Information Model for Evaluation and Selection of Instructor Pilots for Smart City Urban Air Mobility

Rozenberg, Róbert; Szabó, Stanislav; Polishchuk, Valentin; Nemethova, Helia; Jevcak, J.; Choma, Ladislav; Келемен, Мартін; Vuković, Danijel

doi:10.23919/splitech49282.2020.9243702

Cited by 2 publications

(6 citation statements)

References 15 publications

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“…In [36], a hybrid gray model of multiple-criteria decision-making methods for personnel selection is proposed, which allows for eliminating the vagueness of the input information. Only [37,38] solve the task of supporting decision-making for the management of a smart city regarding the evaluation and selection of experts. The aim of [37] was to develop a methodology for assessing and selecting instructor pilots for smart city UAM Urban Air Mobility, based on the principles of fuzzy mathematics and using different information criteria and competency models.…”

Section: Overview Of Domestic and Foreign Research Studiesmentioning

confidence: 99%

“…Only [37,38] solve the task of supporting decision-making for the management of a smart city regarding the evaluation and selection of experts. The aim of [37] was to develop a methodology for assessing and selecting instructor pilots for smart city UAM Urban Air Mobility, based on the principles of fuzzy mathematics and using different information criteria and competency models. A feature of [38] is the general fuzzy model of evaluation and selection of a group of experts (teams) for smart urban transport and mobility.…”

Section: Overview Of Domestic and Foreign Research Studiesmentioning

confidence: 99%

“…We present a fuzzy model for assessing the competence of specialists, M 1 [37,38]. At the first stage, it is necessary to select evaluation models and calculate the number of points scored.…”

Section: Fuzzy Hybrid and Neuro-fuzzy Models For Assessing The Competence Of Smart City Specialistsmentioning

confidence: 99%

“…For the model m 1 , the DM chooses one of the values of the thinking strategies of the specialist, or a combination thereof, according to the proposed characteristic function [37]:…”

Section: Fuzzy Hybrid and Neuro-fuzzy Models For Assessing The Competence Of Smart City Specialistsmentioning

confidence: 99%

“…If there is no need to set weights, then we accept them as equally important. For further calculations, we carry out their rationing [37]:…”

Section: Fuzzy Hybrid and Neuro-fuzzy Models For Assessing The Competence Of Smart City Specialistsmentioning

confidence: 99%

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Model of Evaluation and Selection of Expert Group Members for Smart Cities, Green Transportation and Mobility: From Safe Times to Pandemic Times

et al. 2021

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This paper presents the development of technologies to support the decision-making of local government executives and smart city concept managers in selecting and evaluating the competencies of new members for advisory groups for solving problems that are implemented in safe times in individual areas or in crises, such as pandemics. The reason for developing effective urban transformation strategies and for the transparent selection of independent experts (non-politicians) for policymaking, decision-making, and implementation teams is not only the heterogeneity of smart city dimensions together with the necessary complexity and systems approach, but also the nature of the capacities and tools needed for smart city concepts. The innovative hybrid competency assessment model is based on fuzzy logic and a network for neuro-fuzzy assessment. It is a technological model for evaluating the competencies of specialists, taking into account the influence of human factors on the processes of personnel selection and system management. An innovative web platform named “Smart City Concept Personnel Selection” has been designed, which can be adapted to various users of municipalities or regional institutions for the transparent selection of qualified personnel for effective decision-making and the use of public funds during safe times or emergencies, such as the COVID-19 pandemic.

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Section: Overview Of Domestic and Foreign Research Studiesmentioning

confidence: 99%

Section: Overview Of Domestic and Foreign Research Studiesmentioning

confidence: 99%

Section: Fuzzy Hybrid and Neuro-fuzzy Models For Assessing The Competence Of Smart City Specialistsmentioning

confidence: 99%

“…For the model m 1 , the DM chooses one of the values of the thinking strategies of the specialist, or a combination thereof, according to the proposed characteristic function [37]:…”

Section: Fuzzy Hybrid and Neuro-fuzzy Models For Assessing The Competence Of Smart City Specialistsmentioning

confidence: 99%

“…If there is no need to set weights, then we accept them as equally important. For further calculations, we carry out their rationing [37]:…”

Section: Fuzzy Hybrid and Neuro-fuzzy Models For Assessing The Competence Of Smart City Specialistsmentioning

confidence: 99%

See 3 more Smart Citations

Model of Evaluation and Selection of Expert Group Members for Smart Cities, Green Transportation and Mobility: From Safe Times to Pandemic Times

et al. 2021

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Unmanned Aerial Vehicle Flight Risk Assessment Model for Environmental Research on Mountain Terrain

Polishchuk

Келемен

et al. 2021

2021 6th International Conference on Smart and Sustainable Technologies (SpliTech)

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Information Model for Evaluation and Selection of Instructor Pilots for Smart City Urban Air Mobility

Cited by 2 publications

References 15 publications

Model of Evaluation and Selection of Expert Group Members for Smart Cities, Green Transportation and Mobility: From Safe Times to Pandemic Times

Model of Evaluation and Selection of Expert Group Members for Smart Cities, Green Transportation and Mobility: From Safe Times to Pandemic Times

Unmanned Aerial Vehicle Flight Risk Assessment Model for Environmental Research on Mountain Terrain

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