Modeling of Scientific Publications Disciplinary Collocation Based on Optimistic Fuzzy Aggregation Norms

Sokołov, Oleksandr; Osińska, Wiesława; Mreła, Aleksandra; Duch, Włodzisław

doi:10.1007/978-3-319-99996-8_14

Cited by 6 publications

(6 citation statements)

References 7 publications

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“…Scientists build their scientific profiles in only one or a few disciplines or scientific fields, and scientometricians try to find factors to estimate their contribution to a specific discipline or a field. One of the models of computer systems for calculating the contribution to research areas in computer science is presented in [15]. Moreover, bibliometricians try to visualize the scientist's contribution to disciplines based on published articles and journals' profiles by choosing the weights of examined fields empirically [16].…”

Section: Discussionmentioning

confidence: 99%

Multi-agent model of trust dissemination based on optimistic and pessimistic fuzzy aggregation norms

Mreła¹,

Соколов²,

Bieniek-Majka³

et al. 2022

Annals of Computer Science and Information Systems

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Companies and even institutions have recently tried to form a reasonable opinion about their products. One way companies can achieve this is to prepare and distribute advertisements. Some advertising media, such as TV commercials, are costly and tiresome, so understanding and modeling some aspects of disseminating product information might be helpful. The article presents a multi-agent model of spreading trust in the product among agents based on fuzzy aggregation norms. When people with a similar opinion about a product discuss it with others or listen to a commercial, their trust increases, so the optimistic fuzzy aggregation norm is applied. When people with different opinions meet, their faith decreases, so the pessimistic norm is applied. In addition, the paper presents a theoretical example of this model application, namely, showing the results of a multi-agent model of spreading confidence in the product and presenting the results of the NetLogo simulation.

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Section: Discussionmentioning

confidence: 99%

Multi-agent model of trust dissemination based on optimistic and pessimistic fuzzy aggregation norms

Mreła¹,

Соколов²,

Bieniek-Majka³

et al. 2022

Annals of Computer Science and Information Systems

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“…Table 3 presents the part of relation: Since it is more interesting to study the RES of groups of people, not individuals, some aggregation methods have to be applied. The authors selected the optimistic fuzzy aggregation norm S defined in (Sokolov et al 2019).…”

Section: Methodsmentioning

confidence: 99%

The importance of the renewable energy sector in the opinion of rural and urban youth

Cichowska¹,

Mreła²,

Sokołov³

2021

Polityka Energetyczna – Energy Policy Journal

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The growing interest in green energy observed in recent years has become the basis for pilot studies on its electricity production role in Poland. The diagnostic survey method allowed us to learn about young people's opinions on renewable energy sources in the context of four identified research areas (the need for RES, planning its installation, costs, environmental impact). The authors proposed a method based on fuzzy logic (fuzzy relations and optimistic fuzzy aggregation norms) to develop and interpret the survey results to understand the selected community's knowledge about the importance of RES (or not) in the national energy system. The survey shows that although there is no significant difference between respondents in all research areas, rural women are more interested in using green technologies. They have a high self-awareness of their beneficial effects on the environment. Rural respondents, compared to those from the cities, are willing (despite the high cost of equipment) to invest their capital to purchase green energy carriers, which is dictated by their lower knowledge about the forms of external support. Depending on the residence place, re-spondents selected various government aid programs for renewable energy. People from the city decided mainly on those that would improve the air's comfort and quality in their place of residence. On the other hand, the rural areas' inhabitants focused their attention on the aid possibilities, which would reduce the energy costs of the farms they run in the future. All the respondents agree that investments in clean energy (coming from natural sources) will translate into broadly understood environmental protection, bringing mutual benefits for everyone.

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“…However, to find levels of education quality in these areas, one of the aggregation methods has to be applied. The authors have chosen the optimistic fuzzy aggregation norm S, which was defined in [23].…”

Section: Denotes the Level Of Area Qualitymentioning

confidence: 99%

Bulletin of the Polish Academy of Sciences: Technical Sciences

Śmigielski,

Mreła,

Sokolov

et al. 2021

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All universities are responsible for assessing the quality of education. One of the required factors is the results of the students' research. The procedure involves, most often, the preparation of the questionnaire by the staff, which is voluntarily answered by students; then, the university staff uses the statistical methods to analyze data and prepare reports. The proposed EQE method by the application of the fuzzy relations and the optimistic fuzzy aggregation norm may show a closer connection between the students' answers and the achieved results. Moreover, the objects obtained by the application of the EQE method can be visualized by using the t-SNE technique, cosine between vectors and distances of points in five-dimensional space.

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Modeling of Scientific Publications Disciplinary Collocation Based on Optimistic Fuzzy Aggregation Norms

Cited by 6 publications

References 7 publications

Multi-agent model of trust dissemination based on optimistic and pessimistic fuzzy aggregation norms

Multi-agent model of trust dissemination based on optimistic and pessimistic fuzzy aggregation norms

The importance of the renewable energy sector in the opinion of rural and urban youth

Bulletin of the Polish Academy of Sciences: Technical Sciences

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