A Neutrosophic Decision-Making Model for Determining Young People's Active Engagement

被引:0
|
作者
Colhon, Mihaela [1 ]
Tilea, Monica [2 ]
Gonzalez-Marcos, Ana [3 ]
Resceanu, Alina [4 ]
Smarandache, Florentin [5 ]
Navaridas-Nalda, Fermin [6 ]
机构
[1] Univ Craiova, Dept Comp Sci, 13 Al I Cuza St, Craiova, Romania
[2] Univ Craiova, Dept Romance & Class Languages, 13 Al I Cuza St, Craiova, Romania
[3] Univ La Rioja, Mech Engn Dept, 93 Ave La Paz, Logrono, Spain
[4] Univ Craiova, Dept British, Amer & German Studies, 13 Al I Cuza St, Craiova, Romania
[5] Univ New Mexico, Dept Math, 705 Gurley Ave, Gallup, NM 87301 USA
[6] Univ La Rioja, Dept Educ, 93 Avenida La Paz, Logrono, Spain
关键词
Neutrosophic representation; decision-making model; attribute selection; uncertainty reasoning; questionnaire analysis; youth engagement; INTUITIONISTIC FUZZY-SETS;
D O I
10.1142/S0219622023500384
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Young people's skills and attitudes must be observed, studied and evaluated in order to create appropriate models that would serve an educational purpose. In this paper, we propose a decision-making model with the aim to detect certain attitudinal and behavioral patterns of actively engaged young people. The data used in this research resulted from a questionnaire drawn up by a group of researchers from six European countries with the aim to investigate the youth's awareness about the Sustainable Development Goals and their engagement as active agents of development and change at regional level. For the purpose of this study, we selected the regional results obtained from administering this questionnaire in Dolj County (Romania) and La Rioja (Spain). We developed a neutrosophic model that determines the Mindchanger profile of the respondents based on a minimal set of questions, which is dependent on the inclusion or exclusion of the nationality-specific traits. The resulting decisions were then compared with the respondents' self-evaluations, yielding high precisions (more than 0.83) for all the investigated evaluation scenarios. Our results were significantly better than the ones provided by several machine learning models applied on the same set of data. A direct impact of our model is that it can be applied to questionnaires which include linguistic responses that express, among others, unclear or vague thoughts. Additionally, it offers the possibility to identify the minimal set of questions that impact the respondent's answer choice to a target question.
引用
收藏
页码:569 / 598
页数:30
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