis výsledku v původním jazyce

Vrana et al. (2012a) presented the maximum-agreement-mean (MaxAgM) method, which aggregates expert opinions while focusing on points of agreement. Although MaxAgM can minimize Shannon entropy to optimize results, it has a high level of computational and conceptual complexity, yields difficult-to-interpret results, has no indicator of accuracy, and requires specialized software that is not widely available. In this paper, we present the best-compromise-mean (BeCoMe) method as a modified MaxAgM method. BeCoMe preserves the advantages of MaxAgM, but overcomes its limitations. To enable direct comparison, we applied the BeCoMe method to the same flood-prevention case study that was used to validate the original MaxAgM method. BeCoMe is a universal method, as it can be applied to evaluate environmental and educational measures, about pandemics, industries and resource issues. Here, we demonstrate the applicability of BeCoMe in real-life COVID-19 case study decisions which needed to be rapidly and efficien

Název v anglickém jazyce

BeCoMe: Easy-to-implement optimized method for best-compromise group decision making: Flood-prevention and COVID-19 case studies

Popis výsledku anglicky

Vrana et al. (2012a) presented the maximum-agreement-mean (MaxAgM) method, which aggregates expert opinions while focusing on points of agreement. Although MaxAgM can minimize Shannon entropy to optimize results, it has a high level of computational and conceptual complexity, yields difficult-to-interpret results, has no indicator of accuracy, and requires specialized software that is not widely available. In this paper, we present the best-compromise-mean (BeCoMe) method as a modified MaxAgM method. BeCoMe preserves the advantages of MaxAgM, but overcomes its limitations. To enable direct comparison, we applied the BeCoMe method to the same flood-prevention case study that was used to validate the original MaxAgM method. BeCoMe is a universal method, as it can be applied to evaluate environmental and educational measures, about pandemics, industries and resource issues. Here, we demonstrate the applicability of BeCoMe in real-life COVID-19 case study decisions which needed to be rapidly and efficien

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Environmental Modelling & Software

ISSN

1364-8152

e-ISSN

1364-8152

Svazek periodika

136

Číslo periodika v rámci svazku

104953

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

17

Strana od-do

1-17

Kód UT WoS článku

000616065900001

EID výsledku v databázi Scopus

2-s2.0-85098674261